liquid-rich shale versus conventional depletion performance

SPE 167788

Liquid-Rich Shale Versus Conventional Depletion Performance Guowen Lei, FMC Technologies, Nan Cheng, Statoil, Curtis Hays Whitson, NTNU/PERA

Copyright 2014, Society of Petroleum Engineers This paper was prepared for presentation at the SPE/EAGE European Unconventional Conference and Exhibition held Vienna, Austria, 25–27 February 2014. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessar ily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract This paper evaluates fundamental differences in depletion performance of wells producing from ultra-low permeability

1

(“shale”) reservoirs and wells producing from conventional reservoirs, with the ultimate goal of defining what differentiates

“conventional” from “shale” performance. It attempts to answer the question – what permeability range defines “ultra-low”

depletion performance and what permeability range defines “conventional” depletion performance – with the intermediate

permeability range being a transition from ultra-low to conventional behavior. We “map” the transition from conventional

depletion performance to “shale” depletion performance in terms of formation permeability.

In this study we compare depletion performance for reservoir permeabilities ranging from 10 nD to 100 md, with PVT, relative

permeability functions, and other rock properties being the same for all simulation cases. Four reservoir fluid systems, ranging

from rich gas condensate, near-critical oil to light oil, were used in this study. A one-section drainage area was used even

though we are aware that shale resources are often developed with smaller well spacing (typically 80- or 160-acre strips, ~ one

mile long).

Depletion performance of conventional gas condensate and oil reservoirs - where oil recovery and producing gas-oil ratio

(GOR) are independent of permeability and flowing BHP, is valid for k > 0.1 md. At permeability levels of ~ 0.001 md (1000

nD) or less, the depletion performance of shale and ultra-tight reservoirs is characterized by that producing GOR is a strong

function of flowing bottomhole pressure (BHP) and degree of undersaturation (Whitson and Sunjerga, 2012).

Our results from this study show that conventional reservoir performance, depending somewhat on the reservoir fluid system,

is observed for k > 0.5 md, while ultra-tight “shale” performance is found for k < 1000 nD (0.001 md), with a gradual

transition between these permeability values and shale-like depletion performance appearing already at 0.01md.

Introduction Conventional and ultra-tight shale reservoirs differ fundamentally in the magnitude of rock permeability, with shale and ultra-

tight reservoirs ranging from 10 to 10,000 nD (0.01 md) and conventional reservoirs with permeability up to 10 D (10,000

md).

Conventional depletion performance2 of gas condensate and oil reservoirs is characterized by a unique relationship – oil and

gas recovery factors and producing GOR for oil or oil-gas ratio (OGR) for gas condensate correlate solely with volumetric

average reservoir pressure. This unique relationship is defined (for a specific reservoir volumetric unit) by material balance

equations that consider the effects of PVT and relative permeability on oil and gas recoveries and producing GOR at any stage

of depletion. It is also known that the recoveries and producing GOR performance of a conventional depleting reservoir is

more-or-less independent of the reservoir permeability, hydrocarbon pore volume (porosity, thickness, connate water

1 We refer to ultra-low permeability systems as “ultra-tight”, with these systems typically being shale, silt, or rocks with high shale/silt content. Permeabilities of ultra-tight reservoirs are, based on results in this paper, usually <5,000 nd but may be as high as 0.05 md (50,000 nd). 2 We consider, for the purpose of this paper, conventional depletion performance to describe pseudosteady state (boundary-dominated) flow behavior during

most of the ten-year production horizon considered in our analysis.

2 SPE 167788

saturation), and well drawdown (flowing BHP).3

Liquid-rich shale reservoir (LRSR) depletion performance is only now being understood, based on modeling studies and field

performance. Quantifying differences in LRSRs depletion performance from conventional reservoirs is important for proper

engineering and development of these new resources. Liquids production forecasting and recovery enhancement is a direct

result of quantified depletion performance.

Ultra-tight (e.g. shale) gas condensate and oil reservoirs do not show the same type of depletion performance as conventional

reservoirs (Whitson and Sunjerga, 2012). For example, gas condensate shale reservoirs tend to produce with an OGR more-or-

less equal to the solution oil-gas ratio (rs) at the current flowing BHP, independent of the initial solution OGR and degree of

undersaturation. For oil shale reservoirs, however, it is shown that the recovery and producing GOR depletion performance

varies with the flowing BHP, the initial solution GOR, and degree of undersaturation.

The concept of volumetric average pressure in ultra-tight reservoirs is not useful because it totally depends on the total

drainage area (arbitrarily) assigned to a well, and because the depletion is localized to the inter-fracture volumes and a limited

distance away from the fracture tips. Also, it is practically impossible to determine volumetric average reservoir pressure

during a shut-in period of wells producing from ultra-tight reservoirs, even after months of shut-in. We strongly recommend

against using the concept of volumetric average reservoir pressure when evaluating ultra-tight reservoir performance.

For many of the same reasons that average reservoir pressure is not a useful concept in characterizing ultra-tight reservoir

performance, oil recovery factor is also difficult to use consistently. The cumulative oil produced can be independent of the

outer drainage volume that may, for practical purposes, be undepleted. The arbitrary assignment of drainage volume to such

wells makes recovery factor of little use. The cumulative oil produced (i.e. oil reserves) of a well producing from ultra-tight

reservoirs is more-or-less unaffected by the assigned drainage area (non-contributing area). Gas recovery factor is, for the

same reasons, not a useful quantity in these reservoirs.

In summary, the use of average reservoir pressure and recovery factors is of little value in characterizing ultra-tight reservoir

performance because these performance metrics depend strongly on the assumed well spacing – because well-to-well

interference has little impact on short-term (1 - 3 year) “economic recovery” in ultra-tight reservoirs.

Given the radical differences in depletion performance of conventional liquid-rich reservoirs (Muskat, 1949; Craft and

Hawkins, 1959; and Dake, 1978) and ultra-tight liquid-rich reservoirs (Whitson and Sunjerga, 2012), and the need to

understand what range of permeabilities lead to each type of performance, we endeavored to find some performance metric

that clearly maps the two behaviors, and allows definition of the transition from one to the other.

Common Well Performance Indicator Conventional reservoir depletion performance can usually be quantified independent of well dimensions – e.g. well spacing,

formation thickness, and well completion – using average reservoir pressure as the dependent variable to compare oil recovery

and gas-oil ratio (GOR) behavior. This can be done because pseudosteady state is reached in a relatively short period (days,

weeks or months). However, such an approach can generally not be used for ultra-thigh and low-permeability systems.

