Copyright 2007, Society of Petroleum Engineers This paper was prepared for presentation at the 2007 SPE Latin American and Caribbean Petroleum Engineering Conference held in Buenos Aires, Argentina, 15–18 April 2007. 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, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes 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 where and by whom the paper was presented. Write Librarian, SPE, P.O. Box 833836, Richardson, Texas 75083-3836 U.S.A., fax 01-972-952-9435.

Abstract

This paper describes a new Downhole Fluid Analysis technology (DFA) being implemented in Latin America for improved reservoir management. DFA is a unique process in fluid characterization for improving fluid sampling, reservoir compartmentalization evaluation and support flow assurance analysis. It combines known and new fluid identification sensors, which allow real time monitoring of a wide range of parameters as GOR, fluorescence, apparent density, fluid composition (CH4, C2, C3-C5, C6+, CO2), free gas and liquid phases detection, saturation pressure, as well WBM & OBM filtrate differentiation and pH, which is key for real time contamination monitoring at the well site with the objective of representative sampling and reservoir compartmentalization analysis. This process is not limited to light fluid evaluation or sandstones.

The combination of DFA Fluid Mapping with

pressure measurements has shown to be very effective for compartmentalization characterization. The ability of thin barriers to hold off large depletion pressures has been established, as the gradual variation of hydrocarbon quality in biodegraded oils. In addition, heavy oils can show large compositional variation due to variations in source rock charging

but without fluid mixing [1]. Using this method we present field DFA data

acquisitions and integrate into numerical simulation modeling to conceptually evaluate the impact of fluid composition / properties gradation and compartmentalization in the productivity of some Latin America reservoirs. Introduction

Exploration wells provide a narrow window of opportunity for collecting hydrocarbon samples to make development decisions; therefore, obtaining high-quality samples and performing an adequate fluid scanning along the hydrocarbon column is imperative whether the prospect is in deep water or on the continental shelf. That is, one can obtain a continuous downhole fluid log. This log records (vertical) composition variation along with some indications of compartments or connectivity.

Testing well production is a common way to

obtain fluid samples, but usually does not allow a detailed areal or vertical fluid scanning for compartmentalization, gradual variation of hydrocarbon quality or density inversion analysis, and is not always feasible for economic or environmental reasons. Downhole samples define fluid properties that are used throughout field development.

Downhole Fluid Analysis technology (DFA) is a

concept, rather than a specific tool. Currently, DFA relies on near-infrared spectroscopy (NIR) and new novel approaches. The details of NIR application for DFA have been described elsewhere [2, 3].

SPE 108097

New Downhole Fluid Analysis (DFA) Technologies Supporting Improved Reservoir Management Jesús A. Cañas, Evie Freitas, A. Ballard Andrews, Oliver C. Mullins, Santiago E. Colacelli, SPE, Schlumberger

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Figure 1 shows the absorption spectra (optical density (OD) vs. wavelength) of methane, a dead crude oil and a live crude oil. Methane and other alkane absorption features are readily distinguishable enabling some compositional information to be obtained.

Figure 1. Absorption spectra (optical density (OD) vs. wavelength) of methane, a dead crude oil and a live crude oil

Figure 2. Schematic of the MDT with three optical modules to perform downhole fluid analysis for hydrocarbons and water

Figure 1 shows the two-stretch overtone peak of different chemical groups containing the C-H oscillator. As is true for all mechanical oscillators, the oscillation or vibration frequency depends on the (reduced) mass. Consequently, CH4, -CH3 and -CH2 groups all have somewhat different frequencies allowing their resolution. As described previously, these chemical groups project into methane (C1), other hydrocarbon gases (C2-C5) and hydrocarbon liquids (C6+) [2, 3]. Other DFA measurements include index-of-refraction for gas detection [4], fluorescence for retrograde dew detection or hydrocarbon typing [5, 6], absorption spectra for H20 and CO2, GOR and CGR measurements, pH [9,10] and resistivity sensors for native water characterization, fluid density and other new evaluations for the real time analysis of hydrocarbon fluids and formation water during pump out stations with wireline formation testers.

Figure 2 shows the Modular Formation

Dynamics Tester (MDT*) that pumps fluids from the formation into the tool for analysis and sampling purposes. Two single probes are shown in the tool string; these probes attach to the borehole wall to extract fluids from the formation. Figure 2 presents three DFA modules in the string; the LFA* [7], CFA* [8] and the new optical LFA-pH* module [9,10] for water analysis. The tool configuration shown in Fig. 2 allows down hole flow analysis in OBM and WBM wells; thus, fluid and phase analyzers are positioned in both the low-pressure and high-pressure side of the pumpout.

