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Simple kinetic models of petroleum formation Part III: modelling an open system Andrew S. Pepper & Peter J. Corvi Abstract The movement of petroleum from organic-rich source beds to potential carrier beds is the net result of two processes: expulsion - the release of generated petroleum from kerogen within the source bed; and primary migration - flow of a petroleum phase through the inorganic void networks of the source bed and all other intervening fine grained rocks. Expulsion is by far the more important process within the source bed. ORGAS, a simple zero-dimensional model of the source rock as an open system, explicitly models expulsion, concurrent with oil and gas generation and oil-gas cracking, as a storage/threshold problem. Oil and gas are retained (adsorbed / absorbed) within kerogen until their concentrations exceed the respective sorptive capacity of the residual organic carbon (0.1 and 0.02 g gCK-1). Initial Hydrogen Index (HI0) controls the important balance between potential sorbate (petroleum) and sorbant (residual carbon). Using simple geochemical measurements, we divide initial organic carbon into: initial oil, inert kerogen, and oil- and gas-generative (reactive) kerogen components. Reactive kerogens are assigned to one of five global kinetic Organofacies with pre-determined kinetic parameter sets governing separately rates of oil and gas-generation. Kinetic parameters governing rates of oil cracking within the source rock are predicted from HI0. The two most important determinants of source rock behaviour are Organofacies and HI0. At a reference constant heating rate 2 oC Ma-1, the projected oil expulsion threshold for typical Organofacies members increases in the order A-DE: 100, 110, 120, 135 oC; F typically expels no oil. An order of magnitude increase (decrease) in heating rate increases (decreases) these thresholds by ca. 15 oC. Typical cumulative gas mass fractions in their ultimate expulsion products are (A-F): 0.25, 0.3, 0.25, 0.65 and 1.0 g g-1. 200 mgHC gC-1 is an approximate minimum HI0 pre-requisite for oil expulsion, irrespective of absolute petroleum potential (P0). As a family, coals vary dramatically in their expulsion behaviour since their HI0 ranges both above and below this value. Primary migration is efficient: for expulsive source rocks, movement within the source bed is limited only at low P0. A source rock's total genetic potential (P0, thickness) becomes important during migration outside the source bed: it potentially restricts the primary migration

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distance, and the excess of petroleum available for secondary migration and entrapment. We evaluate primary migration approximately using a small migration loss factor (no more than about 10% saturation of porosity or 1 mg/g), coupled with an understanding of fluid potential gradients which determine migration direction within the stratigraphic architecture. Ultimately, kerogen degradation and oil-to-gas cracking in the source rock are the rate-limiting processes in petroleum accumulation. Keywords: source rock; coal; coal-bed methane; modelling; generation; oil-gas cracking; kinetics; sorption; expulsion; primary migration; petroleum; oil; gas; hydrocarbons; Central Sumatra Basin. Introduction In exploration, quantitative petroleum geochemistry aims to predict the mass, composition and timing of petroleum charge reaching the trap, and the phase state of the emplaced petroleum. During appraisal, reservoir studies can also benefit from an understanding of how, when and from where petroleum entered. Reservoir filling rates are ultimately limited by rates of processes in the source bed (England et al., 1991). There are three fundamental intra-source processes (Figure 1):

• Part I of this trilogy, in this issue (Pepper and Corvi, 1995), describes a kinetic model for generation of petroleum (oil and gas) from sedimentary organic matter (SOM);

• Part II, also in this issue (Pepper and Dodd, 1995), described a kinetic model for oil-to-gas cracking;

• this third Part describes how these are integrated with a model of petroleum release from the source bed, involving the processes of expulsion (Pepper, 1989 and 1991) and primary migration.

Comprehensive models of petroleum formation require quantitative understanding of the complex mutual interplay of physical and chemical processes involved in this seemingly simple reaction scheme. However, these processes are arranged in order of decreasing understanding and consensus among petroleum geochemists.

Generation rates are most easily and reliably quantified, since field and laboratory data can be combined in the calibration (Part I). Fortunately for the petroleum industry, source rocks are to a greater or lesser degree open systems; however this means that oil-gas cracking can only be studied in the laboratory (Part II): results must be extrapolated to the field. Petroleum release is the most difficult process to model because realistic laboratory simulation is difficult and proposed mechanisms are almost as numerous as the field observations themselves. Despite these obvious uncertainties, the need for open system modelling is compelling: in conventional petroleum exploitation (i.e. excluding oil-shale and coal-bed methane), the prize is represented by the petroleum that leaves the rock, not that which remains within it.

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Figure 1 General scheme of processes governing petroleum charge from a source rock; expulsion in our model is defined specifically as release of petroleum into the inorganic void space.

Earlier BP models developed by Cooles et al. (1986), Quigley et al. (1987) and Quigley and Mackenzie (1988) were deliberately simple, forming an integral part of a geochemical prospect evaluation methodology intended for use by the non-specialist (Mackenzie and Quigley, 1988). This paper presents the ORGAS (oil or gas?) model, developed in 1988-89 at the BP Research Centre. ORGAS remains essentially simple: in our exploration experience, complex models requiring many input variables, many of which end up being "guessed", are of limited value.

The paper has five main sections. Because ORGAS differs in approach from many published alternatives, Sections I and II review the processes involved in release of generated petroleum from source beds: expulsion and primary migration. Section III describes the open system (expulsion) model: important inputs; simple parts of the algorithm required to understand the basic concepts; resulting projections of source rock behaviour; and model testing. We also revisit a published case history, assessing the petroleum prospectivity of some Indonesian coals. Section IV discusses primary migration, which is evaluated outside the ORGAS model. Studies of petroleum release Past approaches to the problem have been both heuristic and deterministic.

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Heuristic approaches attempt to establish simple rules from observations (Cooles et al., 1986; Mackenzie and Quigley, 1988): various case studies have estimated source beds' petroleum release efficiency (PRE; our terminology) using a carbon mass balance which compares mature source samples with their immature equivalents (Cooles et al. 1986, Larter, 1988; Rullkoetter et al., 1988; Pepper, 1991). Some oil-generative source beds can have release efficiency of 0.8 - 0.9 (i.e. 80-90%).

Cooles et al. (1986) studied ten thick and relatively homogeneous aquatic source rocks and found an apparent dependency of release efficiency upon initial petroleum potential P0 (= [S10 + S20] or [P10 + P20]) yield from Rock-Eval type pyrolysis of immature SOM; Espitalie et al., 1977). Mackenzie and Quigley (1988) formalised these observations (Figure 2a):

• PRE is high (commonly exceeding 0.6 during oil generation) when P0 exceeds ca. 0.005 g g-1 (i.e. 5 mg g-1 or kg tonne-1);

• release is inefficient (PRE less than 0.4 during oil generation) when P0 is less than 0.005 g g-1.

Empirical correlations are often unreliable outside the calibrant data range:

Pepper's (1991) expanded study of 20 source rocks, including coals (Figure 2b) showed that the correlation apparent in Figure 2a does not extend to very high P0. Rather, on Figure 2c there is a more robust correlation with initial Hydrogen Index HI0 (= S20 normalised to organic carbon). Ironically, the significance of this observation may have been overlooked because during the last two decades petroleum geochemists - for sound economic reasons - have focussed study on rich and high quality source rocks which release their petroleum efficiently, providing little insight as to the underlying controls (i.e. P0 or HI0?). Thus apparent trends in release efficiency (Figures 2a and c) provide, in isolation, rather ambiguous insight into petroleum release mechanisms. In order to clearly identify the critical processes, we need to make more specific observations - and test resulting deterministic models against them.

Deterministic approaches attempt to forward-model petroleum release from first principles. They are limited by our ability to quantify geophysical and geochemical processes. Widely alternative models persist today, each assigning differing relative importance to the various processes potentially governing release efficiency, because so far the critical observations have not been clearly laid out.

In the following two sections we explore two deterministic approaches, both of which are conventional in the sense that petroleum is generated by kerogen and eventually migrates to the secondary carrier bed via an inorganic pore/fracture (void) system, as a discrete bulk phase driven by fluid potential gradients.

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Figure 2 Comparison of trends in petroleum release efficiency (PRE) calculated by carbon mass-balance): (a) Mean PRE vs. P0 for ten source rocks (Mackenzie and Quigley, 1988); (b) Mean PRE vs. P0 and (c) Mean PRE vs. HI0 for twenty source rocks (Pepper, 1991). Figure 3 Petroleum release from the source bed is a multi-step process, where the slowest rate limits the overall rate. Model 1: generation kinetics (Kg) control petroleum delivery rate to the inorganic void system; fluid flow rates govern subsequent primary migration (Kpm). Model 2: considers intermediate storage of petroleum between the point at which bonds are broken in kerogen and the appearance of a petroleum phase in the inorganic void system. Expulsion rate (Ke) is limited by Kg, but only after storage criteria are met within the kerogen. Our observations identify Ke and thus ultimately Kg, as the overall rate-limiting process: hence ORGAS considers only generation and storage of petroleum within kerogen; we also therefore simplify primary migration to a storage problem.

Figure 3 summarises the difference between the two approaches. Although common usage of the terms expulsion and primary migration implies they are

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synonymous, our conceptualisation of petroleum release draws important distinctions. Firstly, generated petroleum is expelled from kerogen. We will show this to be the more significant retarding process during release from the source bed, although most models to-date have ignored it completely. Primary migration begins when petroleum eventually enters the inorganic void network. It has been the focus of most modelling effort to-date; however we will show it to be generally a limiting process only if significant vertical migration outside the source bed is required. Sandvik et al. (1992) and Okui and Waples (1992) also recognised the distinction as important.

Below we summarise abundant geochemical and geophysical evidence linking petroleum and kerogen concentrations in source beds; much obtained by stepping outside 'conventional' petroleum geochemistry into coal and coalbed methane science. Speculation on the relationships between coals and oil deposits dates back at least to Erasmus Darwin in 1791 (Torrens, 1994) but many petroleum geochemists over the last two decades have been content to classify coals rather unhelpfully as "Type III" kerogen, which is usually taken to imply a gas-prone type of release behaviour. Others (Durand and Paratte, 1983; Pepper, 1991) saw no such rigid distinction between coals and 'conventional' petroleum source rocks. Coals are uniquely defined by organic richness rather than chemistry: the latter is reflected in a variation of lithotypes from inertinites to torbanites. Torbanites share a common kerogen type with lacustrine oil-shales (freshwater algal-bacterial OM), and, since both are retorted as commercial oil sources, must be accepted as 'conventional' oil source rocks. This very admission negates the argument used to preclude humic (vascular plant-derived) coal lithotypes as effective oil source rocks based on excessive organic richness per se (e.g. Katz et al., 1990).

I: EXPULSION - PETROLEUM RELEASE FROM KEROGEN

The idea that kerogen might influence petroleum release from source beds is not new (Philippi, 1965; Young and McIver, 1977; Jones, 1980; McAuliffe, 1980). Interest in the idea waned through the 1980's, but the end of the decade saw a revival. Kerogen has been recognised as a potential impediment to release (Barker, 1987; Talukdar et al., 1988; Behar and Vandenbroucke, 1988; Pepper, 1989; Wang and Barker, 1989; Wang, 1990; Katz et al., 1990; Noble et al., 1991; Sandvik et al., 1992). Others have invoked it as a potential pathway (Stainforth, 1988; Stainforth and Reinders, 1989 and 1990; Thomas and Clouse, 1990 a, b and c). Pepper (1991) and Okui and Waples (1992) emphasized that quantitative understanding of kerogen's role is important in petroleum resource assessment.

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Figure 4 Differing conceptual models of the organic-inorganic relationship in source rocks: (a-c) drawn at the correct scale, the load-bearing nature of kerogen is easily appreciated. (1) macro- and microfractures may penetrate both the organic and inorganic matrices; contrast this with (d) a conceptualisation by Barker (1980) portraying kerogen particles smaller than the mineral grains, in dispersed locations which are not load-bearing. Properties of rocks which control expulsion Petroleum storage in kerogen Scale. The first volumetric impediment to petroleum release from a source bed is provided by the originating kerogen particle. Continuous kerogen bodies range in size from coal seams to dispersed particles; even the latter are orders of magnitude larger than particles in the enveloping inorganic matrix (Figure 4a-c). Kerogen is readily examined in the visible light spectrum; mud-sized mineral grains are not - but note that even this rather basic observation is violated by cartoons which have located kerogen particles inside the inorganic void network (Figure 4d)!

Thus kerogen is load-bearing (Du Rouchet, 1981; Palciauskas, 1991). If kerogen were an organic solid with no porosity, subjected to lithostatic pressure, generated petroleum could only exist as a transitory fluid phase within it. Using an analogy with crustal melts, Palciauskas (1991) has gone so far as to suggest that fractional petroleum volumes within kerogen should therefore not exceed 0.02. We find this analogy inappropriate since kerogen has microporosity capable of absorbing petroleum and since storage could also occur by adsorption onto its internal surface area.

Organic "microporosity": absorption / molecular sieving. Coals have an aperture-cavity type of 'porosity' which is well studied (Rightmire, 1984);

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comparatively little is known about its equivalent in conventional petroleum rocks though Lindgreen (1987) described 'organic lined pores' with molecular sieving properties in a marine source rock. Coal 'pores' can be thought of as a series of organic molecular cages ranging down to sub-nannometer, i.e. molecular scale (Gan et al., 1972; Harris and Yust, 1976; Majahan and Walker, 1978). Differing sizes of aperture and cavity can sieve and trap molecules of a characteristic size: small molecules (including gases) are sieved by coal 'micropores' with diameters in the 0.4-1.2 nm range (van Krevelen, 1961; Hanbaba et al., 1968; Peters and Juntgen, 1968; Gan et al., 1972; Given et al., 1986). Total coal porosity, estimated from moisture content, may be around 8-10% during oil generation (Stach et al., 1982). Internal surface area: adsorption. Coals can store gas by adsorption onto their huge internal surface area: one gram of coal can have a CO2 area of hundreds of square metres (Thomas and Damberger, 1976; Majahan, 1991). However, access to potential surface area within micropores is restricted when sorbate molecules are larger than the pore aperture (Debelak and Schrodt, 1979; Debelak and Schrodt, 1979; Majahan, 1982). Some coal pore throats are only open to helium (molecular diameter 0.26 nm; Harrison, 1975): the 'helium area' of a coal is much greater than its 'N2' or 'CO2 area'.