It is a challenge to compare depletion performance of conventional and ultra-tight reservoirs without using average reservoir

pressure, recovery factors, and producing GOR. We decided to use an economic metric for studying depletion performance for

a range of permeabilities from 10 nd to 10 md.

We define an economic well performance indicator for all permeability cases studied. We always used a well with

performance that delivered the same revenue after the first ten days of production: either 0.5 million USD for higher-GOR

fluid systems (~ 4,000 - 6,000 scf/STB corresponding OGRs of 250 - 167 STB/MMscf); or 1.0 million USD for moderate-

GOR (1,000 scf/STB) fluid system.

All wells that are compared for a given fluid system have the same characteristics: (1) thickness, (2) porosity, (3) connate

water saturation, (4) relative permeabilities functions, and (5) total well drainage area. For a well with specific permeability,

the well completion and well flowing BHP control were determined to yield the common 10-day revenue. For low-

permeability cases, the number of vertical fractures along a one-mile-long horizontal well was altered to achieve the 10-day

revenue. At some permeability, a single vertical fracture (in a vertical well) was sufficient to deliver the common 10-day

3 Conventional depletion performance ignores strong gravitational segregation that may exist in very-high permeability reservoirs. However, conventional depletion performance is also observed in gas-coning wells, as first discussed by Muskat in 1937 (pp. 687-692). More-recent studies have shown that

Muskat’s arguments are validated using detailed 3-dimensional reservoir simulation of gas-coning (and water-coning) systems, where producing GOR and

water-cut are found to be more-or-less constant as a function of drawdown (W. Astutik, MSc Thesis, NTNU 2012, “IPR Modeling for Coning Wells”).

SPE 167788 3

revenue. For even higher permeabilities, we still used the single vertical fracture completion but altered the target (maximum)

gas flow rate to achieve the 10-day revenue.

Depletion performance of all wells with widely varying permeability but satisfying the 10-day revenue requirement was

simulated for a ten-year production period. Depletion performance was initially quantified by oil and gas rates, cumulative oil

and gas production, and total well revenue. Ultimately we found that a revenue ratio, defined as well revenue at one year to the

10-day revenue value, helped categorize reservoirs into “ultra-tight”, “conventional”, and “transition” performance behavior

(Fig. 1). Ultra-low permeability performance was found consistently for all fluid systems considered when permeability was

less than ~ 0.005 - 0.05 md (5,000 - 50,000 nd), with conventional performance observed for permeabilities greater than about

0.1 – 1.0 md. The transition from ultra-tight to conventional for a given fluid system was about 1.5 (1 - 2) log cycles of

permeability.

For any system having ultra-tight or transition performance characteristics, conventional reservoir engineering methods (i.e.

material balance) will in general not be applicable and a more detailed, single-well numerical model should be used to forecast

depletion performance – performance that will be strongly affected by transient multi-phase flow behavior.

We, however, recognize that the revenue ratio versus permeability has a similar shape for single-phase reservoirs, with similar

limiting upper and lower bounds. We also recognize that the revenue ratio for such single-phase systems can be calculated

analytically from appropriate dimensionless rate solutions, expressed as the ratio of cumulatives at 365 and 10 days. Our

analysis of two-phase flowing systems with varying initial fluid composition will deviate from these analytically-derived

trends, as we take into account the relative value of gas and oil products and their producing ratio variations with time. Use of

a revenue ratio seemed to be the best means of capturing depletion performance variations with formation permeabilities.

Conventional Decline Curve Analysis The use of Fetkovich decline curve analysis (M. Fetkovich 1980) that accounts for both infinite-acting (“transient”) and

pseudosteady state decline performance can be used in certain situations for ultra-tight and transitional reservoirs, and almost

always for conventional reservoirs. A primary flowing phase (sales product) is chosen to history match and forecast using the

generalized Fetkovich decline curves. Superposition may be required when flowing BHPs are not constant, a method that has

some challenges for high-GOR two-phase flowing systems.

Predicting or correlating production rates of the secondary phase – condensate for gas condensate fluid systems and gas for oil

systems – is usually based on conventional material balance methods that correlate GOR (or OGR) to average reservoir

pressure. This is not applicable for ultra-tight and transitional reservoirs, where producing GOR may be strongly correlated

with flowing BHP, degree of undersaturation, and may exhibit severe hysteresis effects caused by changing BHPs (e.g. shut-

ins). Where the secondary “oil” phase has particularly economic impact – for most liquid-rich reservoirs – forecasting the

variation of liquid yield (OGR) with time is very important, we recommend the use of history-matched numerical well models

instead of conventional or empirical methods that may have substantial uncertainty for these ultra-tight and low-permeability

reservoirs.

Resource Recovery, Economic Recovery, and Well Spacing in Ultra-Tight Reservoirs “Resource recovery” in conventional reservoirs producing by pressure depletion is typically 60 - 95% for gas and 15 - 25% for

oil. This is the expected recovery to a low abandonment pressure. Regulatory bodies often focus on maximizing resource

recovery, but usually take into consideration some economic factors of the companies developing the resource. The most-

common economic consideration is net present value of a resource development, and not necessarily how long it takes to make

the profit. Projects are typically 10 - 30 years with profitability requiring sometimes taking a decade from discovery to

production start (e.g. offshore projects).

The time perspective of “economic recovery” for wells producing from ultra-tight reservoirs complicates the assessment and

comparison of depletion performance with that found in conventional reservoirs. Economic recoveries of ultra-tight reservoirs

are usually considered as the production required within a year to recover all well costs and start making a profit. Wells that

have high economic recoveries or short payout times are often considered to produce from “sweet spots” (due to ‘higher’

permeabilities in the vicinity of a well). Operators seldom value long-life reserves in ultra-tight reservoirs – reserves that may

be significant, but require decades to produce – if they do not see early payout.

One consequence of short-term economic perspective controlling the development of ultra-tight reservoirs is that more wells

(i.e. smaller well spacing) will be attractive in sweet spots with higher permeabilities. The reason is that short-term

profitability may not be adversely affected by well-to-well interference caused by small well spacing. The ultimate (20 - 30

year) oil and gas recovery from sweet spots with small well spacing may be relatively high, even comparable with

conventional reservoirs.

4 SPE 167788

This is in contrast to the expected ultimate oil and gas recoveries from “less-sweet” spots where wells may not break even

within the first 3 - 5 years. These less-sweet areas need many wells (small well spacing) to achieve conventional depletion

recoveries within a reasonable period of time (20 - 30 years), but few operators are willing to drill the required number of

wells because of a late economic return, even if the project has a long-term positive net present value.