Figure 3 shows the LFA and CFA analyzer

modules, part of the DFA process. The CFA analyzer uses a near infrared optical absorption spectrometer for real-time determination of the concentration of methane (C1), ethane-propane-butane-pentane (C2–C5), heavier hydrocarbon molecules (C6+), H2O and CO2. From this composition information, the condensate yield, or CGR (the inverse of GOR), is obtained. The CFA module also measures fluorescence emission to identify fluid type and to ensure that samples are acquired above the dewpoint for a gas condensate.

The LFA analyzer uses specific near-infrared ________________________ * Mark of Schlumberger

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wavelengths to determine the percentage of water-base filtrate in oil or of oil-base filtrate in water.

A range of visible and near-infrared wavelengths are used to determine the percentage of oil-base mud filtrate in oil. The LFA module also measures methane content and hydrocarbon content. From the ratio of these two, the gas/oil ratio (GOR) is calculated using a measurement made on oil above the bubble point. In addition to measuring contamination, the LFA module detects the presence of gas if the flowing pressure is below the bubble point.

Figure 3. Live Fluid Analyzer (LFA*) and Composition Fluid Analyzer (CFA*) modules measurements

The downhole LFA pH measurement technique injects pulses of pH-sensitive dyes storage in a Chamber, see Figures 2 and 4, into the flowline of a wireline formation tester while the formation sample is flowing. The pH-sensitive dyes change color according to the pH of the fluid in the flowline. The color change is detected at the appropriate wavelengths by an optical fluid analyzer [9, 10]. This color measurement is identical to the

familiar litmus paper utilized in schools around the world. This method has been in use for centuries and it works.

Figure 4. LFA pH* tool string [9] DFA Field Examples

Figure 5 depicts log data from the LFA and CFA run in a gas formation drilled with WBM. It shows the pressure and temperature (first track) and the optical channels measuring fluid coloration and the NIR spectrum (last track). Reduced absorption is shown as decreasing line thickness in the last displayed track, increasing pumping time runs vertical. The real time interpreted fluid density (track 2), C1, C2-C5 and C6+ composition (track 3), GOR (track 4), fluorescence (track 5), CFA water fraction (track 6), color channels (track 7), free gas detection (track 8) and LFA oil and water fraction are shown in the intermedium channels.

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Figure 6 depicts log data from the LFA and CFA run in a heavy oil formation drilled with OBM. High absorption is reflected by the line thickness of the optical channels signal in the lower displayed track at the bottom of Fig. 6. The real time interpreted composition, C1, C2-C5 and C6+, GOR, water fraction, color channels, free gas detection and oil fractions are shown in the intermedium tracks.

Figure 5. Live Fluid Analyzer (LFA*) and Composition Fluid Analyzer (CFA*) measurements in a gas station with WBM

Figure 7 presents the continuous log data from the LFA pH in a formation tester pump out station at a water bearing zone drilled with WBM. A reduction in the water pH is perceived as function of time (horizontal axis). The pH stabilized faster than temperature (not shown) and is consistent with the fluid resistivity although much more stable and less prone to flow rate noise. Lab analysis of sequential water samples taken along the pump out process confirmed that clean native water was sampled after 4.5 hours pumping instead of the usual expected 8 - 12 hrs that the field practice dictates to guarantee a clean sample in the absence of rigorous contamination controls while sampling water in WBM environment.

Figure 6. Live Fluid Analyzer (LFA*) and Composition Fluid Analyzer (CFA*) measurements in a heavy oil station with OBM

Figure 7. LFA pH* measurements in a water bearing zone drilled with WB Reservoir Fluid Scanning / Mapping Log and Reservoir Management

The overall objective is to generate a new kind of

log for reservoir management – a fluid scanning log [11, 12]. That is, using DFA, we can obtain a continuous downhole fluid log establishing the variation of the hydrocarbons along the well trajectory. Well to well variations enable mapping the fluid variations within the reservoir. It means the possibility of detecting fluid variations throughout a hydrocarbon reservoir with DFA during exploration and even development phases. In this sense, a more detailed fluid model will support the overall reservoir model.

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At the early exploration stages, extensive reservoir pressure data is very limited and with increasing usage of permanent downhole and/or surface sensing in the development phase, there is the need for on-time action to better design and maximize the benefits of these surveillance systems. In this sense, DFA Fluid Scanning / Mapping processes support a more efficient way to design permanent downhole [13], surface sensing and the development phase itself. DFA Fluid Mapping Example in the evaluation of fluid composition / properties gradation and compartmentalization for effective reservoir management

This DFA field case study presents the integral

analysis of several oil reservoirs in a compartmentalized system to evaluate potential fluid composition / properties gradation. It is recently accepted by the oil industry that compartmentalization gives rise to fluid differences in the formations. Furthermore, it is common now to consider that hydrocarbons fluids are compositionally graded until proven otherwise [12, 14].