There are many additional factors. Molecules of similar size such as N2 and CO2 may simply differ in their tendency to sorbe (Patching, 1965; Gan et al., 1972). Cross-sectional area and density of molecules in the adsorbed state can differ from their conventional values (van der Sommen et al., 1955; Majahan, 1982). Small increases in moisture, up to the level of 2%, inhibit the methane-sorbing capacity of dry coal by about a third (Kim, 1977; Wyman, 1984) probably because water and gas molecules compete for access to surface area (Taber et al., 1974). Larger increases in moisture content have little additional effect, however (Wyman, 1984).

Thus porosity and surface area of coal are not fixed quantities: they depend on the investigative medium. Additionally, it is difficult to distinguish the processes of adsorption and pore filling in coal micropores, where gas may occupy both surface area and volume (Majahan and Walker, 1978; Marsh, 1987). This dictates that our working definition of the petroleum stored in kerogen must be a loose one: we will refer to all petroleum in kerogen as sorbed, whatever the precise mechanism.

Coals can sorbe enough methane to be considered as commercial gas reservoirs (Satriana, 1980; Rightmire, 1984; Wyman, 1984; Choate et al., 1986; Ayers and Kelso, 1989; Ayoub et al., 1991; Kruuskraa et al., 1992.) Ethane through butane are sorbed even more strongly than methane (Figure 5a; Friedrich and Juntgen, 1972; Ruppel et al., 1972; Kim, 1973; Kravtsov et al., 1983).

Comparatively little is known about sorption of oil (C6+) molecular weight range petroleum heavier than hexane (Van Krevelen, 1961). Pepper (1991) reasoned that, if small, simple gas molecules with low dieletric constants can

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sorbe effectively, then increasingly large, complex, and polar oil molecules should have even higher sorbing tendencies. Sandvik et al. (1992) have investigated data obtained from solvent chemistry and swelling of coals and organic polymers (Figure 5b), which provide a chemical basis for the ideas we promote in our model of petroleum release. Figure 5 Organic sorption: a) Results of simple experiments allowing rocks of various TOC to equilibrate with methane and n-butane at ambient temperature and atmospheric pressure (previously unpublished proprietary data). Proportionality between gas uptake and TOC, together with minimal positive intercepts at zero TOC, imply sorption by kerogen. n-butane is sorbed much more strongly than methane, as observed in coal beds. (b) Solubility parameters for various organic compounds, bulk petroleum compound classes, and kerogen (Sandvik et al., 1992). The total solubility parameter for a compound has three components: del H, del P, and del D, attributed to hydrogen bonding, polarity and dispersion, respectively. Aromatic, then polar molecules / compound classes are increasingly similar to, and hence are increasing soluble in, kerogen. Petroleum movement through kerogen Oil is mobile through kerogen (Allan and Larter, 1983; Given et al., 1986; Stainforth, 1988; Stainforth and Reinders, 1989 and 1990; Thomas and Clouse, 1990a, b and c). A number of transport mechanisms are possible.

Diffusion through kerogen. Small petroleum molecules move through coal by activated diffusion (van Krevelen, 1961). This concept has recently been applied to 'conventional' petroleum source rocks (Stainforth, 1988; Stainforth and Reinders, 1989 and 1990; Thomas and Clouse 1990a, b and c). Kerogen behaves as a liquid medium for diffusion (Thomas and Clouse, 1990b): in continuous 'model' networks, diffusion rates can be two orders of magnitude faster than in an aqueous phase (Thomas and Clouse, 1990a).

Viability of diffusive transport depends on the presence of a continuous network. Stainforth and Reinders (1990) suggest 1% TOC as a minimum pre-requisite for a continuous kerogen network; Thomas and Clouse (1990c) suggest 2 - 2.5 %, a limit which would exclude many source rocks with established oil

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release capability (Cooles et al., 1986; Pepper, 1991). Furthermore, the mechanism is also unhelpful in explaining migration through an organic-lean interburden.

Microfracturing. Any petroleum phase forming via amalgamation of desorbed molecules within a collapsing kerogen network will experience a lithostatic load. Microfracturing is the likely result. Although the natural 'cleat' or fracture system in coals is volumetrically insignificant in terms of petroleum storage capacity (Meissner, 1987; Hvoslef et al., 1988), it represents an important fluid release pathway (Meissner, 1987).

During the uplift-erosion cycle, fractured coals may be exhumed to shallow depths (< 1 km), where confining pressure is low. Economic coal bed methane extraction under these conditions requires cleat that is sufficiently frequent and permeable to allow pressure draw-down and desorption from the kerogen reservoir on a commercial production timescale. Under hydrostatic pressure, cleat permeability decreases with depth due to increasing confining pressure (Figure 6). If trends are extrapolated to depth, cleat permeabilities in the 10-7 to 10-6 Darcy range are projected - higher than reported for inorganic void networks in mudrocks (e.g. 10-10 to 10-7 Darcy to oil; Sandvik and Mercer, 1991). Thus fractures, particularly when propped open by lithostatic internal pressure during petroleum generation, should also provide efficient, rapid drainage of a petroleum phase forming within OM during burial. Figure 6 Fracture permeability versus confining pressure for cleats (fractures) in coal (data from Patching, 1965). Observations of expulsion Extraction; microscopic analysis

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Common geochemical measurements of oil yield are organic solvent extract (Durand, 1980) and pyrolysis thermal volatilate S1 (Espitalie et al., 1977) - the latter sometimes misleadingly referred to as 'free' hydrocarbons. In fact, these yields in themselves tell us nothing about the location or mobility of petroleum in a source rock. Associations between petroleum and OM are well known from studies of: humic acids (Khan and Schnitzer, 1972); coals and other OM-rich rocks using n.m.r. (e.g. Given et al., 1986); progressive extraction with solvents of increasing strength (e.g. Marzec et al., 1979; Sandvik et al., 1992); repeated extraction after acidification (Behar and Vandenbroucke, 1988; Stainforth and Reinders, 1990); and even repeated extraction with a mild solvent (e.g. Durand et al., 1987). Horsfield et al. (1988) and Noble et al., (1991) proposed that aromatic hydrocarbons, generated by perhydrous vitrinite and resinite macerals, can deactivate sorptive sites in Indonesian coals, thereby enhancing expulsion efficiency of the saturated hydrocarbons in which coal-sourced oils are enriched. (Again, this mechanism negates arguments that coals which generate aromatic-rich hydrocarbons cannot be a source of saturate-rich oil; Katz et al., 1990). The fluorescence of exinite and perhydrous vitrinite macerals under U.V. light (Teichmueller, 1974; Stach et al., 1975; Radke et al., 1980) suggests a capacity to sorbe aromatic oil. As in the case of coalbed gas, we will use a loose definition of the term 'sorbed' to describe any oil which we can demonstrate to be OM-associated, whether actually adsorbed or physically trapped within kerogen. For example, in low ash coals, which are essentially pure kerogen bodies, S1 yields up to 44 mg g-1 (Khorasani, 1987) and 57 mg g-1 (Katz et al., 1990) can be interpreted as a sorbed oil content of ca. 5 % (mass). Figure 7 Oil yield vs. organic carbon for two oil source rocks at various depths: (a) S1 vs. TOC for Kimmeridge Clay Formation (KCF) source beds in UK North Sea Basin wells (depths in km); (b) Extract yield vs. TOC for Toarcian source beds in three Paris Basin wells (data from Tissot et al., 1971). Note the strong linear covariance between S1/extract and TOC at all stages of maturity. There is no absolute ceiling value of S1/extract in expulsive sections (KCF at 4.1 and 4.5 km; Toarcian in Montmirail well); in contrast these sections record a maximum TI

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(S1 or extract vs. TOC gradient) which is controlled by the sorptive capacity of residual organic carbon. Dependency between oil yield and TOC However, our most persuasive demonstrations of sorbed oil content are not based on coals, but on marine source rocks relatively unperturbed by lateral and vertical variation in OM type, which exhibit persistent correlations between indigenous petroleum concentration and residual TOC. Figure 7a illustrates remarkably linear correlations between S1 and TOC in the Kimmeridge Clay Formation (KCF), UK North Sea. Covariance is strong irrespective of maturation level (burial depth). Transformation Index TI (in this case S1/TOC gradient) increases with increasing maturity from the pre-expulsive section at 3.4 km, to the expulsive sections at 4.1 and 4.5 km, where a limiting TI is reached which averages 106 mgHC gC-1 in a number of wells (Pepper, 1991). Figure 7b plots extract yield vs. TOC for three Toarcian mudstone source beds from the Paris Basin (data from Tissot et al., 1971). Two pre-expulsive sections (Der, Dontrien wells) display linear gradients with high correlation coefficients (equivalent TI ca. 0.1 gO gC-1). A section from the deepest, expulsive well section Montmirail displays a higher TI, ca. 0.2 gO gC-1 also with high correlation coefficient. Figure 7 suggests that petroleum and OM concentrations are closely related in both pre-expulsive and expulsive source rocks. Co-variance during early maturation is a normal consequence of first-order kinetic behaviour (Part I): the amount generated is proportional to the amount of reactant kerogen. However, persistent co-variance at all maturity levels, including during petroleum release, can be explained only if (sorption by) residual kerogen continues to limit the residual petroleum yield. Depending on the sorbate a limiting value of TI is observed (c.f. coalbed methane). We use such data to estimate the sorptive capacity of kerogen for oil. Borehole geophysical logs Organic-rich clastic rocks and low ash coals show the same progression in electrical resistivity during maturation: both are conductive at low thermal stress, increasing in resistivity during oil generation. Since low-ash coals lack an inorganic void system, these resistivity changes must result from increasing oil and decreasing water content of the kerogen itself. Thus (Pepper, 1991) high electrical resistivity does not in itself imply high petroleum saturation in the inorganic void system of mature clastic source beds, as is commonly assumed. Rather, resistivity logs confirm the same associations between petroleum and kerogen which we have demonstrated using geochemical data (e.g. Meyer and Nederlof, 1984; Mann et al. 1986; Pepper, 1991; Creaney and Passey, 1993; Figure 8). In our experience, high resistivity readings within fine grained rocks are always associated with, and broadly proportional to, organic carbon content.

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Sorption-fractionation effects Gas fractionation. Coal beds produce a hydrocarbon gas mix dominated by methane (Kim, 1973), quite dissimilar to most petroleum gases which have varying but significantly higher proportions of heavy gases (Clayton, 1991). However, this is an artifact of fractionation under the low pressure / temperature regime of currently exploited coal beds. Figure 8 Partial geophysical and geochemical log from a Paris Basin well (located close to the Montmirail well; Figure 7b), showing the lower Toarcian 'Schistes Carton' oil source rock (2100-50 m) which has expelled oil in this basin centre location. Gamma and sonic logs show a regionally persistent 'funnel'-shaped log motif: organic richness and petroleum potential increases downwards through the source bed, as confirmed by S2 data. The gamma ray motif is

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replicated / sonic log is mirrored by the resistivity log: petroleum exists in a concentration proportional to the OM content (c.f. Figure 7b). Binary sorption experiments (combined methane and ethane) by Ruppel et al. (1972) provide insight into the way that gases (and other petroleum molecular classes, i.e. those in oils) might be partitioned between the sorbed and fluid phases in source beds, as a function of pressure and temperature. Their results (Figure 9) suggest that at high temperatures (e.g. during thermogenic gas generation) ethane and - we speculate - higher homologues are likely to be desorbed much more readily than in the near-surface coal-bed analogue. Figure 9 Binary sorption of methane and ethane on a bituminous coal with TOC 78.7% (dry ash-free basis). Experimental data from Ruppel et al. (1972). Increasing pressure causes ethane to be preferentially concentrated in the adsorbed phase (weak dependency over the pressure range 1 - 40 atm; 0.1 - 4.0 MPa; 0 - 400 m hydrostatic) but increasing temperature (0 - 50 oC) causes methane to be preferentially concentrated in the adsorbed phase (strong dependency over the same pressure range).

These experimental results support a number of qualitative field observations: the increasing proportion of C2+ gases observed with increasing isothermal pressure draw-down on a production time-scale (Iannacchione and Puglio, 1979 and 1980; Rieke and Kirr, 1984; Wyman, 1984); and the tendency

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for shallower coals, brought closer to the surface due to uplift and erosion on a geological timescale, to produce more C2+ from the outset (Choate et al., 1984). Thus, the composition of conventionally-reservoired thermogenic gases, though different to coalbed gases, could simply reflect phase partitioning during desorption under a higher pressure-temperature regime, coupled with first order effects (i.e. varying initial proportions of hydrocarbon gases generated). Oil fractionation also occurs during petroleum release. Initially, fractionation was inferred from consistently recognised differences between compound class distributions in source rock extracts and reservoired oils (Hunt and Jamieson, 1956; Bray and Evans, 1965; Tissot and Pelet, 1971; Young and McIver, 1977; Combaz and Matharel, 1978; Price et al., 1984). Increasing confirmation came from direct examination of source beds, close to source-carrier bed boundaries (Tissot and Pelet, 1971; Vandenbroucke, 1972; Deroo, 1976; Barker, 1980; Figure 10) or across basin pressure transition zones (Vandenbroucke et al., 1983). Figure 10 Relative release efficiency of oil components from an Algerian Devonian clastic source bed in contact with a reservoir bed. Based on extract data in Tissot and Pelet (1971), manipulated using techniques developed and applied in more recent KFA case studies. Fractionation occurs according to oil component polarity (c.f. Figure 5b).

This approach was refined by workers at KFA, Juelich, Germany and implemented in numerous case studies during the last decade. Consistent observations, some of which have been verified experimentally (Lafargue et al., 1990), can be summarised:

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o source rocks release hydrocarbons preferentially to non-hydrocarbons (Figure 10; Tissot and Pelet, 1971; Mackenzie et al., 1987; Leythaeuser et al., 1987a and 1988a; Wilhelms et al., 1990; Lafargue et al., 1990);

o within the non-hydrocarbons, the polar/NSO/resin fraction is released preferentially to asphaltenes (Figure 10; Tissot and Pelet, 1971);

o within the hydrocarbons, saturates are released preferentially to aromatics (Leythaeuser et al., 1983; Vandenbroucke et al., 1983; Leythaeuser et al., 1984a and b; Mackenzie et al., 1987 and 1988; Leythaeuser et al., 1987a, 1988a and b; Lafargue et al., 1990; Littke et al., 1990);

o within the saturates, n-alkanes are released preferentially to branched alkanes (Mackenzie et al., 1983; Leythaeuser et al., 1983; Leythaeuser and Schaefer, 1984; Leythaeuser et al., 1984a and b; Leythaeuser and Schwarzkopf, 1986; Lafargue et al., 1990);

o 'Type III' (low HI0) source beds release n-alkanes preferentially in order of decreasing chain-length from nC35-15 (Mackenzie et al., 1983; Leythaeuser et al., 1983; Vandenbroucke et al., 1983; Leythaeuser and Schaefer, 1984; Leythaeuser et al., 1984a and b; Hvoslef et al., 1988). During release from "Type II" (high HI0) source rocks, such as the KCF and its Norwegian equivalent, fractionation occurs according to chain length among the short- (< C10) rather than long- (> C15) chain n-alkanes (Mackenzie et al., 1987 and 1988; Leythaeuser et al., 1987a and 1988a; Wilhelms et al., 1990).

o In the Brae KCF, redistribution of the light hydrocarbons (e.g. C5 n-alkanes) perturbs the otherwise monotonous concentration gradients towards the source rock edges (Mackenzie et al., 1987 and 1988; Leythaeuser et al., 1987a and 1988a).