The bottom-line consequence of development strategies for ultra-tight reservoirs, with emphasis on fast payout, is that sweet

spots will be developed with high resource recoveries, while lower-permeability areas will have low resource recoveries. From

a resource conservation perspective, the development of areas that are “less-sweet” will require other economic incentives to

achieve development with well spacing that leads to higher, conventional-like ultimate resource recoveries.

Numerical Model In this study we have conducted numerical modeling of one-half of a hydraulic fracture and a horizontal well using a finite-

difference simulator (Coats Engineering 2013). The numerical model assumed a well spacing of 640 acres (5280 x 5280 ft).

The hydraulic fracture and its tip were very finely gridded (0.01 ft). Grid blocks away from the fracture and the fracture tip

increased logarithmically in size (Fig. 2).

Table 1 gives the well data and the reservoir data for different cases. We assumed that traditional rock relative permeabilities

are applicable to shales and ultra-tight rocks. All cases presented in this paper used saturation exponents of 2.5. Concepts of

critical gas and residual oil saturations were also assumed to be valid for ultra-tight systems.

We have studied two groups of fluid systems, namely Higher-GOR fluids and Moderate-GOR fluid. The Higher-GOR fluids

consist of (1) a rich gas condensate (initial OGR of 150 STB/MMscf), (2) a near-critical oil (initial GOR of 4170 scf/STB),

and (3) the same gas condensate as (1) but initial reservoir pressure being 10,000 psia – highly-undersaturated. The Moderate-

GOR fluid is an oil with the initial GOR of 1,000 scf/STB.

Black-oil tables used in this paper were generated based on two equation-of-state (EOS) models, one for the Higher-GOR

fluids (Whitson & Sunjerga, 2012), and the other for the Moderate-GOR oil shown in Table 2. Figs. 3 - 4 show the solution

oil-gas ratio and viscosity variation with pressure for the Higher-GOR fluids and Figs. 5 - 6 show the solution oil-gas ratio and

viscosity variation with pressure for the Moderate-GOR fluid.

Each well model was controlled by a maximum gas rate and a minimum BHP (500 or 750 psia) such that it delivered a

revenue of 0.5 million USD within the first 10 days for the Higher-GOR fluid wells, and 1.0 million USD within the first 10

days for the Moderate-GOR fluid wells. The revenue model is based on the assumptions given in Table 3.

The number of fractures in each well model case varies for a given reservoir permeability. For low-permeability cases, the

number of vertical fractures along a one-mile-long horizontal well was altered to achieve the 10-day revenue. At some

permeability, a single vertical fracture (in a vertical well) was sufficient to deliver the 10-day revenue. For yet-even higher

permeabilities, we still used the single vertical fracture completion but altered the target (maximum) gas flow rate to achieve

the 10-day revenue. The number of fractures and well constraints for each well model are given in Tables 4 - 7.

All the well models were simulated for ten years production under pressure depletion.

Results & Discussion

Gas Condensate, Higher-GOR fluid model. Simulation results for this fluid system are given in Figs 7 - 12. Fig. 7 shows

producing oil-gas ratio and solution oil-gas ratio (initial OGR=150 STB/MMscf) for the gas condensate fluid (initial dewpoint

pressure equal to initial reservoir pressure of 4,400 psia). For the ultra-tight cases, the producing oil-gas ratio stays near

constant, more-or-less independent of the rock permeabilities. This behavior is reported and discussed by Whitson and

Sunjerga (2012). For higher-permeability (k > 10 md) cases, the producing oil-gas ratio closely follows the solution oil-gas

ratio curve, as expected for conventional gas condensate reservoirs. For intermediate permeabilities ranging from 0.05 to 3 md,

a large variation in producing oil-gas ratio is observed.

Fig. 8 shows revenue in a 10-year production period. All the simulation cases show that a cumulative revenue of 0.5 million

USD is achieved in the first 10 days. For ultra-tight cases, the 10-year revenue reaches 10 million USD. For the higher-

permeability cases the 10-year revenue reaches 100 million USD, this is mainly due to a more efficient drainage of the entire

well spacing within the 10 years considered.

Figs. 9 - 12 show gas production rate, oil production rate, cumulative gas and oil production, respectively. The gas production

rates are higher in the first few days for the ultra-tight cases than for the higher-permeability cases. This is because the

SPE 167788 5

producing oil-gas ratio for the ultra-tight wells is much lower than solution oil-gas ratio (at current average reservoir pressure)

and the well has to be stimulated to achieve a higher gas rate to meet the 10-day revenue target. For higher-permeability cases,

the gas production rates stay constant and oil production rates also remain high because the producing oil-gas ratio follows the

solution oil-gas ratio (conventional gas condensate performance). This also is reflected in the cumulative production plots.

Near-Critical Oil, Higher-GOR fluid model. Fig. 13 shows producing OGR for all the simulated cases with different

permeabilities and solution OGR (initial OGR = 240 STB/MMscf) for the near-critical oil (initial bubblepoint pressure equal

to initial reservoir pressure of 4,400 psia). For the higher-permeability wells (k > 10 md), the producing oil-gas ratio curves

collapse together showing a clear characteristic of depletion performance of conventional reservoirs. For the ultra-tight (k <

0.002 md) cases, the producing oil-gas ratio stays at a low level and more-or-less constant, approximately the solution OGR

evaluated at flowing BHP. Similar as the gas condensate cases, a large variation in producing oil-gas ratio also exists for

intermediate-permeability cases.

Fig. 14 shows revenue in a 10-year production period for the near-critical oil cases. It can be observed that ultra-tight (k <

0.002 md) cases assemble as one group (lines in red) and conventional (k > 3 md) permeability cases assemble as another

group (lines in black). Cumulative revenue from 10-year production of higher-permeability cases is found to be 10 times

higher than that of the ultra-tight cases (due to more efficient depletion of the one-section spacing during the 10 years

considered).

Figs. 15 - 18 show gas and oil production rates and cumulative production performance of the simulation cases. Main

characteristics for the near-critical oil cases are primarily the same as for the gas condensate cases.

Highly-Undersaturated Gas Condensate, Higher-GOR fluid model. 10-year production revenue for the highly-undersaturated

gas condensate is shown in Fig. 19. Three distinct groups may be identified: one for the ultra-tight cases (lines in red), one for

conventional cases (lines in black), and one for “transitional” performance (lines in green), where a large variation in revenue

is observed for this group of cases.

Figs. 20 - 23 show production performance of gas rate, oil rate, cumulative gas produced, and cumulative oil produced,

respectively. For this highly-undersaturated gas condensate, a production plateau is sustained for permeability as low as 0.1

md. Oscillation in production rates is observed in simulations of the ultra-tight cases. This is believed to be caused by

insufficient degree of griddling in the vicinity of the fracture for the ultra-tight permeability cases (Whitson and Sunjerga,

2012 & Juell and Whitson, 2013).

Moderate-GOR fluid model. The producing GOR performance is shown in Fig. 24. The open circles on this figure represent

the producing GOR after 10-year pressure depletion. For permeabilities higher than ~ 0.01 md, the producing GOR remains

practically constant at the initial value of 1,000 scf/STB. For permeabilities lower than ~ 0.005 md, the producing GOR tends

to increase with decreasing permeability. This is because pressure in the near fracture area has fallen below the initial

bubblepoint pressure of the reservoir oil.

Fig. 25 shows cumulative revenue from 10-year production. All cases reached 1.0 million USD after the first 10 days of

production. The revenues during the first 10 days are the same for all cases because the well was producing at the same gas

and oil production rates in this period. The 10-year cumulative revenues range from ~ 25 million USD for ultra-tight (370 nd)

to ~ 370 million USD for permeability of 10 md; clearly the one-section spacing is being drained more efficiently during the

ten year period considered for higher permeabilities.

Figs. 26 - 29 show production performance of gas rate, oil rate, cumulative gas production, and cumulative oil production,

respectively. All the cases sustain a gas plateau rate4 for more than 10 days. Gas and oil plateau periods progressively increase

as the reservoir permeability increases. For the highest permeability case of k = 10 md, gas production rate always stayed at

the plateau level throughout the 10-year simulation.

Conclusions The depletion performance of liquid-rich (oil and gas condensate) reservoirs is well documented for “conventional” reservoirs,

with the main characteristic being that both producing GOR and recovery factors (of gas and oil) correlate strongly with

average reservoir pressure. Conventional depletion performance is more-or-less independent of rock permeability, well

completion, and flowing bottomhole pressure. The fluid properties and relative permeabilities control depletion performance

of conventional reservoirs – as traditionally quantified by conventional material balance methods.

4 A more-natural well control using oil rate targets could have been used for the wells producing with the Moderate-GOR fluid system, but performance

characteristics would not have been different than presented here using gas well rate targets.

6 SPE 167788

The depletion performance of liquid-rich reservoirs with ultra-low permeability – e.g. shale reservoirs – has been shown

previously (Whitson and Sunjerga, 2012) to deviate considerably from conventional performance. The difference is mainly

that oil recovery and producing GOR are strong functions of flowing BHP and degree of undersaturation. Also, average

reservoir pressure and recovery factors cannot be used (in a meaningful way) to describe ultra-tight liquid-rich depletion

performance.

This paper, based on numerical reservoir simulation of finely-gridded, vertically-fractured well models, provides the following

observations and conclusions:

1. A means to identify whether depletion performance follows conventional behavior – or not – has been devised to

classify ultra-low and low-permeability liquid-rich reservoirs. Three categories of depletion behavior are clearly

identified – ultra-tight, transitional (from ultra-tight to conventional), and conventional.

2. Four fluid systems with similar reservoir properties (porosity, thickness, relative permeability) have been studied to

identify permeability regions where ultra-tight, transitional, and conventional depletion performance exist. These

example reservoir systems show that conventional performance is always found at permeabilities greater than ~ 1.0

md.

For a highly-undersaturated gas condensate system (e.g. as found in much of the Eagle Ford shale), we show that

conventional depletion performance exists at permeabilities greater than ~ 0.05 md, mainly because single-phase flow

behavior exists everywhere except locally near the fractures. In this special case, the producing OGR (liquid yield)

will remain constant for very long periods of time, even with low flowing BHPs.

For a highly-undersaturated, moderate-GOR oil system (e.g. Bakken-like oil), we find that producing GOR remains

constant for long periods of time (e.g. 10 years), close to initial solution GOR, when permeability is in the range of

0.2 – 1.0 md. In this case, Fetkovich generalized (transient & pseudosteady state) decline curve analysis should be

applicable for production forecasting both oil and gas rates.

3. Conventional depletion performance modeling methods, including material balance and decline curve analysis, are

not generally recommended for ultra-tight and transitional reservoirs, particularly if the fluid system is near-saturated.

The only way to obtain a reliable production forecast of ultra-tight and transitional oil and gas depletion performance

is to use a history-matched, finely-gridded numerical well model.

The exception to this conclusion would be for highly-undersaturated fluid systems that show more-or-less constant

producing GORs for longer periods of time, even with flowing BHPs far below the saturation pressure.

Nomenclature Ωa = EOS constant

Ωb = EOS constant

k = rock permeability, md or nd

kf = fracture permeability, md

Lf = fracture total length, ft

xf = fracture half length, ft

ye = distance between the wellbore and reservoir boundary y-dir, ft

xe = external reservoir boundary x-dir length, ft

M = molecular weight

M30+ = molecular weight of C30+ components

Nf = number of fractures

p = pressure, psia.

pb = bubblepoint pressure, psia.

Pd = dewpoint pressure, psia.

pR = reservoir pressure, psia.

pRi = initial reservoir pressure, psia.

pwf = flowing bottomhole pressure (FBHP), psia.

qg = surface gas rate, Mscf/D

qo = surface oil rate, STB/D

rp = producing oil-gas ratio or liquid yield, STB/MMscf.

rsi = initial solution oil-gas ratio, STB/MMscf.

SPE 167788 7

Rp = producing gas-oil ratio (GOR), scf/STB.

Rs = solution gas-oil ratio (GOR), scf/STB.

Rsi = initial solution gas-oil ratio, scf/STB.

s = dimensionless volume shift parameter in EOS ( = c/b)

Swc = connate water saturation.

Sgi = initial gas saturation.

Soi = initial oil saturation.

t = time, days

Tc = critical temperature, oR

TR = reservoir temperature, oF

Tsp = separator temperature, oF

Zc = component critical Z-factor used in Lorenz-Bray-Clark viscosity calculations

zi = composition used to create black-oil tables, mol-%.

μg = gas viscosity, cp

μo = oil viscosity, cp

ω = acentric factor

References

Fetkovich, M. J.: "Decline Curve Analysis Using Type Curves," JPT (June 1980) 1065-1077.