Most of the source beds in Figure 2 were thick and relatively homogeneous, so the additional depletion which accompanies these fractionation effects at source-carrier bed contacts has a relatively minor impact on bulk release efficiency. Many workers have recognised fractionation behaviour consistent with component polarity - some emphasizing the role of liquid-solid interaction or "geo-chromatography" (Silverman, 1965; Vandenbroucke, 1972; Barker, 1980; Mackenzie et al., 1983; Leythaeuser and Schaefer, 1984; Leythaeuser et al., 1984a, 1984b and 1988b; Lafargue et al. 1990). However, most invoked inorganic minerals as the sorbant phase. Clays and clay-rich rocks can adsorb and fractionate petroleum under dry experimental conditions (e.g. Eltantawy and Arnold, 1972; Espitalie et al., 1980 and 1984; Tannenbaum et al., 1986; Krooss, 1991 and references therein). However, detrital clay minerals are wetted from the moment of aqueous transport. More realistic physical experiments involving sequential permeation of already water-wet clays (Krooss, 1991 and references therein) and clay-rich soils (Fernandez and Quigley, 1985) show that hydrocarbons with low dielectric constants can not compete with water molecules (with high dielectric constant) for sorptive sites on clays. Most silicate minerals are initially hydrophilic (Benner

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and Bartell, 1941); although carbonate reservoir rocks are more frequently oil-wet than clastic ones (Treiber et al., 1972), they are not analogous to carbonate source facies. Reviews by Krooss et al. (1991) and England et al. (1991) conclude that the evidence in favour of geo-chromatography is, at best, ambiguous. More recently, the trend has been increasingly to attribute chain-length fractionation in 'Type III' source beds to petroleum phase-separation effects: this requires a gas phase to form in the source rock, which preferentially 'strips' lighter components from the overall molecular mix (Vandenbroucke et al., 1983; Mackenzie et al., 1987 and 1988; Leythaeuser et al., 1987a, 1987b, and 1988a; Hvoslef et al., 1988; Price, 1989). Leythaeuser and Poelchau (1991) developed an elegant numerical simulation of n-alkane fractionation. Price (1989) wishes to extend the mechanism to a "Type II" source rock, i.e. the Bakken Shale. However, we doubt whether this process is responsible for the fractionation effects observed during petroleum release from source rocks because neither experimental nor natural phase segregation (Larter and Mills, 1991; Phillips et al., 1991) induce strong fractionation between normal and branched alkane isomers. Additionally, on mass-balance grounds, a major constraining factor is gas supply: our pyrolysis-GC database (Part I, Figure 2) shows that even "Type III" kerogens are not primarily gas-generative. Intra-source cracking under high thermal stress could provide the required gas:oil ratio (Price et al., 1983), but under this high P,T regime, phase behaviour is more likely to be supercritical: fluid composition may evolve continuously without segregation into distinct oily and gassy fluid phases (Part II). Furthermore, at the basin scale of observation, petroleum pools charged from "Type III" source rocks are not exclusively gas-saturated. Classical diffusion offers a mechanism for fractionation of only the light n-alkanes (e.g. n-C5; Mackenzie et al., 1987). Stainforth and Reinders (1989 and 1990) used a model of thermally-activated diffusion through kerogen to match various observations in the Brae KCF dataset (Mackenzie et al., 1987 and 1988; Leythaeuser et al., 1987a and b, 1988a and b). However, experiments by Thomas and Clouse (1990c) showed diffusion of compound classes through kerogen in the opposite order to that observed in nature, i.e. aromatics > napthenes > alkanes, . We find it surprising that, with the notable exceptions of Thomas and Clouse (1990c) and Sandvik et al. (1992), only occasional passing references have been made to the potential role of organic matter in fractionation (e.g. Leythaeuser et al., 1988b). Concentration gradients near source-reservoir bed contacts could represent desorption gradients, regulated by the pressure gradient between overpressured source bed (pressure source) and reservoir (pressure sink). We find the analogy with coalbed methane intriguing: just as methane is released before ethane on progressive pressure draw-down of a coal 'reservoir', oil fractionation within source beds would be expected according to the differing sorptive capacity for each compound class (c.f. Figure 5b) and the pressure gradient experienced. Such a process might operate both on the scale of source-reservoir interbeds, and on a much larger scale across major basin pressure transition zones (e.g. Vandenbroucke et al., 1983).

18

Thomas and Clouse (1990c) conclude that organic solid-fluid phase partitioning is probably more important than diffusivity in explaining fractionation effects. We agree. Katz et al. (1990) highlighted the paradox: how can poor quality (saturates-poor) source rocks be the source of high quality (saturates-rich) oils? Figure 11 illustrates the potential consequences of organic sorption-fractionation in source rocks of varying initial organic quality. The high quality (HI0) OM in "Type I and IIS" source rocks e.g. the Green River Shale (Hunt et al., 1954; Tissot et al., 1978), Senonian Bituminous Rock of the Dead Sea Basin (Tannenbaum and Aizenstat, 1985) and Monterey Formation (Orr, 1986), easily overcomes its internal sorptive capacities: even asphaltenes are available in excess, for expulsion. Thus expelled oils can be poor in quality (saturate-poor, polar, heavy and viscous). In contrast, source rocks with progressively poorer quality (lower HI0) OM have successively higher expulsion thresholds, permitting increasingly selective release of only the higher quality (saturate-rich, light, mobile) generation products. In the extreme case, OM with quality approaching the sorption limit will retain all but the least sorbant oil products (e.g. Westphalian coals, Southern North Sea Basin). Light saturated hydrocarbons will comprise the small C6+ component expelled; this is ultimately reservoired in highly undersaturated gas-phases and produced as a very low yield of high gravity condensate. Condensates of this type may have been sufficiently fractionated to constitute a 'naturally refined' petroleum product suitable for direct use as a fuel on remote gas production facilities. Figure 11 Likely effect of sorption-fractionation on expelled oil quality. Five exclusively oil-generative synthetic source rocks have equal TOC0 and generate the same mix of petroleum compound types, but differ in HI0 (i.e. they are different mixtures of inert and oil generative kerogen). HI0 determines the ease with which organic sorption is overcome (e.g. arrowheads show oil concentration required to exceed sorption coefficient = 0.2 g gCK

-1 at full maturity). If generated oil compound types sorbe in order of increasing polarity / molecular weight range (c.f. Figure 5b), expelled oil quality will vary inversely with HI0 (e.g. saturate fractions annotated at top of each bar). Relative compound proportions in the modelled expulsion products conform broadly to those observed in nature.

19

Figure 11 is an illustrative cartoon: reality will involve differing generative and sorptive capacities for differing compound types, differing generation temperatures and, at higher stages of maturity, effects of oil-gas cracking. More realistic simulation of sorption-fractionation would require complex equations of state describing how compound mixes partition between the desorbed and sorbed states (c.f. Figure 9, showing only binary mixtures!). Given the simplicity of our current compositional model of petroleum (gas: C1-5; oil: C6+) and current data limitations, such complexity remains to be addressed in future generations of model. Quantifying expulsion: sorption coefficients Having summarised the evidence for organic sorption during petroleum expulsion from kerogen. We now present simple equations, and estimate global parameter values, required to predict the sorbed oil and gas contents of source beds. Important variables governing sorption are pressure, temperature, surface area of the sorbant phase and chemical properties of the sorbate phase. Gas sorption coefficient aG Volume, surface area and mass. The coal bed methane and coal mining industries use a technique known as the Direct Method to estimate the undisturbed gas content of coal seams (Kissell et al., 1973; McCulloch et al., 1975; Diamond and Levine, 1981). This involves laboratory desorption, crushing

20

(to release physically trapped gas), and an extrapolation to estimate gas losses during sampling and handling. Its relative accuracy is regarded as high (within + 30 %; Kim, 1977). Although an absolute reference is hard to obtain, these data provide a closer approximation to in-situ gas content than is possible using standard petroleum industry techniques - although we note that Sokolov et al. (1971) designed apparatus for the purpose. Coal gas yields are expressed as a surface volume of gas per unit mass, usually in cm3 g-1 or ft3 ton-1 (Rightmire, 1984); coal mass is usually taken DAF (dry, ash-free basis) i.e. net of water (moisture) and mineral matter (ash). Such units are useful in resource estimation; but they are inappropriate if adsorption s.s. is regarded a surface phenomenon reflecting internal area. Variations in facies and maturity (rank) cause coals to have widely differing carbon content, even on a DAF basis. Thus rank-, lithotype- or even seam-specific adsorption isotherms are required to predict methane resources (Kim, 1977; Eddy et al., 1982; Lamberson and Bustin, 1993). We simplify this undoubtedly complex problem by making use of the known proportionality between coal internal surface area and carbon content, for a given sorbate (Nandi and Walker, 1971; Gan et al., 1972). After normalising coalbed gas yields to carbon mass, we can extrapolate the sorbed gas content of source beds with any given TOC (c.f. Figure 5a). Since kinetic models predict petroleum mass, we first convert methane volume yields to mass using an STP density, i.e. 670 g m-3 (although the actual pressure base at which methane volumes are measured is not always reported). Now the gas content is expressed in units [ggas gC

-1] useful to us in estimating a gas sorption coefficient aG. We found abundant published field data (e.g. Diamond, 1979; Kissell et al., 1973; McCulloch et al., 1975; Iannacchione and Puglio, 1979 and 1980; Diamond and Levine, 1981; Eddy et al., 1982; Rightmire et al., 1984; Wyman, 1984; Meissner, 1984 and 1987; but experimental data at high pressure and at differing temperatures more limited (e.g. van der Sommen et al., 1955; Ruppel et al., 1972). Depth, pressure and temperature. One approach to determining aG is purely empirical: plots of methane yield vs. logarithmic burial depth have high correlation coefficients for individual coal measures (e.g. Figure 12) or coals of common rank (Eddy et al., 1982). However, our depth range of interest is far outside this calibrant pressure / temperature regime - extrapolation is highly unreliable. It would be better to understand and quantify the underlying pressure-temperature dependency. Methane sorption on dry coal increases with increasing pressure and decreasing temperature: this forms the basis of theoretical adsorption algorithms used by the coalbed methane industry (e.g. Ruppel et al., 1972; Kim, 1977). Again, these models are well calibrated within the pressure-temperature regime typical of current economically and technically feasible coal-bed methane developments < ca. 1.1 km (3500'; Eddy, 1984). However, when extrapolated to

21

depth, published correlations predict sharp reversals in gradient, and negative values for aCH4. Figure 12 Depth-logarithmic trend in sorbed methane content of Pennsylvanian Hartshorne Coal, Arkoma Basin, Oklahoma (data from Iannacchione and Puglio, 1979 and 1980). Conversion to mass carbon units assumes a coal bed TOC of 70%. A further frustration arises when using published correlations based on shallow coal beds which, on a production timescale, remain static in the sedimentary column: gas yields are invariably projected as low temperature adsorption isotherms (Kim, 1977; Eddy et al., 1982). Conventionally, even high pressure experiments useful to us have been carried out at low isothermal temperature (e.g. up to 50 MPa, equivalent burial depth 5 km at hydrostatic pressure but at 25 oC; van der Sommen et al., 1955). In the following projection of aCH4 to depth we combined experimental results from van der Sommen et al. (1955) to estimate pressure dependency, with data from Ruppel et al. (1972) to estimate temperature dependency. Pressure: Figure 13a shows a regression of high pressure isothermal data at 25 oC. The pressure dependency is linear up to pressures of 10 MPa, which at this temperature represents a critical pressure beyond which no further methane can sorbe: the coal's internal surface area is saturated. At 25 oC, aCH4 is given by:

aCH4 = c + 9.4*log(P) (1)

22

where: aCH4 has units [cm3 gCOAL-1]; c is an intercept value which is not of interest since we only seek the gradient value; and P is pressure (MPa). No carbon content was given for the coal, but for a TOC of 67% (typical of a low ash coal) yields in units [cm3 gCOAL

-1] are simply 1000 times the yield in units [g gC-

1]. Temperature: Figure 13b shows three sets of isothermal data, fitted with curves of slope established in Equation 1. At 0 oC, aCH4 is given by:

aCH4 = 6.7e-3 + 9.4e-3*log(P) (2) where aCH4 now has units [g gC

-1]; P is again pressure [MPa]. At constant pressure, sorption decreases with increasing temperature. This correction is derived from the shift in y-intercept of the 30 and 50 oC isothermal curves:

aCH4 = - 6.2e-5*T (3) T is in [oC]. Substitution into equation (2) gives:

aCH4 = 6.7e-3 + 9.4e-3*log(P) - 6.2e-5*T (4) Figure 13c makes projections for a range of geological pressure-temperature regimes. At shallow depth, the curves have similar form to empirically-derived trends (e.g. Figure 12): the decreasing rate of increase in aCH4 with depth results from competing effects of increasing temperature and pressure - a competition which temperature is predicted to 'win' at greater depth. However, the reversals projected at depth remain hard to substantiate due to lack of deep calibration.

23

Figure 13 Estimation of pressure and temperature dependency of methane sorption in coal: (a) isothermal (25 oC) pressure dependency from data for the Emma VIII seam (van der Sommen et al., 1955); (b) temperature dependency established by superimposing the gradient from (a) on three isothermal (0, 30, 50 oC) experimental sets on dry coal (Ruppel et al., 1972); (c) Predictions of coal bed methane content using Equation (4) for geological extremes of P,T gradient (lithostatic at 20 oC km-1; hydrostatic - probably unreasonable given our earlier comments about internal pressures in kerogen - at 40 oC km-1). Plotted for comparison, aG values for 367 coal seams, calculated from data in Diamond and Levine (1981). In conversion to mass carbon units, TOC was back-calculated using standard DAF fixed carbon values corresponding to coal rank: 64.1% (Lignite); 69.2% (Sub-C); 71.5% (Sub-B); 75.2% (HVB-C); 78.6% (HVB-B); 82.2% (HVB-A); 86.6% (MVB); 89.0% (LVB); 94.4% (Anthracite). Also plotted are data from Figures 5 and 12. Many of the coals plotting below the projected range are of too low rank for gas content to be controlled by an expulsion limit. Range of projections is consistent with data from coals at 2.6 km with methane yield 15 cm3 g-1, recovered from anorganic rich section between 1.55-3.55 km in the Elmworth Field, West Canada (Wyman, 1984). Though aCH4 varies widely with depth, it changes most rapidly at shallow depth: from its vanishingly small near-surface value (Figure 5a) down to ca. 2 km (20 MPa at hydrostatic pressure gradient). Within this interval, thermogenic gas generation is proceeding at insignificant rates during the burial cycle. (However, it might be important in understanding biogenic gas expulsion.) Over most of the 2-10 km depth range (20-100 MPa at hydrostatic pressure gradient), aCH4 remains between 0.01-0.02 g gC

-1. Figure 13c also predicts that kerogen will expel gas more efficiently in hot, low-pressured basins than in cold, highly overpressured basins. However, the absolute effect of the change in aG - about 0.01 g gC

-1 - is small and probably untestable using field data. However, there is a clear danger in estimating aCH4 using trend-fitting of field data only, since the uplifted and eroded basins from which coal gas is produced often have lower pressure and cooler geothermal regimes than actively subsiding basins. Since there are obvious limitations in the data we used to make these projections, we continue to assume a global constant aG value of 0.02 g gC

-1 (Pepper, 1991) - a value which accounts for an additional contribution from C2+ gas sorption (Figure 9). Oil sorption coefficienl aO Values of aO are more difficult to demonstrate since we lack laboratory experimental data. Currently we base our estimates on field samples (Table 1; Figure 7).

24

Table 1 Table 1 Potential values of oil sorption coefficient derived from geochemical measurements

Rock Method Max. TI* (mg gC

-1) aO**

(g gC-1)

Reference

Douala Extract 125 0.14 1 Toarcian Extract 200 0.24 2 Green River Extract 150 0.18 1 Saharan

Extract 140 0.16 1

W. Canadian

Extract 160 0.18 1

KCF, Brae

Extract 180 0.21 3

'Global' 0.2 4 Various HC Extract 120*** 0.13 5 KCF, Brae HC Extract ca. 90 0.10 3 Lias, Paris Basin S1 ca. 80 0.09 6 KCF, UK N. Sea S1 106 0.12 4, 6 Tertiary coals S1 98 0.11 6, 7, 8

'Global' 0.1 4 Notes: * TI (Transformation Index) = (Extract or S1) / TOC; ** Calculated using Equation (5); *** Represents upper bound of quoted range. References: 1) Tissot and Welte (1984); 2) Tissot et al. (1971); 3) Mackenzie et al., 1987; 4) Pepper (1991) and Figure 7; 5) Philippi (1965); 6) BP proprietary data; 7) Katz et al. (1990); 8) Khorasani (1987). The value of aO will depend on the geochemical measurement used and the type of oil (sorbate) it quantifies (c.f. coalbed gas sorption). Extracts and thermal volatilates measure different types of 'mobile' organic matter: some of the high molecular weight material measured by solvent extraction may actually appear in the S2 (P2) rather than S1 (P1) yield of an unextracted sample subjected to pyrolysis (e.g. Tarafa et al., 1988); some samples still yield S1 (P1) after solvent extraction (e.g. Katz et al., 1990). Philippi (1965) made the first such estimates, argueing that hydrocarbon extract yields ranging between 30-120 mgHC gC

-1 were sorbed by organic carbon. Sandvik et al. (1992) reviewed these data together with total extract yield data in Hunt and Jamieson (1956), Hunt (1967) and McAuliffe (1980), concluding that the potential values range from 30-180, averaging 60-90, mgO gC

-1. Pepper (1991) argued for a higher value ca. 200 mgO gC-1, consistent with

25

the TI maximum observed in the Paris Basin (Figure 7b) and with maxima reported in other proven oil-expulsive source rocks. This implies an 'oil window' value for aO, when derived for polar-rich oils characterised by total extract yields, ca. 0.2 gO gC

-1 (Table 1). However, because ORGAS defines 'oil' using S1 (Part I), an appropriate aO value must be redetermined. In the North Sea KCF, the TI maximum averages 106 mgHC gC

-1 (Figure 7a; Pepper, 1991). This lower value is reasonable since hydrocarbons measured in the S1 (P1) yield should be less strongly sorbed than largely non-hydrocarbon (polar and asphaltenic) petroleum dominating the extract yield. Converting to a ratio of oil to carbon in kerogen [units gO gCK

-1], i.e. excluding the carbon in the oil itself: aO = S1 / (TOC - S1*WO) (5) where all quantities are given in fractional SI units and WO is the average mass fraction of carbon in oil (i.e. S1 yield). (Because gas yields as a fraction of TOC are so small, this correction can be neglected in determining aG). Substituting 0.85 gC g-1 for WO in Equation (5) results in an aO value of 0.116 gO gCK

-1. We currently lack data on the P,T dependency of aO. If it is similar to the behaviour of aCH4 (Figure 13), it will change relatively little within the P,T regime over which oil is present in source beds (Parts I and II). Additionally, the decrease in molecular weight and polar content of oils retained in source rocks as thermal stress increases might offset the effect on aO of an increasing pressure / temperature regime. Some natural variation in aO might also be expected between Organofacies which generate different oil types (Part I): note the differences between aO derived from S1, HC extract, and total extract yields (Table 1). Given such uncertainties, we use a global constant value for aO, of 0.1 g gCK

-1. Okui and Waples (1992) arrived at a similar value 'more or less by guesstimation', while Sandvik et al. (1992) found reasonable agreement with field data using 10g liquid per 100g solid organic matter (i.e. the same value).

II: PRIMARY MIGRATION - MOVEMENT THROUGH INORGANIC VOID NETWORKS

'Primary migration' involves movement of petroleum through the inorganic pore-fracture systems of both source beds and the non-source beds which separate them from potential secondary carrier beds. During the last decade geochemists reached overwhelming agreement that this process requires flow of petroleum in a discrete bulk phase (Ungerer et al., 1984; Doligez et al., 1986 and 1987; Heum et al., 1986; Tissot, 1987; Ungerer et al., 1987; Mann et al., 1988; Welte and Yalcin, 1988; Ozkaya, 1989; Burnham and Braun, 1990; Sandvik and Mercer,

26

1990; Ungerer et al., 1990; Forbes et al., 1991; Burrus et al., 1991; Dueppenbecker et al., 1991; Braun and Burnham, 1992). While we do not challenge this general concept, the evidence above persuades us that petroleum release from source beds cannot be solely a fluid flow problem, in which generated petroleum is immediately available within the inorganic void network (Figure 3, Model 1). Yet such an approach continues to be popular (e.g. Rudkiewicz and Behar, 1994) especially in 'basin modelling' (e.g. Burrus et al., 1993), despite mounting realisation elsewhere that it is only a part of the story (Stainforth and Reinders, 1990; Sandvik et al., 1992; Okui and Waples, 1992). In our view, fluid flow within the source rock is an extremely efficient process which in many cases, to a first approximation, can be neglected when considering source bed behaviour (Pepper, 1989 and 1991). Properties of rocks which control primary migration Currently accepted primary migration concepts suffer, in our view, from too-close an analogy with the petroleum reservoir or aquifer rocks from which they were essentially borrowed. This is despite long-recognised differences in the inorganic matrix and void systems of fine and coarse grained rocks (Dickey, 1975). There are mineralogical dissimilarities: fine grained clastics have a mineral matrix rich in clays. In carbonate systems, source rocks commonly occur in low energy clay-rich carbonate / marly facies quite atypical of carbonate reservoir rocks (Kwak, 1981; Brosse et al., 1988; Talukdar et al., 1988). Clays present a much larger surface area to volume ratio than quartzo-feldspathic or carbonate grains predominant in reservoir rocks: a much greater proportion of the pore fluid is in contact with the pore surfaces. Petroleum and water-mineral interaction For reasons we explained during discussion of fractionation effects, we agree with Mackenzie et al. (1988), Price (1989) and England et al. (1991) and Dueppenbecker et al. (1991), that already wet mineral surfaces are an unlikely sorbant phase for migrating petroleum: clays can be considered an oleophobic component and petroleum- mineral phase interaction neglected. However, clays do influence the behaviour of pore water: they present an enormous specific area for sorption of water, often referred to as 'bound' or 'structured' (Drost-Hansen, 1969; Low, 1976; Barker, 1980; Hinch, 1980; Magara, 1980; Honda and Magara, 1982; Talukdar et al., 1988; Price, 1989). The more pore volume occluded by bound water (i.e. the higher the irreducible water saturation), the less petroleum will be required to attain the high local saturations required for bulk-phase percolative flow within remaining 'effective' void space (Dickey, 1975; Pepper, 1991). Scale of the inorganic matrix void network Pores and pore-throats of source rocks are orders of magnitude smaller than those of reservoir rocks. Mean pore sizes over the depth range of most petroleum generation (> 2 km) are generally in the 1-10 nm range (Figure 14a;

27

Momper, 1978; Borst, 1982), with corresponding bulk permeabilities in the micro- to nanno-Darcy range (e.g. 10-7 to 10-8 Darcy at ca. 4 km in the Brae KCF; Leythaeuser et al., 1987b). Clastic source rocks' pore size distributions are typically skewed, with a modal population of very small, nannometer range pores and a subordinate 'tail' of larger ones (Figure 14b; Borst, 1982). In the Brae KCF, mean pore diameter is 6 nm with the 10th percentile at 100 nm (Leythaeuser et al., 1987b). The critical factor limiting petroleum flow here will be the minimum pore throat size involved in the interconnection of the larger pores. If this critical size is at the 10th percentile in the distribution, then of the 12% total porosity in the KCF (Figure 14b), only 1.2% will be effective, involved in through-going petroleum flow. This way, low overall saturations (e.g. 1-10% of total porosity, equating in this example to 0.12-1.2% of rock volume; Dickey, 1975) can still provide enough oil for high local oil saturation (10-100%) in the 'effective' pore network: the continuous petroleum pathways necessary for discrete-phase flow could only form if primary migration were highly localised within these larger pore networks. That is, similar to the invasion-percolation mechanism by which secondary migration occurs (e.g. England et al., 1987; Winter, 1987; England et al., 1991). The remaining matrix void space would remain occluded by bound water and overall irreducible water saturation would be high. Overall saturations of this order are unlikely to present a significant volumetric impediment to petroleum release: given a porosity around 5%, pore saturations of 1-10% equate to a rock volume fraction of 0.1-1%, and a mass fraction of 0.1-1 mg g-1 (Figure 15).

28

Figure 14 Pore sizes: (a) mean pore size vs. depth for US Gulf Coast mudstones (data from Borst, 1982); (b) pore diameter distribution determined by mercury injection of a KCF mudrock from 3129m (porosity 12%; TOC 22%), Magnus Field, UK North Sea (c.f. mean pore diameter 6 nm and 10th percentile 100 nm and porosity 2-3% at ca. 4000m, Brae Field area; Leythaeuser et al., 1987b), plotted for comparison alongside organic pore diameter distribution derived by CO2 adsorption on a coal (data from Debelak and Schrodt, 1979). Fractures can enhance the bulk permeability of rocks with low matrix permeability and may represent preferential petroleum fluid conduits in tight carbonate-rich source rocks (Talukdar et al., 1988) as well as clastic source rocks (Martinez et al., 1988; Lewan, 1987); and coals (Figure 6; Patching, 1965; Taber et al., 1974). Since fractures typically account for less than 2% of rock volume (Meissner, 1987; Hvoslef et al., 1988; Palciauskas, 1991) they constitute potential low-volume, high permeability conduits for efficient fluid transfer, supplementing and linking the more permeable avenues within the matrix pore network (Figure 4a-c).

29

Figure 15 Conversions between oil yield (i.e. S1 or extract yield in mg/g or kg/tonne rock) and pore-space saturations (percentage of total pore space occupied by petroleum) assuming a subsurface oily phase density of 7*105 g m-3 (approximate surface GOR 500 scf bbl-1), for rocks of differing porosity (%). Capillary pressure Capillary pressures required for a petroleum phase to enter the average or below-average pore throats in source rocks (e.g. Figure 14b) will be enormous; a further reason why most of the total inorganic porosity will not be exploited by migrating petroleum. Within the 'effective' void network, capillary pressures will be lower, especially within the additional space created if auto-fracturing results from pressure build-up during generation and / or oil cracking (Ungerer et al., 1983; Barker, 1988). Multi-phase flow, relative permeability and irreducible water saturation In a two-phase fluid system, the volumetrically subordinate phase will not flow until it occupies some critical fraction of void space. In the petroleum reservoir, two-phase flow is handled empirically using relative permeability (Longeron, 1987). Thus, primary migration will also require build-up of a critical saturation within the effective void network (Dickey, 1975; Durand, 1983; Durand and Paratte, 1983; Durand et al., 1987; Mackenzie et al., 1987; Leythaeuser et al., 1987a; Mackenzie and Quigley, 1988). A major problem arises in assessing relative permeability behaviour (e.g. for input to 'basin models'; Doligez et al., 1986; Burrus et al., 1991 and 1993). Since it is an experimentally-derived property, lacking strict theoretical foundation (Ungerer et al., 1984), and can not be measured in compacted fine-grained (including source) rocks, this introduces the need to guess, assume simple analogy with the petroleum reservoir, or extrapolate behaviour from other datasets. Setting aside pure guesswork, there are many difficulties in the analogy with petroleum reservoir rocks: wettability and sense of displacement are important. The oil phase is recovered from a water-wet reservoir by imbibition: displacement of the non-wetting petroleum phase by a wetting aqueous phase - a process accelerated by water flooding. At start-up, such reservoirs flow oily and aqueous phases at equal rates when the oily phase occupies about one third to one half of void space (Schowalter and Hess, 1982; Pepper, 1991). However, water-wet source rock pores experience increasing petroleum saturation as water is initially displaced. This is drainage: the displacement of a wetting phase by a non-wetting phase. So although simple analogy with a water-wet reservoir might initially seem appropriate, the expulsion process is actually analogous to the converse situation during oil production - i.e. water flooding of an oil-wet reservoir! Pepper (1991) argued that relative permeability to petroleum should be comparatively high at low petroleum saturations in source rocks, while Okui and Waples (1991 and 1993) made significant progress towards relative permeability

30

estimation. By studying relative permeability data on a wide range of coarser-grained rocks (Morgan and Gordon, 1970) they established relationships between relative permeability and absolute permeability / grain size, subsequently extrapolating down to the mudrock grain size range. Their most important projections were of: low oil saturation required for preferential flow in a typical oil-mature mudrock (Figure 16); and irreducible water saturation approaching 80%, consistent with observations that mudstones with porosity lower than 15% contain dominantly 'bound' water (Honda and Magara, 1982). Even clay-rich soils with porosity up to an order of magnitude higher than compacted source rocks, little of which will contain 'bound' water, can be permeated by simple hydrocarbons at only 10% saturation (Fernandez and Quigley, 1985). Thus, perhaps it should not surprising that net permeability to oil in compacted mudrocks can be quite high (e.g. 10-10 to 10-7 Darcy; Sandvik and Mercer, 1990) at low saturation.