Coats Engineering 2013. www.coatsenginering.com (SENSOR).

Whitson, C.H. and Sunjerga, S. 2012. PVT in Liquid-Rich Shale Reservoirs. Paper SPE 155499 presented at the SPE Annual

Technical Conference and Exhibition, San Antonio, Texas, 8-10 October. http://dx.doi.org/10.2118/155499-MS.

Juell, A.O. and Whitson,C,H. 2013. Optimized Well Modeling of Liquid-Rich Shale Reservoirs. Paper SPE 166380 present at

the SPE Annual Technical Conference and Exhibition held in New Orleans, Louisiana, USA, 30 September–2 October 2013.

http://dx.doi.org/10.2118/166380-MS.

Whitson, C.H. and Brulé, M.R. 2000. Phase Behavior, Monograph Series, Society of Petroleum Engineers.

http://dx.doi.org/10.2118/155499-MS

8 SPE 167788

TABLE 1 – REQUIRED INFORMATION FOR SINGLE-WELL LRS RESERVOIR SIMULATOR MODEL.

Reservoir Data

Depth to formation top 10,000 ft

Reservoir thickness (Higher-GOR Cases) 200 ft

Reservoir thickness (Moderate-GOR Cases) 100 ft

Initial reservoir pressure (Higher-GOR Cases) 4,40010,000 psia

Initial reservoir pressure (Moderate-GOR Cases) 6,500 psia

Reservoir temperature (Higher-GOR Cases) 250 oF

Reservoir temperature (Moderate-GOR Cases) 240 oF

Rock porosity 0.059

Rock permeability variable (10 nd to 100 md)

Relative permability saturation exponents 2.5

Well Data

Horizontal length 5,280 ft

Well spacing 640 acre

Number of fractures variable (20 to 1)

Fracture half length 200 ft

Moderate-GOR PVT Model

Separator pressure 100 psia

Separator temperature 150 F

see other tables for EOS model

see Whitson-Sunjerga reference for Higher-GOR PVT model

SPE 167788 9

TABLE 2 – SRK EOS and LBC VISCOSITY MODEL FOR STUDY (Moderate-GOR oil).

TABLE 3 – ECONOMIC CONSTRIANT AND CALCULATION ASSUMPTION

Molecular Cri tica l Cri tica l Acentric Volume Cri tica l N2 CO2 H2S Molar

Weight Temperature Pressure Factor Shi ft Z-factor BIPs BIPs BIPs Compos ition

Component M Tc pc w s Zc kN2-i kCO2-i kH2S-i zi

oR psia mol-%

N2 28.01 227.16 492.84 0.037 -0.0009 0.2918 2.864

CO2 44.01 547.42 1069.50 0.225 0.2175 0.2743 0 0.306

H2S 34.08 672.12 1300.00 0.090 0.1015 0.2829 0.12 0.12 0.000

C1 16.04 343.01 667.03 0.011 -0.0025 0.2862 0.02 0.12 0.08 28.540

C2 30.07 549.58 706.62 0.099 0.0589 0.2792 0.06 0.15 0.07 9.370

C3 44.10 665.69 616.12 0.152 0.0908 0.2763 0.08 0.15 0.07 8.375

I-C4 58.12 734.13 527.94 0.186 0.1095 0.2820 0.08 0.15 0.06 1.232

N-C4 58.12 765.22 550.56 0.200 0.1103 0.2739 0.08 0.15 0.06 5.079

I-C5 72.15 828.70 490.37 0.229 0.0977 0.2723 0.08 0.15 0.06 1.585

N-C5 72.15 845.46 488.78 0.2520 0.1195 0.2684 0.08 0.15 0.06 2.810

C6 84.07 926.08 494.89 0.2349 0.1103 0.3050 0.08 0.15 0.05 3.487

C7 100.09 995.61 452.79 0.2935 0.0988 0.3098 0.08 0.1 0.03 5.648

C8 111.25 1036.10 424.21 0.3408 0.1036 0.3081 0.08 0.1 0.03 5.185

C9 125.44 1082.30 391.58 0.4010 0.1116 0.3042 0.08 0.1 0.03 3.280

C10 139.49 1123.40 363.37 0.4604 0.1205 0.3010 0.08 0.1 0.03 3.027

C11 153.51 1160.50 338.84 0.5196 0.1296 0.2982 0.08 0.1 0.03 2.354

C12 167.52 1194.40 317.40 0.5785 0.1384 0.2958 0.08 0.1 0.03 2.010

C13 181.51 1225.50 298.57 0.6373 0.1468 0.2938 0.08 0.1 0.03 1.826

C14 195.50 1254.30 281.96 0.6961 0.1546 0.2921 0.08 0.1 0.03 1.510

C15 209.47 1280.90 267.24 0.7549 0.1617 0.2907 0.08 0.1 0.03 1.326

C16 223.45 1305.70 254.14 0.8137 0.1680 0.2896 0.08 0.1 0.03 1.128

C17 237.42 1329.00 242.44 0.8726 0.1736 0.2889 0.08 0.1 0.03 0.978

C18 251.38 1350.70 231.94 0.9316 0.1784 0.2883 0.08 0.1 0.03 0.891

C19 265.35 1371.20 222.50 0.9907 0.1825 0.2881 0.08 0.1 0.03 0.816

C20 279.31 1390.60 213.97 1.0499 0.1859 0.2881 0.08 0.1 0.03 0.664

C21 293.27 1408.90 206.25 1.1093 0.1886 0.2884 0.08 0.1 0.03 0.569

C22 307.23 1426.20 199.23 1.1688 0.1907 0.2889 0.08 0.1 0.03 0.517

C23 321.18 1442.70 192.84 1.2286 0.1922 0.2896 0.08 0.1 0.03 0.460

C24 335.14 1458.50 187.00 1.2885 0.1932 0.2904 0.08 0.1 0.03 0.416

C25 349.09 1473.40 181.65 1.3487 0.1937 0.2915 0.08 0.1 0.03 0.378

C26 363.05 1487.80 176.73 1.4092 0.1936 0.2928 0.08 0.1 0.03 0.307

C27 377.00 1501.50 172.20 1.4699 0.1932 0.2942 0.08 0.1 0.03 0.298

C28 390.96 1514.70 168.03 1.5310 0.1923 0.2957 0.08 0.1 0.03 0.291

C29 404.91 1527.40 164.16 1.5925 0.1910 0.2975 0.08 0.1 0.03 0.239

C30+ 548.58 1634.80 136.80 2.2561 0.1621 0.3216 0.08 0.1 0.03 2.236

Note: WA = 0.42748 and WB=0.0866403 used in simulator.