There is similarity with the gas-water system in draining coal cleat: permeability to the gas phase increases almost immediately as gas saturation increases from zero; irreducible water saturation is high (Figure 16; Kissell and Edwards, 1975; Taber et al., 1974). Figure 16 Possible relative permeability curves for source rocks: typical reservoir behaviour from Schowalter and Hess (1982); projected effect of decreasing water saturation in oil-water system of a typical mudstone source rock with absolute permeability 10-7 Darcy (modified from Okui and Waples, 1993); measured effect of decreasing water saturation in gas-water system of a Pittsburgh coal draining under 200 psi overburden pressure (modified from Taber et al., 1974).

31

Observations of primary migration Almost all of the various independent observations we listed under 'Observations of expulsion' are difficult to reconcile with a 'primary migration' model of petroleum release (Table 2):- Table 2 Estimates of oil saturation in fine grained rocks ________________________________________________________________ Author(s) Host Fractional Basis of rock saturation estimate ________________________________________________________________ Conceptual

Dickey (1975) mudstone 0.01-0.1

Analogy

Leythaeuser et al. (1987a) 0.4 Analogy with reservoir

Measurements in organic-lean beds (primary migration pathway)

Fernandez & Quigley (1985) soils 0.1 permeation experiments

Pepper (1991) above Draupne

Fm., Ula Field < 0.08 S1 / porosity

This paper GOM hard-

pressured mdst 0.11-0.19 Extract / porosity

Measurements in coal cleat

Hvoslef et al. (1988) Hitra 0.03-0.09 Extract / fracture volume

Measurements in organic-rich source beds

Mackenzie and Quigley (1988) Various 0.4 Extract / porosity

Forbes et al. (1991) Spekk 0.5 S1 / porosity

Forbes et al. (1991) Are 0.8 S1 / porosity

Leythaeuser et al. (1987a) KCF 0.67-1.0 Extract / porosity ________________________________________________________________ Bulk petroleum release efficiency. The observation set of ten source rocks shown in Figure 2a is often cited as evidence of a dependency between release efficiency and P0: richer source rocks supposedly generate more petroleum in excess of the saturations required for preferential petroleum flow in the inorganic void network. However, an extended observation set (Figure 2b) refutes this apparent dependency, which we explain as a result of the indirect relationship between HI0 and P0 commonly seen in aquatic source rocks; Fractionation effects. We summarised above many observations which show that interactions between bulk petroleum and water-wet inorganic mineral phases are not important in petroleum fractionation. For example, Leythaeuser et al. (1983 and 1984a) observed that fractionation did not occur when a

32

migrating bulk oil phase impregnated a fine-grained organically lean lithology (siltstone). Oil yield vs. TOC plots. Small positive S1 or extract yield intercepts (<1 mg g-1) on Figures 7a and b indicate that little of the indigenous oil in source beds is associated with the inorganic void system. Furthermore, we have never observed a situation where S1 and extract yields in expulsive source rocks are constrained by an absolute ceiling (e.g. 5 mg g-1) imposed by the inorganic void system. Our experiences strongly support Stainforth and Reinders' (1990) conclusion that most of the oil in mature source beds is retained within kerogen. Electrical resistivity as an indicator of petroleum saturation. We have not observed high resistivity in organically lean rocks penetrated during primary petroleum migration: the process is efficient, involving little intermediate storage (residual petroleum left en route). Quantifying primary migration: pore saturations Estimates of petroleum saturations required for discrete phase petroleum flow during primary migration span two orders of magnitude, from 1% to 100% (Table 3). One reason for their poor consistency could be that the process of primary migration is tremendously complex and unpredictable. We would argue not. Setting apart those which have been simply guessed, reasoned, or assumed, these inconsistencies originate because the values are calculated by normalising oil yields to porosity in organic-rich rocks, without justification for the implicit assumption that the measured solvent extract or S1 yield actually resides in the inorganic void system! On the contrary, data in Figure 7 and elsewhere (e.g. Espitalie et al., 1988) clearly show that in source beds, yields record petroleum sorbed on kerogen; only a small additional component (<1 mg g-1) is attributable to the inorganic void system.

Table 3 Observations pinpointing critical petroleum release mechanism

Petroleum release phenomenon

Pore saturation exclusively

(most current models);

e.g. "5 mg/g rule"

Sorption dominant, pore saturation

low: "200 mg/gC

plus 1 mg/g rule"

Efficient oil release from rich, high quality source beds (oil prone) Yes Yes

Inefficient oil release from lean, low quality source beds (gas prone) Yes Yes

Oil sourcing from some coals; dry gas from others No Yes

Proportionality of oil content to TOC in source beds No Yes

Borehole geophysical log patterns in source beds No Yes

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Oil expulsion-fractionation by compound polarity No Yes

Oil expulsion-fractionation normal > branched alkanes No Yes

Oil and gas expulsion fractionation by n-alkane chain length Yes

(if gas phase

present)

Yes

Low oil yield observed along primary and tertiary migration pathways No Yes

Regional vertical migration through significant interburden rock

thickness

No

(or limited)

Yes

Analysis of primary migration routes. Further, unambiguous confirmation can be obtained from "control experiments" which measure petroleum concentrations along a primary migration pathway through organically lean rocks. We have never observed high residual saturations in this situation (Table 3). The process is very efficient: even in highly porous near-lithostatic ("hard") pressured Gulf of Mexico mudstones, primary migration saturations are < 20%. Our first example (Figure 17) is from an East Java Sea well penetrating an overpressured reservoir leaking oil through its organically lean caprock. Production Index (PI = S1 / [S1 + S2]) in the caprock shows that oil concentrations are abnormally high compared to the low levels attained in over- and underlying sediments (Figure 17a). This confirms the presence of migrant petroleum (Espitalie et al., 1977) witnessed during wellsite screening. However (Figure 17b), extremely low S1 yields in the leakage zone (0.1 - 1 mgS1 g-1) demonstrate that absolute oil losses incurred in establishing this migration pathway are trivial. In contrast, the coals, though premature for expulsion, already have ca. 10 - 20 mgS1 g-1 "in store".

34

Figure 17 Partial geochemical log showing leakage of oil from an overpressured oil-bearing sandstone reservoir (S: ca. 8100' or 2470m) through an organically lean caprock into a potential thief zone limestone (L: ca. 6900' or 2100m). Oil shows recorded while drilling are annotated: solid circles = oil stain; open diamonds = fluorescence. (a) PI is abnormally high (>0.1) over the leakage zone, confirming wellsite observations, but (b) absolute S1 yields are very low, showing that migration through the caprock is very efficient (c.f. Figures 7 and 18). Biomarker analysis confirms that coals between 8800-9600' (2680-2930m) are insufficiently mature and of the wrong facies to have sourced the oil. A second example (Figure 18) is from the Snorre Field, North Sea. Through what Leith et al. (1993) and Caillet (1993) interpreted as a zone of pervasive caprock failure, the yield attributable to leaked reservoir oil is no more than about 1 mg g-1; consistent with our observations of low petroleum saturation in migration routes through organically lean mudstones in the Ula region of the North Sea (Pepper, 1991), the East Java Sea and Paris Basin.

35

Figure 18 Geochemical analysis of a leakage pathway through the Shetland Group caprock of the Snorre Field, Norwegian North Sea (based on data from Leith et al., 1993). Extractable oil concentrations decrease from ca. 2 to 1 mg g-1 across the migration front; hydrocarbon contents are relatively low (ca. 30-50% versus ca. 90% in the reservoir fluid), suggesting that only about half is indigenous. Thus, migrant oil is present in concentrations no greater than ca. 1 mg g-1 (c.f. Figures 7 and 17). n-alkane ratios (e.g. nC17/(nC17+nC27) remain constant: there is no fractionation according to chain length during bulk petroleum flow. Important parameters in 'primary migration' models If primary migration were an important limiting factor in petroleum release from source beds - counter to our arguments - then the complex model required to describe it (e.g Ozkaya, 1989) would require many input variables including the rock properties: pore / pore throat size; absolute and relative permeability (Okui and Waples, 1991, 1992 and 1993) or net permeability to oil (Sandvik and Mercer, 1990); and absolute petroleum potential P0 (Leythaeuser et al., 1987a; Mackenzie and Quigley, 1988). Important fluid properties would include interfacial tension and viscosity (Palciauskas, 1991).

III: DESCRIPTION OF THE OPEN-SYSTEM MODEL Expulsion and primary migration: summary and implications for model design Expulsion efficiency is an intrinsic property of a source bed, dependent on the composition (generative vs. sorptive capability) of its internal OM mass; not on its absolute concentration. Expulsion is governed by HI0 (Figure 2a) because of the important compositional information provided by this simple parameter (Part I, Figure 3). 0.1 gOIL gC

-1 and 0.02 mgGAS gC-1 must be available (the net result of

generation and cracking processes) for expulsion of oil and gas range molecular weight petroleum to occur. Having demonstrated that source beds' internal primary migration losses are small, we focus our modelling of petroleum release on the process of expulsion. Primary migration is controlled by the total stratigraphic architecture,

36

and needs to be accounted for outside simple zero-dimensional models such as ORGAS (see Section V). In this Section we describe the model's components and input requirements, illustrate some results, and test it against data. Components of the model Oil and gas generation module Part I presented a scheme in which oil- and gas-generative kerogen portions degrade independently. Required kinetic parameters in the system of Arrhenius equations governing oil and gas generation rates are provided by A (the frequency factor), Emean (the mean activation energy) and a gaussian activation energy distribution comprising five σE (standard deviations in activation energy) about Emean. Global parameter values are assigned for both oil and gas generation by classifying the source rock as one of five global kerogen kinetic Organofacies. Oil to gas cracking module Part II described the scheme ORGAS uses to simulate concurrent oil generation and oil-to-gas cracking. The required kinetic parameters in the system of Arrhenius equations governing oil to gas cracking rates are again provided by A, Emean and a gaussian activation energy distribution comprising five σE about Emean. Parameter values are derived: A is a global value 1014 s-1; Emean and σE are predicted from HI0 of the OM, which reflects the average saturate / aromatic ratio of the generated oil and controls its thermal breakdown rate. Expulsion module Quantities of oil and gas available (i.e. after the processes of oil and gas generation and oil-gas cracking have been allowed to take place) are compared with threshold quantities required for expulsion. The Oil and Gas Expulsion Threshold (OET and GET, respectively) quantities of oil and gas at any time are defined relative to the residual organic carbon at that time.

CO(j) < WO * aO * [ CKI + CKO (j) + CKG (j) ] (6) and:

CG(j) < WG * aG * [ CKI + CKO (j) + CKG (j) ] (7) where: CO(j), CG(j), CKI, CKO(j) and CKG(j) are the carbon concentrations in oil, gas, inert kerogen and residual oil- and gas-generative kerogen, respectively, during the jth temperature step; aO and aG are sorption coefficients for oil and gas, respectively. (N.B. this differs from Pepper's (1991) notation which considered an earlier model of reactive kerogen.)

37

Equations 6 and 7 imply that expulsion thresholds are controlled partly by the rates of oil- and gas-generative carbon breakdown and, most importantly, by the constant inert carbon mass. Except in very good quality source rocks (HI0 > ca. 600 mgHC gC

-1), inert carbon (which is a chemical concept: it is not synonymous with the petrographic maceral inertinite; Part I) will comprise more than half of the initial carbon and so will play a major role in determining the expulsion efficiency at all maturation levels. Even at high levels of thermal stress, when most of the oil-generative kerogen has degraded, inert (and subordinate residual gas-generative) carbon will remain to impede oil expulsion (Pepper, 1991). This is the first of two fundamental reasons for the gas-proneness of Type III source rocks sensu Tissot (1984), with low HI0 and hence high inert kerogen content. (Part II showed the second factor to be that low HI0 kerogens generate aromatic oils which crack readily to gas.) The ORGAS algorithm: a cycle of events The results of the kinetic calibrations outlined in Parts I and II demonstrated that the processes of oil generation, gas generation and oil-to-gas cracking are (at least to some extent) concurrent processes. Modelling a system which respects this concurrency, and which is 'open' (in the sense that some of the generated petroleum can be expelled), is a matter of 'organic carbon book-keeping', performed in the order:

oil and gas inherited v

oil and gas generated from kerogen v

oil cracked to gas v

oil and gas expelled Repetition of this cycle in successive small isothermal temperature steps (1 oC) simulates a continuum. Temperature limits for the cycle would typically be 50-300 oC, covering the range of OGW and GGW in sedimentary basins unaffected by igneous intrusions. Permissible heating rates include those encountered in laboratory bulk-flow pyrolysis, e.g. 250 - 550 oC at 25 oC min-1 (1.315e13 oC Ma-1). Step 1: inheritance involves "carrying forward" to the next temperature step the residual oil and gas quantities remaining after expulsion during the previous one, ensuring a mass balance. The model starts up by "inheriting" the initial oil concentration present in all immature source rocks. Step 2: generation involves breakdown of some fraction of the residual oil- and gas-generative kerogen, producing oil and gas. Step 3: oil cracking involves breakdown of some fraction of the oil to gas. Step 4: expulsion evaluates the critical threshold quantities required for expulsion (Equations 6 and 7). If quantities of oil and gas available (after the oil

38

and gas generation and oil-gas cracking steps) are less than or equal to this critical threshold, they are carried forward, to be inherited by the succeeding iso-maturity slab; they are labelled as Residual quantities. Any excess oil or gas is labelled as Expelled. Input data requirements ORGAS is designed to require only a basic minimum of raw input data: the Organofacies and initial organic matter composition; and its thermal history. Starting organic carbon composition Routine geochemical measurements are used to divide up the initial carbon quantities in a source rock (Part I, Equations 1-10), including the inert portion important in modelling the total sorptive carbon mass. Initially, in the immature source rock, since all quantities are normalised to TOC:

CKI + CO0 + CKO0 + CKG0 = 1 (8) The required initial parameters are: Transformation Index TI0 (i.e. S10 or TSE0 normalised to TOC0), HI0, and G0 (initial gas fraction in S20). Absolute P0 and TOC0 are not required. Organofacies and HI0 are the most important inputs to be known accurately. If TI0 or G0 data are lacking they can be predicted using global correlations vs. HI0, or defaulted to global values for the relevant Organofacies (Part I, Figure 2 and Table 6). Figure 19a contrasts the calculated initial carbon composition of three different types of coal which reinforces our point (Part I, Figure 3) that the most significant difference between source rocks lies in the proportion of oil-generative vs. inert kerogen. Scaling generation profiles for each coal according to total carbon (Figure 19b-d), rather than to the carbon in P0 (Part I, Figure 18) emphasises the high sorptive potential of the typical Organofacies D/E, and particularly F, coals compared to the Torbanite.