Higher-GOR Cases Moderate-GOR Cases

Revenue in the First 10 days, million USD 0.5 1

Oil Price, USD/STB 100 100

Gas Price, USD/Mscf 4 4

Note: Revenues are not discounted.

10 SPE 167788

TABLE 4 – WELL CONSTRAINTS FOR GAS

CONDENSATE FLUID CASES

(pRi = 4,400 psia, pd = 4,400 psia)

TABLE 5 – WELL CONSTRAINTS FOR NEAR-

CRITICAL OIL FLUID CASES

(pRi = 4,400 psia, pb = 4,400 psia)

TABLE 6 – WELL CONSTRAINTS FOR HIGHLY-

UNDERSATURATED GAS CONDENSATE FLUID

CASES (pRi = 10,000 psia, pd = 4,400 psia)

TABLE 7 – WELL CONSTRAINTS FOR MODERATE-

GOR FLUIDS CASES

(pRi = 6,500 psia, pb = 3,150 psia)

Permeability Nf Max Gas Rate

md Mscf

(70 nd) 0.0000695 20 10,000

(285 nd) 0.000285 10 10,000

0.00108 5 10,000

0.025 1 10,000

0.05 1 6,100

0.1 1 4,700

0.3 1 3,550

1 1 2,980

3 1 2,740

10 1 2,660

20 1 2,630

100 1 2,630


md Mscf

(141 nd) 0.000141 20 10,000

(547 nd) 0.000547 10 10,000

0.00218 5 10,000

0.0505 1 10,000

0.1 1 4,860

0.3 1 2,480

1 1 1,680

3 1 1,714

10 1 1,780

20 1 1,784

100 1 1,784


md Mscf

(11 nd) 0.0000111 20 10,000

(44 nd) 0.0000438 10 10,000

(166 nd) 0.000166 5 10,000

(970 nd) 0.00097 2 10,000

0.00352 1 10,000

0.0091 1 10,000

0.01 1 10,000

0.015 1 10,000

0.02 1 10,000

0.03 1 10,000

0.1 1 10,000

1 1 10,000

10 1 10,000

100 1 10,000


md Mscf

(370 nd) 0.00037 20 1,000

0.00147 10 1,000

0.0056 5 1,000

0.0085 4 1,000

0.1 1 1,000

0.2 1 964

0.5 1 964

1 1 964

10 1 964

SPE 167788 11

Fig. 1 – Ratio of one-year revenue to the 10-day revenue. Three categories can be identified: a near constant value of ~ 7 for

ultra-tight, a value around 36.5 for conventional, and a gradual transition for intermediate permeabilities.

Fig. 2 – Finely-gridded well model for a half of a hydraulic fracture of a horizontal well (line in red indicates half of the

hydraulic fracture).

0

10

20

30

40

50

0.00001 0.0001 0.001 0.01 0.1 1 10 100

Re

ve

nu

e R

atio

, (1

ye

ar)

/ (

10

da

ys)

Reservoir Permeability, md

Gas Condensate, Pi = 10,000 psia

Gas Condensate, Pi = 4400 psia

Near Critical Oil, Pi = 4400 psia

Moderate-GOR Oil, Pi = 6500 psia

Conventional (higher-k) Performance

Ultra-low PermeablityPerformance

10 100 1000(nd)

ye=2640ft

xf=200 ft

xe=5280 ft

Wellbore

12 SPE 167788

Fig. 3 – Solution oil-gas ratio versus pressure for the Higher-GOR fluid systems.

Fig. 4 – Saturated viscosity versus pressure for the Higher-GOR fluid systems.

10

100

1000

10000

100000

0 1000 2000 3000 4000 5000

Solu

tion O

il-G

as R

atio,

r sor

1/R

s,

ST

B/M

Mscf

Pressure, psia

Oil Phase

Gas Phase

0.01

0.1

1

0 1000 2000 3000 4000 5000

Sa

tura

ted

Vis

co

sity,

cp

Pressure, psia

Oil Phase

Gas Phase

SPE 167788 13

Fig. 5 – Solution oil-gas ratio versus pressure for the Moderate-GOR oil.

Fig. 6 – Saturated viscosity versus pressure for the Moderate-GOR oil.

1

10

100

1000

10000

100000

0 1000 2000 3000 4000 5000 6000 7000 8000

So

lutio

n O

il-G

as R

atio

, r s

or

1/R

s,

ST

B/M

Mscf

Pressure, psia

Oil Phase

Gas Phase

0.01

0.1

1

0 1000 2000 3000 4000 5000 6000 7000 8000

Sa

tura

ted

Vis

co

sity,

cp

Pressure, psia

Oil Phase

Gas Phase

14 SPE 167788

Fig. 7 – Producing OGR and solution OGR (initial OGR = 150 STB/MMscf) for the gas condensate fluid (pRi = pd = 4,400

psia). Black: conventional reservoir; Green: transition from conventional to ultra-tight; Red: ultra-tight reservoir.

Fig. 8 – Cumulative revenue versus time for gas condensate fluid (pRi = pd = 4,400 psia). Black: conventional reservoir; Green:

transition from conventional to ultra-tight; Red: ultra-tight reservoir.

0

50

100

150

200

3000 3250 3500 3750 4000 4250 4500

Pro

ducin

g O

GR

, S

TB

/MM

scf

Average Reservoir Pressure, psia

k = 100 mdk = 20 mdk = 10 mdk = 3 mdk = 1 mdk = 0.3 mdk = 0.1 mdk = 0.05 mdk = 0.025 mdk = 0.00108 mdk = 0.000285 md (285 nd)k = 0.0000692 md (69 nd)rs

rs

Conventional performance

Ultra-low-k performance

0.001

0.01

0.1

1

10

100

0.1 1 10 100 1000 10000

Re

ve

nu

e, M

illio

n U

SD

Time, days

k = 100 md

k = 20 md

k = 10 md

k = 3 md

k = 1 md

k = 0.3 md

k = 0.1 md

k = 0.05 md

k = 0.025 md

k = 0.00108 md

k = 0.000285 md (285 nd)

k = 0.0000695 md (69 nd)

SPE 167788 15

Fig. 9 – Procuding gas rate versus time for gas condensate fluid (pRi = pd = 4,400 psia). Black: conventional reservoir; Green:


Fig. 10 – Producing oil rate versus time for gas condensate fluid (pRi = pd = 4,400 psia). Black: conventional reservoir; Green:


100

1000

10000

0.1 1 10 100 1000 10000

Ga

s R

ate

, M

scf/

D

Time, days

k = 100 md

k = 20 md

k = 10 md

k = 3 md

k = 1 md

k = 0.3 md

k = 0.1 md

k = 0.05 md

k = 0.025 md

k = 0.00108 md

k = 0.000285 md (285 nd)

k = 0.0000695 md (69 nd)

10

100

1000

0.1 1 10 100 1000 10000

Oil R

ate

, S

TB

/D

Time, days

k = 100 md

k = 20 md

k = 10 md

k = 3 md

k = 1 md

k = 0.3 md

k = 0.1 md

k = 0.05 md

k = 0.025 md

k = 0.00108 md

k = 0.000285 md (285 nd)

k = 0.0000695 md (69 nd)

16 SPE 167788

Fig. 11 – Cumulative gas production versus time for gas condensate fluid (pRi = pd = 4,400 psia). Black: conventional

reservoir; Green: transition from conventional to ultra-tight; Red: ultra-tight reservoir.

Fig. 12 – Cumulative oil production versus time for gas condensate fluid (pRi = pd = 4,400 psia). Black: conventional reservoir;

Green: transition from conventional to ultra-tight; Red: ultra-tight reservoir.

1

10

100

1000

10000

0.1 1 10 100 1000 10000

Cu

mu

lative

Ga

s P

rod

uce

d, M

Mscf

Time, days

k = 100 md

k = 20 md

k = 10 md

k = 3 md

k = 1 md

k = 0.3 md

k = 0.1 md

k = 0.05 md

k = 0.025 md

k = 0.00108 md

k = 0.000285 md (285 nd)

k = 0.0000695 md (69 nd)

0.1

1

10

100

1000

0.1 1 10 100 1000 10000

Cu

mu

lative

Oil P

rod

uce

d, M

ST

B

Time, days

k = 100 md

k = 20 md

k = 10 md

k = 3 md

k = 1 md

k = 0.3 md

k = 0.1 md

k = 0.05 md

k = 0.025 md

k = 0.00108 md

k = 0.000285 md (285 nd)

k = 0.0000695 md (69 nd)

SPE 167788 17

Fig. 13 – Producing OGR and solution OGR (initial OGR = 240 STB/MMscf) for the near-critical fluid (pRi = pd = 4,400 psia).

Black: conventional reservoir; Green: transition from conventional to ultra-tight; Red: ultra-tight reservoir

.

Fig. 14 – Cumulative revenue versus time for near-critical oil fluid cases (pRi = pd = 4,400 psia). Black: conventional reservoir;


0

50

100

150

200

250

300

340036003800400042004400

Pro

du

cin

g O

GR

, S

TB

/MM

scf


k = 100 mdk = 20 mdk = 10 mdk = 3 mdk = 1 mdk = 0.3 mdk = 0.1 mdk = 0.051 mdk = 0.00218 mdk = 0.000547 md (547 nd)k = 0.000141 md (141 nd)rs

rs

Conventional performance

Ultra-low-k performance

0.001

0.01

0.1

1

10

100

0.1 1 10 100 1000 10000

Re

ve

nu

e,

mill

ion

US

D

Time, days

k = 100 md

k = 20 md

k = 10 md

k = 3 md

k = 1 md

k = 0.3 md

k = 0.1 md

k = 0.051 md

k = 0.00218 md

k = 0.000547 md (547 nd)

k = 0.000141 md (141 nd)

18 SPE 167788

Fig. 15 – Gas production rate versus time for near-critical oil fluid cases (pRi = pd = 4,400 psia). Black: conventional reservoir;


Fig. 16 – Oil production rate versus time for near-critical oil fluid cases (pRi = pd = 4,400 psia). Black: conventional reservoir;


100

1000

10000

100000

0.1 1 10 100 1000 10000

Ga

s R

ate

, M

scf/

D

Time, days

k = 100 md

k = 20 md

k = 10 md

k = 3 md

k = 1 md

k = 0.3 md

k = 0.1 md

k = 0.051 md

k = 0.00218 md

k = 0.000547 md (547 nd)

k = 0.000141 md (141 nd)

1

10

100

1000

10000

0.1 1 10 100 1000 10000

Oil R

ate

, S

TB

/D

Time, days

k = 100 md

k = 20 md

k = 10 md

k = 3 md

k = 1 md

k = 0.3 md

k = 0.1 md

k = 0.051 md

k = 0.00218 md

k = 0.000547 md (547 nd)

k = 0.000141 md (141 nd)

SPE 167788 19

Fig. 17 – Cumulative gas production versus time for near-critical fluid (pRi = pd = 4,400 psia). Black: conventional reservoir;


Fig. 18 – Cumulative oil production versus time for near-critical fluid (pRi = pd = 4,400 psia). Black: conventional reservoir;


0.1

1

10

100

1000

10000

0.1 1 10 100 1000 10000

Cu

mu

lative

Ga

s P

rod

uce

d, M

Mscf

Time, days

k = 100 md

k = 20 md

k = 10 md

k = 3 md

k = 1 md

k = 0.3 md

k = 0.1 md

k = 0.051 md

k = 0.00218 md

k = 0.000547 md (547 nd)

k = 0.000141 md (141 nd)

0.01

0.1

1

10

100

1000

10000

0.1 1 10 100 1000 10000

Cu

mu

lative

Oil P

rod

uce

d, M

ST

B

Time, days

k = 100 mdk = 20 mdk = 10 mdk = 3 mdk = 1 mdk = 0.3 mdk = 0.1 mdk = 0.051 mdk = 0.00218 mdk = 0.000547 md (547 nd)k = 0.000141 md (141 nd)

20 SPE 167788

Fig. 19 – Cumulative revenue versus time for highly undersaturated gas condensate cases (pRi = 10,000 psia, pd = 4,400 psia).

Black: conventional reservoir; Green: transition from conventional to ultra-tight; Red: ultra-tight reservoir.