In a closed system, with no oil cracking, carbon in generated oil (COK) and gas (CGK) would increase at the expense of carbon in reactive kerogens CKO and CKG, respectively. However, to monitor oil-to-gas conversion, further quantities CGO (carbon in gas derived from oil) and CO (carbon in remaining oil) are required (Equation 8 of Part II). (Not all these individual quantities are output - this is merely an internal 'book-keeping' nomenclature). If available quantities of oil (=CO) or gas (=CGO+CGK) in any time-step exceed the required thresholds (Equations 6 and 7), excess carbon is labelled as expelled oil (COE) and / or gas (CGE). Carbon mass in the total system is conserved at any step j in the temperature history:

CKI + CKO(j) + {CO(j)+ COE(j)} +CKG(j) + {CGK(j) + CGO(j) + CGE(j)} = 1

39

(9)

Thermal history The temperature-time history of a potential source bed can be simulated in a number of ways. Following Parts I and II, we will illustrate model results calculated at a reference constant heating rate of 2 oC Ma-1. To denote this we use the notation T2. ORGAS can also read a non-linear temperature-time history from a 1-D or 2-D thermal model. Figure 19 (a) Initial carbon composition of three coals, calculated usingEquations 1-10 (Part I). (b)-(d) Generation profiles for each, shown on a carbon basis, including the Inert portion: (b) torbanite / algal boghead coal (Organofacies C); (c) typical Organofacies D/E humic coal; (d) typical Organofacies F humic coal; (e)-(g) Mass fraction of gas in petroleum reserves of representative basins containing Organofacies C, D/E and F, respectively (data from Pepper, 1991; Macgregor, 1994). Illustrative model output graphs

40

ORGAS dumps results into a spreadsheet-based graphing package CRICKET GRAPHTM. Thus the user has flexibility in data presentation, and it is easy to test model results by cross-plotting against calibrant data imported from other databases or spreadsheets. Figures 20a - c show the full range of output fractional concentration quantities vs. temperature, for a typical Organofacies B source rock (e.g. Upper Jurassic KCF or Draupne Formations, North Sea Basin). Oil and gas concentrations are normalised to P0 [= cO0 + cKO0 + cKG0]. Absolute quantities are obtained by scaling the y-axis appropriately, e.g. residual oil concentration cO = 0.1 represents 3 mg g-1 oil in a rock with original potential of 30 mg g-1.

Figure 20 Example ORGAS output for typical high quality Organofacies B (Part I; Table 6) showing fractional quantities (normalised to P0) vs. temperature, at heating rate 2 oC Ma-1: (a) generated quantities; (b) residual quantities; (c) expelled quantities. Generated quantities: generation profiles Figure 20a shows four generated quantities: o "cO" - an area representing the cumulative oil concentration (= cO / [cO0 +

cKO0 + cKG0] );

41

o "cG" - an area representing the cumulative gas concentration ( = cG / [cO0 + cKO0 + cKG0] );

o G, the mass fraction of gas in petroleum ( = cG / [cG + cO]), on both an instantaneous and a cumulative basis.

This is the simplest graph: oil and gas accumulate as the respective kerogens break down. The upper bound of the oil-plus-gas envelope represents the cumulative petroleum generated (Hydrocarbon Generation Index HGI of Cooles et al., 1986; Petroleum Generation Index PGI of Mackenzie and Quigley, 1988). Two line graphs show the fractional gas content of the generation products on both an instantaneous and cumulative basis. The instantaneous graph predicts that very low GOR petroleum is generated over the early generation profile; dry gas is exclusively generated > 170 oC. The cumulative curve illustrates the general rule that kerogen-derived gas from "overmature" source rocks is almost always subordinate to cumulative oil (Part I, Figures 18a-e). If source rocks behaved as completely open systems (c.f. bulk-flow pyrolysis), retaining no oil feedstock for cracking to gas, then the quantities on this graph could be re-cast as expelled quantities. The graph could also present the artificial situation of a completely closed source rock in which no oil-gas cracking were permitted. However, source rocks are neither completely closed nor completely open systems. Residual quantities: retention profiles Figure 20b provides a more realistic picture of evolving oil and gas concentrations: a graph of residual quantities derived by allowing some of the products to be removed while the residual oil is progressively subjected to cracking at inceasing rates. It shows four residual quantities: o 'cO': an area representing the residual oil concentration (= cO / [cO0 +

cKO0 + cKG0]); o 'cG': an area representing the residual gas concentration (= cG / [cO0 +

cKO0 + cKG0]); o 'G': mass fraction of gas in petroleum, on both an instantaneous and a

cumulative basis (= cG / [cG + cG]). Petroleum concentrations in source rocks reflect generation processes in isolation only at low maturity levels, prior to expulsion, and before oil-gas cracking rates become significant (c.f. similar oil concentration curves on Figures 20a and b at < 110 oC). If expulsion efficiency were zero, then Figure 20b would be identical to Figure 12b of Part II - illustrating cracking in a closed-system. However, ORGAS allows the source rock to become 'open' to oil or gas when/if the residual kerogen is saturated. In expulsive source rocks, concentrations of residual oil and gas (solid areas) increase as generation proceeds, reaching inflections which mark the threshold of oil expulsion (OET) and gas expulsion (GET), respectively. OET is reached before GET. They then begin a gradual decline which occurs because the expulsion threshold is calculated by reference to total residual carbon, which

42

decreases as reactive carbon degrades until only Inert carbon remains. An oil concentration associated with inert carbon would persist at the end of the profile, but for the effect of oil-to-gas cracking which converts this residual oil to gas. Thus, a second inflection point occurs, marking an acceleration in the rate of decline, where oil-to-gas cracking rather than sorption begins to limit the oil concentration in the source rock. Since gas is not degraded, residual gas concentrations are always controlled by the expulsion threshold concentration (e.g. 0.02 g gCK-1), once reached. The G curve monitors the mass fraction of gas in the residual petroleum. Expelled quantities: expulsion profiles Oil and gas concentrations expelled at the end of each cycle are simply those in excess of the Residual quantities; when summed over the whole temperature profile they produce the cumulative expelled quantities shown in Figure 20c. Four expelled quantities are shown: o "cOE" an area representing the cumulative oil concentration (= cOE / [cO0

+ cKO0 + cKG0]); o "cGE" an area representing the cumulative gas concentration (= CGE / [cO0

+ cKO0 + cKG0]); o 'G': mass fraction of gas in petroleum (= cGE / [cGE + cOE]), on both an

instantaneous and a cumulative basis. Expelled quantities (solid areas) begin to register at temperatures corresponding to inflections in the respective residual curves. Quantitative expulsion behaviour of typical Organofacies The use of "typical" Organofacies A-F source rocks helps illustrate some fundamentally important differences in their retention and expulsion behaviour (Figure 21). Typically high quality Organofacies A-C source rocks expel oil readily, after 15-20% of P0 has been converted (PGI 0.15-0.2). Oil expulsion temperature (T2) thresholds for typical Organofacies increase in the order A-DE: 100, 110, 120, 135 oC. Organofacies D/E typically expel oil at a slightly higher PGI of 0.3, but at a significantly higher temperature, than A-C, resulting in a narrow oil expulsion window prior to acceleration of oil-gas cracking rates. The Organofacies F retention profile illustrates the behaviour of poor quality source rocks (HI0 < ca. 200 mgHC gC-1) in general, irrespective of Organofacies. The symmetry of the residual oil curve arises because: the expulsion threshold concentration of oil is never generated; and / or oil-gas cracking is fast enough to prevent this threshold concentration from being reached. Low HI0 source rocks - and those with Organofacies F generation kinetics in particular - can generate oil but typically can not expel it: they are gas-prone as a result of oil-gas cracking in a low expulsion efficiency environment. Typically high quality Organofacies A-C source rocks will expel the dominant fraction of their P0 (70-80%) as oil (c.f. Figure 2c). Organofacies D/E

43

typically expels oil, but as a subordinate fraction (ca. 30%) of P0. Thus, concerning the historical debate about whether "Type III" source rocks - including coals - can source low GOR petroleum (oil) pools: those with high enough HI0 and Organofacies D/E kinetics can; but even so their cumulative expulsion products will be gas-dominated. Typical cumulative gas fractions in the expelled products are, in the order A-F, ca.: 0.25, 0.30, 0.25, 0.65 and 1.0 g g-1. These fractions are ultimately reflected in "basin GOR" (Figures 19e-g). High quality aquatic source rocks such as the Pematang Brown Shale, Central Sumatra (Longley et al., 1990) give rise to petroleum provinces dominated by efficiently-expelled oil (e.g. Typical C expulsion profile, Figure 21); so-called "oil-prone" coals such as the Miocene Balikpapan Formation coals of the Mahakam Delta, Kutei Basin, Kalimantan give rise to "oil" provinces which are actually dominated by the gas formed from cracking of unexpelled oil (e.g. Typical D/E expulsion profile, Figure 21); poor quality coals such as the Carboniferous of the Southern North Sea Basin release hardly any of the oil they generate, and yield essentially dry gas deposits (e.g. Typical F expulsion profile, Figure 21). The high concentrations of gas expelled from the Typical F source rock is consistent with estimates of 90-95% gas expulsion efficiency attained in Palaeozoic anthracite rank coals (Stach et al 1982).

Figure 21 ORGAS output showing fractional quantities of oil and gas in: (a) residual petroleum "retention profiles"; and (b) cumulative expulsion products "expulsion profiles", for typical Organofacies A-F as a function of temperature, at reference heating rate 2 oC Ma-1. Testing against geochemical data Since ORGAS attempts to quantify two products (oil and gas) resulting from three partially concurrent processes: generation, cracking and expulsion, our

44

tests compare predicted vs. 'actual' residual or expelled quantities which are sensitive to these processes. Figure 22 shows how the model fares in predicting various calibrant organic geochemical quantities in a thick Monterey Formation source bed. Sulphur-rich Monterey OM is the source of major oil fairways both on- and offshore California (Orr, 1986). This marine source rock contains algal / bacterial OM in a matrix low in detrital clay and rich in carbonate and siliceous / cherty material: the kinetic Organofacies is A. (Since this was a dataset used in the global kinetic optimisation in Part I, this is mainly a true 'blind test' of oil cracking and petroleum release behaviours.) Initial model input parameters (TI0, HI0, G0) are the average of numerous measurements from the shallow (immature) section of the well. Carbon-mass balance used these same data as an immature reference. Figure 22 Model testing in a thick Monterey Fm. source bed. (a) cOE (concentration of P0 expelled as oil) vs. temperature (heating rate 12.8 oC Ma-1), using alternately: extract or S1 as measures of oil; S2e and Ge or S2 and G as measures of residual kerogen, respectively. (b) ORE (oil release efficiency) versus OGI (oil generation index), predicted and calculated using S1 as a measure of oil, S2 and G as measures of residual kerogen. (c) Modelled and observed PI using S1, S2, G and aO as in (b). The data-trend (solid symbols) can not be matched oby any single model curve (e.g. curves shown for HI0 = 476, 639 and 1106 mg gC-1).

45

Testing against carbon mass-balance results Generated, residual and expelled quantities output by ORGAS (e.g. Figure 21) are normalised to P0 and can only be compared with corresponding quantities derived from geochemical measurements on natural sample suites once these raw data have been manipulated using carbon mass-balance back-calculations (Leythaeuser et al., 1980; Ungerer et al., 1988; Cooles et al., 1986; Rullkoetter et al., 1988; Pepper, 1991). Some caveats in the approach, together with equations defining additional quantities, are summarised in Appendix A. Expelled quantities: extract vs. S1 comparison (Figure 22a). In the studied well, pyrolysis was performed on duplicate samples with and without pre-extraction. Pre-extraction avoids the problem of 'double-counting' which occurs when extract and unextracted S2 yields are manipulated together (Cooles et al., 1986), which is particularly acute in Organofacies A source rocks where extract yields may be five times larger than the S1 yield for the same sample. The two resulting datasets comprised: conventional S1 plus S2 yield plus G data; and extract plus post-extraction S2 yield and G data (denoted S2e and Ge). This figure tests the performance of different oil sorption coefficients: 'observations' (point symbols) are well matched by the model (curves) using the appropriate aO value: 0.1 gO gCK-1 for S1 (solid symbols and unbroken curve); 0.2 gO gCK-1 for total extract (open symbols and dashed line). In each case, observed release / predicted expulsion from the Monterey begins at low temperatures (ca. 100-110 oC) even given the high heating rate; it is ultimately efficient (cOE reaching 0.7 - 0.8). The good agreement we obtained here between predicted expelled quantities and 'observed' released quantities supports our decision to neglect primary migration effects in the ORGAS model. Expelled quantities: ORE vs. OGI (Figure 22b). This diagram compares predicted and observed ORE (oil release efficiency) versus OGI (oil generation index). 'Observations' (solid symbols) are matched by the model (solid curve) using S1 as a measure of oil, and aO = 0.1 g gCK-1: oil release begins during early generation (before 20% of oil-generative kerogen is degraded: OGI < 0.2). Thus, expulsion of 'low mature' (heavy, asphaltenic) oils is a characteristic of the Monterey petroleum system (Orr, 1986). Calibration using geochemical ratios Routine geochemical measurements of oil concentration are normalised to residual organic carbon or residual petroleum potential. ORGAS facilitates calibration by outputting these residual ratios during each model run: PI Production Index = cO / [cO+{cKO+cKG}], i.e S1/[S1+S2]. Though widely

used as a maturity index, this pyrolysis-derived ratio has no straightforward progression: S2 decreases systematically as oil and gas-generative kerogen are consumed; S1 increases progressively prior to expulsion, but then decreases due to combined effects of expulsion and / or cracking to low molecular weight products (which are either themselves expelled or, if

46

remaining, are usually lost during the normal drilling and sample handling procedures). Depending on the relative rates of generation and cracking, the net effect on PI at high thermal stress can be an increase or decrease.

HI (= 1000 * [{cKO + cKG}/W ] / [cO + cKO + cG + cKG + cKI] in mgHC gC-1). The numerator decreases systematically as reactive kerogen degrades, while the rate of decrease of the denominator depends on release efficiency: note the cO and cG terms in the denominator; the TOC of a source rock which does not expel remains constant. Thus, ratios involving the term [HI/HI0] (as used by e.g. Forbes et al., 1991) are not reliable calibrants of petroleum generation.

TI Transformation Index (= 1000 * [cO / W] / [cO + cKO+ cG + cKG + cKI]); i.e. {S1 or TSE} / TOC, in mgHC gC-1). Again, the rate at which the denominator decreases depends on expulsion efficiency. S1 increases progressively prior to expulsion, but then decreases due to the effects described for PI.

These residual geochemical ratios provide perhaps the most practical way to test the model with minimal data manipulation although, again, there are caveats (Appendix A). Figure 22c compares modelled and observed PI vs. maximum burial temperature. Here there is crude agreement between model and observation viz. the overall increase in PI between 100-170 oC, although the model curve for average HI0 = 639 mg gC-1 is much smoother than the data trend (solid symbols) which shows consistent excursions (magnitude ca. 0.1) towards relatively high followed by relatively low PI. These are most likely due to deviation in original downhole organic matter quality from the reference (immature tophole average), since their magnitude is consistent with results of re-running ORGAS with a range of initial source characteristics in the immature section (HI0 = 476 and 1106 mg gC-1, respectively). This suggests that PI is not purely a maturation index, since its rate of increase is sensitive to expulsion efficiency: PI increases most rapidly with maturity in rocks with low HI0 and hence low expulsion efficiency; in contrast PI will remain low in source rocks with extremely high HI0, and negligible Inert carbon.

IV: EXPLORATION APPLICATIONS Potential applications of the ORGAS model range from to the routine - such as calculations of expelled charge masses in petroleum resource estimation- to the unorthodox, as we illustrate below. Calculation of petroleum charge masses Calculation of the masses of petroleum available for entrapment in a given basin, or in the drainage area of a given trap, requires understanding of the overall

47

average concentration of oil or gas expelled from the source rock at increasing levels of thermal stress. Since ORGAS' output concentrations are normalised to P0, it is easy to convert concentration of petroleum of type i (oil/gas/total petroleum generated, instantaneous oil/gas expelled, or cumulative oil/gas expelled) at temperature T(j) to an absolute mass delivered to the inorganic void system Mi(j) (g):

Mi(j) = ci(j)* P0(j) * rhos(j) * hs(j) * A(j) (10) where: ci(j) is concentration of a petroleum component i (e.g. cOE; dimensionless units); P0(j) is the initial petroleum potential (g grock-1); rhos(j) is the bulk density of the source bed (g m-3); hs(j) is its thickness (m); and A(j) is the area (m2), of an 'iso-maturity slab' of source rock experiencing a mean temperature T(j). Thus P0 is just a volumetric multiplier for fractional concentrations output by the model; it is neither a model input parameter nor a determinant of expulsion behaviour. A basin geothermal profile is used to project isotherms (midpoints of sections of equal average maximum temperature, known as iso-maturity slabs) onto a stratigraphic surface representing the source bed (ideally an isopach from sediment surface to source bed mid-point). In basins with simple thermal histories (relatively uniform burial rate with no uplift and erosion), the burial rate prior to attaining maximum temperature can be used to calculate a heating rate. This eliminates the need for exhaustive 1-D thermal modelling (e.g. Forbes et al., 1991). Heating rate should never be assessed using the age of the sediments themselves; early burial and heating rates are irrelevant, since rates of reaction at temperatures less than about 70 oC are negligible even on a geologic timescale. Given homogeneous organic matter quality, the source rock may be characterised as a whole, simply by averaging required geochemical input data over the net source interval. Note that this approach becomes less appropriate as internal heterogeneity of source character increases - a particular problem in terrestrial source sequences (see below). After running a model for the appropriate source facies, each iso-maturity slab can be assigned a value of cOE / cGE, and Equation 10 used to calculate the total oil and gas mass expelled within each iso-maturity slab. (Section 5 considers the additonal problem of primary mgration.) Predicting petroleum composition and phase ORGAS' ability to account separately for oil and gas quantities enables prediction of petroleum composition. G (mass fraction of gas) is monitored throughout the expulsion cycle, on both an instantaneous and cumulative basis (Figure 23). Combined with pressure data, these quantities can be used to predict the instantaneous phase of migrating petroleum, or the evolving phase(s) of a

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petroleum accumulation. Apart from the usual exploration applications, this kind of predictive capability can help understand intra-reservoir compositional variations (England and Mackenzie, 1989; England, 1990), which originate during reservoir filling due to spatial and temporal variations in charge composition. Figure 23 Model output for the fractional mass of gas in: (a) instantaneous petroleum expelled (Ginst.); and (b) cumulative petroleum expelled (Gcum.), from typical members of Organofacies A-F at a reference heating rate of 2 oC Ma-1. Heterogeneous source rocks Although we have illustrated "typical Organofacies" behaviours, we do not propose another "Type" classification into which individual source rocks are shoe-horned. Since ORGAS requires only limited input data, individual cases are rapidly re-run; for example when evaluating the impact of natural source rock heterogeneity, most importantly HI0. This permits detailed description of the expulsion behaviour of heterogeneous sequences. This problem is most acute in non-marine basins with rapid depositional facies variations which impact OM quality, leading to different generation and expulsion behaviours in different parts of the resulting source sequence (Demaison, 1987).

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Figure 24 Modelled effect on (a) Ginst. and (b) Gcum. of a + 200 mgHC gC-1 variation in HI0 for high quality (e.g. typical Organofacies C) and mediocre quality (e.g. typical Organofacies D/E) potential source rocks. Vertical variability (Figure 24). The expulsion behaviour of high quality source rocks will be least impacted by, say + 200 mgHC gC-1, variation in HI0 (e.g. typical Organofacies C). However, where average HI0 is modest (e.g. typical Organofacies D/E with mean HI0 333 mgHC gC-1), the effect of this same HI0 variation is much more dramatic: Gcum. ranges from ca. 0.4 (slightly more oil then gas) to 1 (dry gas source throughout the expulsion profile). In such cases we would re-run ORGAS as necessary to reflect OM quality variations, and then re-composite the results into a profile weighted according to relative abundance of each OM type. These composited results can differ significantly from the results for the average. Lateral variability. Many petroleum drainage areas will be large enough that random lateral variations in initial characteristics are statistically smoothed. Alternatively, regional variations will systematically affect the composition of petroleum from one drainage area to the next (Figure 25). In such basins, it may be necessary to calculate separate local (composited) expulsion profiles, and contour the resulting cOE / cGE values with respect to facies as well as thermal stress - quite a laborious process! Pepper (1991) described an Australasian Angiosperm-dominated coal basin with local developments of exceptionally high quality coal which expel petroleum at moderate thermal stress (T2 ca. 140 - 160 oC), which is oily enough to form a single subsurface "black oil" phase. Elsewhere quality is locally poor (mean HI0 ca. 200 mgHC gC-1) and coals retain and crack much of the oil they generate, expelling only gas and low molecular weight oil desorbed at higher temperatures (Figure 25a; T2 > ca. 150 oC). This may have high enough GOR to form single subsurface gas-condensate phases (Figure 25b). Intermediate quality coals expel petroleums intermediate in composition which, unless reservoired at very high pressure, form mixed phase associations (saturated oil phases with gas caps; saturated gas-condensates with oil rims).

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Figure 25 Data from an Australasian coal-sourced petroleum province where lateral variation in coal quality determines maturity and gas-richness of expelled - and the phase state of reservoired petroleum (Pepper, 1991). Plotted against mean HI0 of local coal are (a) thermal stress level of reservoired petroleum estimated from aromatic biomarkers and (b) G of reservoired petroleum. Large open circles: subsurface gassy phase; small solid circles: subsurface oily phase; both: mixed phase. Model curves predict: (a) variation in temperature of OET; and (b) Gcum, as a function of HI0. Biogenic gas and "early condensates" Some gassy petroleums have C6+ molecular chemistry apparently inconsistent with a conventional high maturity origin. These so-called "early" or "immature" condensates (Vassoevich et al., 1969; Laplante, 1974; Connan and Cassou, 1980; Snowdon and Powell, 1982; Monnier et al., 1983) supposedly form due to stripping of low molecular weight C6+ material during expulsion of a thermogenic gas phase at low thermal stress. Alkane fractionation effects observed in Type III source rocks are consistent with this mechansm (Leythaeuser et al., 1984a; Leythaeuser and Poelchau,1991). Our kinetic parameters (Part I) predict that thermogenic gas generation rates are very low at the cited thermal stress levels (though perceptible using sensitive chromatography; e.g. Monnier et al., 1983). So, thermogenic gas expulsion is delayed by the sorptive kerogen network until T2 > 150 oC (Figure

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21; Organofacies D/E). However a different result occurs if sorptive sites are "presaturated" during biogenic gas generation, an idea supported by Friedrich and Juntgen's (1972) discovery that methane most tightly sorbed on highly mature coals (1.0-1.25 % Ro) had a biogenic isotopic signature. Though ORGAS is an exclusively thermogenic model, we can simulate this situation by setting aG to zero (Figure 26). The result is an initial window of dry gas expulsion; G falls to a minimum during early oil expulsion, rising later as thermogenic gas expulsion rates increase. The period prior to the G minimum might correspond to the "early condensate" window. Even so, this early-expelled gas charge will be minor compared to the later thermogenic charge. Figure 26 Possible "early condensate" expulsion phenomenon simulated by "pre-saturating" kerogen with biogenic gas. Curves show the predicted evolution of Ginst and Gcum calculated for typical Organofacies D/E OM (Part I, Table 6). Expulsion during uplift and erosion Conventionally, the burial cycle is attributed with the driving energy - increasing pressure and temperature - for petroleum migration. ORGAS responds to cooling during uplift and erosion like any other kinetic model, by decreasing the rates of the chemical reactions which provide the expulsion feedstock. However, if aG and aO are pressure-dependent, this generalisation may break down. Figures 12 and 14 suggest that gas sorption capacity should decrease rapidly during at least the last 2 km of overburden removal, consistent with the co-occurrence of coalbed and conventionally-reservoired gas deposits at shallow depth in uplifted basins (e.g. Iannacchione and Puglio, 1980). Gas expulsion during "basin-scale desorption" will be limited by the saturation value of aG (0.02 g gCK-1). This is low compared to expellable gas potential during burial (i.e. the product [cGE* HI0]). Thus, such an expulsion mechanism will be volumetrically significant only in highly organic-rich -

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particularly coal-bearing - sedimentary successions. The methane-rich Elmworth dry gas field, Western Canada (Masters, 1984) may be a spectacular example. Welte et al. (1984) showed that gas concentration gradients in the field are best explained by dynamic charging, i.e. with gas being continuously supplied up to the present; however this is inconsistent with the burial history of the basin, which has been substantially uplifted, eroded and cooled since the Oligocene. Our proposed desorption model offers a solution consistent with these constraints and also with the methane-richness of the reservoired gas: progressive desorption of part of the 2.2 X1015 g (116 trillion scf) of methane originally stored in the basin's recognised164 billion tons of low ash coal (Figure 13c; data from Wyman, 1984; these projections do not account for other organic-rich beds in the 2 km thick series). This mechanism also offers an explanation for relict abnormal pressures in source beds, in uplifted and eroded basins where overpressure generated by compaction disequilibrium processes has long since dissipated in surrounding organic-lean beds (e.g. Williston Basin; Burrus et al. 1993). Case history: Malacca Straits, Indonesia We conclude this Section by applying ORGAS in an Indonesian coal-bearing basin: the Malacca Straits area, Central Sumatra, Indonesia. We revisit a published quantitative case study of charging and migration losses involved in the pooling of waxy non-marine oils (see Macgregor and Mackenzie, 1986, for supporting information; also Mackenzie and Quigley, 1988). To ensure a fair comparison of models, we have ignored all subsequent information in our re-evaluation, which concerns only the issue of expelled oil charge. Assuming Lower Miocene Sihapas Formation coals as the principle source rock, Macgregor and Mackenzie (1986) defined kitchens using an oil release window between 120 - 150 oC (Figure 27): a global rule of thumb emerging from Cooles et al. (1986) study of ten source rocks. This was supported by a carbon mass-balance calculation for the Sihapas coals. Compare this with ORGAS modelled expulsion behaviour for a typical Organofacies D/E (i.e. most Indonesian Tertiary) coal, which predicts oil expulsion > ca. 140 oC at 6 oC Ma-1; the oil expulsion window is narrow and is soon followed by thermogenic gas expulsion at ca. 160 oC.

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Figure 27 Proposed expulsion profiles for coaly Sihapas Fm. potential source rocks: Macgregor and Mackenzie's (1986) bulk petroleum release curve projected early (>120 oC) and efficient oil release; ORGAS output (cOE and cGE area curves) for 'typical' Organofacies D/E OM (initial characteristics TI0 = 7 mgHC gC-1, HI0 = 333 mgHC gC-1; G0 = 0.24; Part I, Table 6) has a high oil expulsion threshold (>140 oC) and implies a low expulsion efficiency. These differences can be reconciled: the dataset on which Cooles et al. (1986) formulated their global rules of thumb did not include coals (Figure 2a); Macgregor and Mackenzie (1986) did not apply the large corrections which we believe are necessary to account for losses in the low molecular weight range of coal samples (Appendix A). The consequences for resource potential of the Sihapas coals are dire: the extensive and volumetrically significant Sihapas kitchen (Figure 28a) is replaced by a trivial area of marginal oil expulsion in the basin axis (Figure 28b).