Fig. 20 – Gas production rate versus time for highly undersaturated gas condensate fluid cases (pRi = 10,000 psia, pd = 4,400


0.001

0.01

0.1

1

10

100

0.1 1 10 100 1000 10000

Re

ve

nu

e, m

illio

n U

SD

Time, days

k = 100 mdk = 10 mdk = 1 mdk = 0.1 mdk = 0.03 mdk = 0.02 mdk = 0.015 mdk = 0.01 mdk = 0.0091 mdk = 0.00352 mdk = 0.00097 mdk = 0.000438 md (438 nd)k = 0.000166 md (166 nd)k = 0.0000111 md (11 nd)

100

1000

10000

0.1 1 10 100 1000 10000

Ga

s R

ate

, M

scf/

D

Time, days

k = 100 md

k = 10 md

k = 1 md

k = 0.1 md

k = 0.03 md

k = 0.02 md

k = 0.015 md

k = 0.01 md

k = 0.0091 md

k = 0.00352 md

k = 0.00097 md (970 nd)

k = 0.000438 md (438 nd)

k = 0.000166 md (166 nd)

k = 0.0000111 md (11 nd)

SPE 167788 21

Fig. 21 – Oil production rate versus time for highly undersaturated gas condensate fluid cases (pRi = 10,000 psia, pd = 4,400


Fig. 22 – Cumulative gas production versus time for highly undersaturated gas condensate fluid cases (pRi = 10,000 psia, pd =

4,400 psia). Black: conventional reservoir; Green: transition from conventional to ultra-tight; Red: ultra-tight reservoir.

10

100

1000

10000

0.1 1 10 100 1000 10000

Oil R

ate

, S

TB

/D

Time, days

k = 100 md k = 10 md

k = 1 md k = 0.1 md

k = 0.03 md k = 0.02 md

k = 0.015 md k = 0.01 md

k = 0.0091 md k = 0.00352 md

k = 0.00097 md (970 nd) k = 0.000438 md (438 nd)

k = 0.000166 md (166 nd) k = 0.0000111 md (11 nd)

0.1

1

10

100

1000

10000

0.1 1 10 100 1000 10000

Cum

mula

tive G

as P

roduced,

MM

scf

Time, days

k = 100 md

k = 10 md

k = 1 md

k = 0.1 md

k = 0.03 md

k = 0.02 md

k = 0.015 md

k = 0.01 md

k = 0.0091 md

k = 0.00352 md

k = 0.00097 md (970 nd)

k = 0.000438 md (438 nd)

k = 0.000166 md (166 nd)

k = 0.0000111 md (11 nd)

22 SPE 167788

Fig. 23 – Cumulative oil production versus time for highly undersaturated gas condensate fluid cases (pRi = 10,000 psia, pd =

4,400 psia). Black: conventional reservoir; Green: transition from conventional to ultra-tight; Red: ultra-tight reservoir.

Fig. 24 – Producing GOR versus average reservoir pressure for the Moderate-GOR oil cases (pRi = 6,500 psia, pb = 3,150 psia).

0.01

0.1

1

10

100

1000

0.1 1 10 100 1000 10000

Cum

mula

tive O

il P

roduced,

MS

TB

Time, days

k = 100 mdk = 10 mdk = 1 mdk = 0.1 mdk = 0.03 mdk = 0.02 mdk = 0.015 mdk = 0.01 mdk = 0.0091 mdk = 0.00352 mdk = 0.00097 md (970 nd)k = 0.000438 md (438 nd)k = 0.000166 md (166 nd)k = 0.0000111 md (11 nd)

0

1000

2000

2000 3000 4000 5000 6000 7000

Pro

ducin

g G

OR

, scf/S

TB


k = 10 md

k = 1 md

k = 0.5 md

k = 0.2 md

k = 0.1 md

k = 0.0085 md

k = 0.0056 md

k = 0.00147 md

k = 0.00037 md (370 nd)

SPE 167788 23

Fig. 25 – Cumulative revernue versus time for moderate-GOR oil cases (pRi = 6,500 psia, pb = 3,150 psia). Black: conventional

reservoir; Green: transition reservoir from conventional to ultra-tight reservoir; Red: ultra-tight reservoir.

Fig. 26 – Gas production rate versus time for moderate-GOR oil cases (pRi = 6,500 psia, pb = 3,150 psia). Black: conventional


0.1

1

10

100

1000

1 10 100 1000 10000

Re

ve

nu

e, m

illio

n U

SD

Time, days

k = 10 md

k = 1 md

k = 0.5 md

k = 0.2 md

k = 0.1 md

k = 0.0085 md

k = 0.0056 md

k = 0.00147 md

k = 0.00037 md (370 nd)

10

100

1000

0.1 1 10 100 1000 10000

Ga

s R

ate

, M

scf/

D

Time, days

k = 10 md

k = 1 md

k = 0.5 md

k = 0.2 md

k = 0.1 md

k = 0.0085 md

k = 0.0056 md

k = 0.00147 md

k = 0.00037 md (370 nd)

24 SPE 167788

Fig. 27– Oil production rate versus time for moderate-GOR oil cases (pRi = 6,500 psia, pb = 3,150 psia). Black: conventional


Fig. 28 – Cumulative gas production versus time for moderate-GOR oil cases (pRi = 6,500 psia, pb = 3,150 psia). Black:

conventional reservoir; Green: transition reservoir from conventional to ultra-tight reservoir; Red: ultra-tight reservoir.

10

100

1000

10000

0.1 1 10 100 1000 10000

Oil R

ate

, S

TB

/D

Time, days

k = 10 md

k = 1 md

k = 0.5 md

k = 0.2 md

k = 0.1 md

k = 0.0085 md

k = 0.0056 md

k = 0.00147 md

k = 0.00037 md (370 nd)

1

10

100

1000

10000

1 10 100 1000 10000

Cu

mu

lative

Ga

s P

rod

uce

d, M

Mscf

Time, days

k = 10 md

k = 1 md

k = 0.5 md

k = 0.2 md

k = 0.1 md

k = 0.0085 md

k = 0.0056 md

k = 0.00147 md

k = 0.00037 md (370 nd)

SPE 167788 25

Fig. 29 – Cumulative oil production versus time for moderate-GOR oil cases (pRi = 6,500 psia, pb = 3,150 psia). Black:

conventional reservoir; Green: transition reservoir from conventional to ultra-tight reservoir; Red: ultra-tight reservoir.

1

10

100

1000

10000

1 10 100 1000 10000

Cu

mu

lative

Oil P

rod

uce

d, M

ST

B

Time, days

k = 10 md

k = 1 md

k = 0.5 md

k = 0.2 md

k = 0.1 md

k = 0.0085 md

k = 0.0056 md

k = 0.00147 md

k = 0.00037 md (370 nd)

liquid-rich shale versus conventional depletion performance

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