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Figure 28 Comparison of oil-expulsive kitchens implied by curves in Figure 27. Black dots are control wells. Maps derived by superimposing iso-cOE values on mid-Sihapas isotherms: (a) Macgregor and Mackenzie's (1986) widespread kitchen; (b) ORGAS-based projection of a kitchen of insignificant area. Macgregor and Mackenzie (1986) recognised an alternative potential source for the basin's waxy oil pools, then unproven: the freshwater lacustrine Pematang Formation, a syn-rift deposit in the adjacent Central Sumatra Basin (Katz, 1991) which has sourced some 13 billion barrels of oil reserves. Similar wax-prone Pematang facies have since been drilled in the Malacca Straits and oil-source correlation studies have confirmed them as the working source rock (Longley et al., 1990). While this does not invalidate quantitative resource assessment using charge volumetrics and migration losses, it does serve to illustrate - retrospectively - an example where ORGAS would have proved more accurate in assessing the oil resource potential of the coals.

V: PRIMARY MIGRATION AND BASIN ARCHITECTURE Primary migration occurs when petroleum eventually exploits the more permeable avenues of the inorganic void systems of fine grained rocks; an exception may occur where a low-ash coal lies in direct contact with a secondary migration avenue. The process is very efficient: we estimate losses of the order 1 mg g-1 or less; past estimates ca. 5 mg g-1 confused oil present in the organic vs. inorganic networks. Primary migration efficiency is not an intrinsic property of a source bed - except where a source bed lies in direct contact with a secondary migration avenue - since losses will occur in the whole volume of source and non-source

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lithologies separating kerogen-rich zones from potential secondary migration avenues. Primary migration is controlled by the total stratigraphic architecture, so it needs to be accounted for outside simple zero-dimensional models. Although rigorous treatment of the problem requires some kind of 1- or 2-D multi-phase fluid flow modelling approach, we have found it useful for the purposes of resource estimation to treat it as a mass balance problem. We apply a primary migration loss factor, just as secondary migration losses may be handled in geochemical resource assessment (Mackenzie and Quigley, 1988). Thus, before product masses from Equation 10 are summed over the expulsion kitchen for the play fairway or prospect, as appropriate, losses occurring during primary migration must be accounted for. Equation (10) can be modified:

Mi(j) = [(ciE(j)* P0(j) * rhos(j) * hs(j)) - (si * rhom(j) * hm(j))] * A(j) (11)

where quantities were defined in Equation 10 except: the fractional loss factor si [g grock-1; sO lies in the range 0.0001 to 0.001]; rhom(j) which is the bulk density of rocks along the primary migration route [g m-3]; and hm(j) which is the height of vertical migration. Limits on vertical migration distance can be evaluated by rearranging Equation (11) with Mi(j) set to zero.

ciE(j) * P0(j) * rhos(j) * hs(j) hm(j) = ___________________ (12)

si * rhom(j) Furthermore, the potential distance of primary oil migration (provided expulsion has occurred) will be constrained by a source bed's ultimate genetic potential (UGP) - the numerator of Equation 11 evaluated when ciE has its PGI=1 value. The lower the UGP, the shorter the permitted distance between source and secondary migration avenue; internal losses may not be overcome in the worst cases. Resource potential: implications of different models Most extant approaches treat petroleum release as a primary migration / inorganic void saturation problem or else simply relate petroleum release efficiency to maturation level, without any attempt to be deterministic. In this final section of the paper we use Figure 29 - a quality / yield matrix - to compare their implications for petroleum resource potential (e.g. critical P0 ca. 5 mg g-1) with those of our organic sorption based model (critical HI0 ca. 200 mgHC gC

-1).

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Figure 29 Location of five illustrative source rock fields on a quality (HI0) vs. richness (P0) matrix: (1) rich, high quality marine source rocks; (2) rich, high quality lacustrine oil shales and boghead coals; (3) humic coals; (4) source rocks with modest richness and quality; (5) lean, poor quality source rocks. Fields 1 and 2 represent aquatic source rocks, rich in high quality algal / bacterial biomass: Field 1 contains the marine source rocks which have sourced most of world's oil resources (Klemme and Ulmishek, 1991); Field 2 contains lacustrine source rocks which are economically important in the Far East (Katz, 1990 and 1991). Due to combined richness and quality (P0 >> 5 mg g-1 and HI0 >> 200 mgHC gC

-1) high oil release potential will be assigned using either approach. Ironically, the source rocks which - for sound economic reasons - are most frequently studied are actually the least useful in testing petroleum release concepts! By substituting reasonable values for typical Organofacies A, B, or C in Equation 12 (e.g. cOE = 0.7; P0 =0.03; rhos = 2.4 X106 g m-3; hs = 50m; rhom = 2.5*106 g m-3), and taking sO = 0.0005 (i.e. roughly the midpoint of the range 0.1 < sO < 1 mg g-1) it becomes apparent that substantial vertical migration is possible: in this case, when fully mature, 2 km. Thus, such source beds, even when buried deeply by thick sedimentary piles such as the Tertiary Gulf of Mexico delta system, can charge prolific fairways at much shallower depths.

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Vertical migration distances would be much more limited - of the order 200m in this case - if si were an order of magnitude larger i.e. 0.005 (5 mg g-1). However, differing behaviours are predicted for source rocks plotting elsewhere on the matrix. Field 3 contains a family of source rocks whose petroleum potential has been widely debated: the humic coals (Durand and Paratte, 1983). We have emphasised that the key to understanding oil expulsion capability of coals lies in organic quality rather than richness (Figures 24b and 25). It is our experience in humic coal-bearing basins (Figures 19f and g) that coal-sourced petroleum systems are relatively oily when significant proportions of the coal population has HI0 >> 200 mgHC gC

-1 (e.g. Mahakam Delta, Kalimantan: GOR of reserves ca. 104 scf bbl-1); exceedingly gas-rich petroleum systems result when significant proportions of the coal population has HI0 << 200 mgHC gC-1 (e.g. Southern North Sea Basin: GOR 105-106 scf bbl-1). Our projections are generally consistent with global observations of oil and gas reserves tied to coal source rocks (Macgregor, 1994). For 2 km vertical migration to occur from a fully mature low-ash coal source rock (cOE = 0.3; P0 =0.22; rhos = 1.35 X106) the bed thickness hs(j) would need to be 30m. Field 4 comprises source rocks with, at best, modest richness and quality (e.g. Upper Jurassic and Lower Cretaceous marine mudrocks on the northwest Australian continental margin; some zones of the Upper Jurassic Heather Formation of the UK North Sea Basin). While "pore saturation" models would largely relegate such rocks to potential gas sources, our model permits - so long as HI0 exceeds ca. 200 mgHC gC

-1 - some fraction of P0 to be expelled as oil before the gas expulsion window is entered. However, vertical migration will be increasingly limited as the product (ciE(j) * P0(j)) approaches si, eventually constrained within the source bed itself as hm(j) / hs(j) approaches unity, when:

ciE(j) * P0

(j) = si (13) As P0 drops significantly below 5 mg g-1, any oil concentrations successfully expelled from kerogen will become increasingly sensitive to the internal primary migration losses which can largely be ignored in predicting the behaviour of richer source rocks. Also, significant thicknesses will be required for volumetric significance after external migration losses are overcome. Substituting again in Equation 12 reasonable values for a source rock of modest quality and potential (cOE(j) = 0.3; P0(j) =0.004; rhos(j) = 2.4*106), 2 km of vertical migration could only occur if 900m of that thickness were source rock itself! In such situations, exemplified by the Australian NW Shelf, the stratigraphic architecture begins to exert strong control on whether petroleum accumulation is possible: presence of carrier / reservoir beds within or next to the source bed becomes a deciding factor; so does the presence of occasional high quality, high

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potential source beds in a sequence where the role of the remaining source rocks is mainly to "prime" the migration pathway out of the gross interval. While such source rocks are rarely responsible for prolific petroleum systems, reluctance to recognise their capability to charge modest oil fairways can lead to a great deal of wasted geochemical effort whereby increasingly obscure undrilled locations in the basin are proposed as the location of the 'actual' source interval. Because of the general observation that lean source rocks with very low potential (P0 << 5 mg g-1) typically also have low organic quality (HI0 << 200 mgHC gC

-1), both approaches agree on the lack of oil potential associated with source rocks in Field 5, whose resource potential would widely be accepted as minor, gas-prone, irresspective of stratigraphic architecture.

CONCLUSIONS Petroleum moves from kerogen to secondary migration avenues in two steps: expulsion is the release of petroleum from kerogen, where it is generated; primary migration is the movement of petroleum through the inorganic pore / fracture (void) networks of fine grained rocks. Expulsion is controlled by kerogen's ability to sorbe (adsorb / absorb) petroleum, hence ultimately by the relative proportions of generative (Reactive)vs. retentive (Inert) kerogen. These proportions are reflected in the initial Hydrogen Index (HI0). HI0 > ca. 200 mgHC gC-1 distinguishes OM with the potential to expel oil from OM which retains all generated oil by sorption. Source rocks with higher HI0 expel oil earlier and more efficiency. HI0 also controls intra-source cracking. Low HI0 OM generates aromatic oils which crack more rapidly than the saturate-rich oils generated by high HI0 OM. Thus, lower HI0 source rocks are affected by increasingly inefficient and late expulsion of oil, which is increasingly quickly cracked to gas. Equally important is the kinetic Organofacies, which governs the thermal stress required for kerogen to generate petroleum. We recognise five global kinetic Organofacies A, B, C, D/E and F which generate oil at thermal stress levels increasing in the same order. Many source rocks with low HI also belong to Organofacies D/E, and especially F, and so suffer even further from concurrent generation and cracking of oil in a low expulsion efficiency environment. Variations in Organofacies kinetics, and in the HI0 typical of each Organofacies, lead to consistent variation in expulsion threshold temperatures (oC): (A) 100; (B) 110; (C) 120; (D/E) 135; (F) cannot expel oil; at a reference heating rate of 2 oC Ma-1. Each order of magnitude increase (decrease) in heating rate elevates (depresses) these thresholds by 15 oC. Ultimate cumulative gas yields (as a mass fraction of total expelled petroleum) from each typical Organofacies also vary: (A) 0.25; (B) 0.30; (C) 0.25; (D/E) 0.65; (F) 1.0.

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Once petroleum enters the source rock's inorganic void network, primary migration begins. Its effectiveness is determined by a source rock's initial petroleum potential (P0). However, primary migration is efficient, with minimal saturation losses. Past estimates of losses in the 5 mg g-1 region in source rocks have confused organic- and inorganic void-derived quantities. Primary oil migration losses sO are of the order 1 mg g-1 or less. The effectiveness of primary oil migration from source rocks (provided HI0 > ca. 200 mgHC gC

-1) is therefore constrained by the product [cOE*P0) and the stratigraphic architecture: vertical migration from thick, rich, high quality source beds may be several km; but as the value of this product decreases to approach the value of sO, the shorter will be the permitted distance between source bed and secondary migration avenue and the more important will be an understanding of stratigraphic architecture of the basin. ORGAS provides very similar predictions to 'pore saturation' models for release efficiency from rich, high quality source beds, but offers greater predictive capability for understanding the behaviour of source rocks with low-modest potentials, and of coals. Humic coals in particular have been the subject of great debate, with opposing views expressed throughout the last decade concerning their oil resource potential. Our model suggests that all views are correct, up to a point. Humic coals belong to Organofacies D/E/F and have HI0 values which span the critical 200 mgHC gC

-1 value. Those with Organofacies D/E kinetics and HI0 > 200 mgHC gC

-1 are able to expel some of their potential as oil; the rest are not! Acknowledgments We thank the management of BP Exploration for permission to publish; Drs. D. Mann and A. Barwise of BP Research who re-wrote the original Vax-based ORGAS code for the Apple MacintoshTM; Dr. R. Miller for the KCF data on Figure 7a; R. Drozd for the Monterey data on Figure 22; Dr. C. Cornford and D. Macgregor for reviews of the first draft; Misran and the Jakarta drawing office; Ade and Agus for technical assistance; and Drs. C. Travis and Z. Yu for comments on a revised manuscript. ASP thanks ICP, KJP and RCP for their support and patience.

APPENDIX A PRACTICAL DIFFICULTIES IN MODEL CALIBRATION

As a measure of total oil concentration in a rock, the S1 yield will be an under-estimate since the lighter ends of the C6+ spectrum are prone to loss during drilling, recovery and handling, while the heavy non-hydrocarbons are not volatilised (Forbes et al., 1991). Thus, data must be corrected before use in calculations (Cooles et al., 1986; Price, 1989; Forbes et al., 1991; Pepper, 1991).

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Cooles et al. (1986) used an average correction factor Z, estimating that about 35% of the total oil concentration was lost during work-up of a conventional C15+ organic extract; they treated S1 yields in the same way. However, an average correction factor may be inappropriate if the molecular weight range of the residual petroleum decreases with increasing maturity, when underestimation of total C6+ oil present in the source rock will lead to overestimation of 'observed' expulsion efficiency. Coals are particularly susceptible to this effect: Durand et al. (1987) showed that the proportion of volatile products in pyrolysis effluent compositions of Mahakam Delta coals increases dramatically with maturity. Even worse, gas quantities predicted by ORGAS will remain largely untestable in the absence of reliable methods of measuring or estimating virgin gas concentrations in geochemical samples. Uncorrected gas and low molecular weight C6+ petroleum losses may be the cause of high apparent (oil) release efficiencies reported for coals from the Mahakam and Gippsland (Macgregor and Mackenzie, 1986) and Australian Cooper-Eromanga and Clarence-Moreton basins (Powell and Boreham, 1994). Petroleum Release Efficiency (PRE), can be calculated using an estimated gas correction. Pepper (1991) used corrections derived from closed vessel pyrolysis of comparable source rock samples. The effects on PRE were relatively minor for high quality source rocks, but quite dramatic for coals. Thus, although PGI will be unaffected: PGI =1- [{CKO + CKG} / {CO0 + CKO0 + CKG0}] (A1) PRE will be affected:

PRE = 1- [{CO + CG} / [{CKO0 + CO0 + CKG0} - {CKO + CKG}]] (A2)

Overall, there are fewer uncertainties in calibration using quantities which avoid gas quantities, viz. Oil Release Efficiency (ORE) and Oil Generation Index (OGI):

OGI = 1- [CKO / {CO0 + CKO0}] (A3)

ORE = 1- [CO / [{CKO0 + CO0} - CKO]] (A4) Even OEE determined from back-calculation of field sample data will always be an apparent maximum (OEEapparent) since, the residual quantity CO is affected by removal of oil by thermal cracking as well as by expulsion! For completeness, the gas quantities are:

GGI = 1- [CKG / CKG0] (A5)

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