This DFA field case study was performed in fourteen wells along an extensive compartmentalized system with reservoirs containing dense / heavy oils, therefore a more robust DFA process should be implemented because: - The saturation (opacity) of the initial

spectrometer channels in the standard industry optical fluid sensors [15]; the lower track in Figure 6 presents this phenomena.

- The common presence of emulsions in WBM drilling conditions which tend to increase the optical density; masking the true fluid optical spectrum.

- Heavy oils have an optical density of greater than 1.0 at 1µ wavelength due to contribution from asphaltenes. Figure 8 presents the optical spectra for some of the studied fluids. Failing to consider these aspects in the DFA of

heavy oils will affect the oil sample contamination

and composition analysis. However, our experience shows that rigorous integration of fluorescence / reflectance detectors (part of the CFA sensors and new DFA MDT tools) with the increase in the number of optical channels on the new MDT DFA platform (spectrometer with 36 channels) and new algorithms supported by lab analysis makes possible to overcome the difficulties while evaluating heavy oils in WBM.

The DFA Fluid Scanning in the studied fourteen

wells consisted of twenty four fluid sampling stations along an extensive compartmentalized system with oil density in the range of 0.73 to 0.93 g/cc. Figure 9 shows the variation of down-hole fluid density with depth. In spite that there is a preferential trend to have heaviest ends with depth, the analysis of the data has revealed substantial variations in the LFA – CFA optical spectra, CFA density and Fluorescence throughout the studied area. Some of these variations are marked by color circles in Figure 9 and looks to be related to compartmentalization and different degree of biodegradation as implied by the following analysis of the available DFA parameters.

Figure 8. Optical spectra for some of the studied heavy oils

Figure 10 shows the variation of down-hole fluorescence with depth. In spite of the presence of at least two fluorescence gradients the majority of the readings present medium to low values for the studied heavy oils (FLDO < 0.6). This is due to the presence of asphaltenes in these oils. This is confirmed by the following facts:

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- High absorption on the first spectrometer channels found in the studied oils (Figure 6). Asphaltenes are highly absorptive in the visible even into the near-infrared, while the absorption edge (defined as the wavelength at which the optical density = 1.0) for crude oils without asphaltenes is observed to be less than 1µ wavelength [16]. Additionally, the optical absorption beyond 1µ is found to be due solely to the asphaltene fraction, not the resins.

- The medium to low fluorescence found in

the studied heavy oils (Figure 10). Asphaltenes lack much fluorescence emission because of the small electronic band gap of the aromatic systems; meaning that the energy of the absorbed photon is more likely to transfer into heat than light [16]. In addition, asphaltenes at high concentration undergo collisional quenching (reduction in fluorescence). While aromatics and resins also fluoresce, the quenching rate is more governed by the asphaltene population, so more asphaltene leads to fluorescence ‘damping’ (quenching).

- Available SARA analysis indicating the presence of asphaltenes in these crude oils.

Figure 9. Variation of down hole Fluid Density with Depth. Potential biodegradation may be the reason for increased heavy ends with depth.

Fluorescence is reduced severely in most of these oils as result of the increased asphaltene concentration, mainly in the fluids Type C, followed by the Type B oils (Figure 11). It suggests a more severe biodegradation process in oils type C.

In order to estimate the original fluorescence gradient for the studied reservoirs (none biodegradation effect), correction factors of 0.6 and 1.1 were applied to the field data in Figure 10 as per

the difference observed between the oils type B and C with A in Figure 11. This assumption proposes that the main cause for the existence of three main oil types is the asphaltene presence associated to different biodegration regimes and that the oil type A is the least affected by biodegradation. The result of this normalization is presented in Figure 12.

Figure 10. Variation of Down-hole Fluid Fluorescence with Depth. Variation in asphaltene content looks to affect most of these oils.

Figure 11. Variation of Down-hole Fluid Fluorescence with Fluid Density. A correlation can be identified for the majority of the studied oils, which may define different asphaltene content.

Figure 12. Reference Fluorescence Gradient for oils without biodegradation.

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Results in Figures 10 and 12 help as reference to evaluate the degree of oil biodegradation through the reservoirs with the integration of SARA and detailed compositional analysis. However for well placement and completion strategies the gradients identified in Figure 10 are the one to be considered for optimum reservoir management.

Finally to complement the DFA Fluid mapping

analysis in the studied reservoirs the LFA oil channel optical density (OD (8)) vs. depth analysis is presented in Figure 13. The analysis of the data has revealed a tendency to increase in the oil channel OD (8) vs. depth. This turned out to be related to the composition gradient inferred by the fluorescence gradients (Figure 10). Therefore both variables present a direct proportional trend as indicated by Figure 14 because the heavy ends dictate both and agree in the definition of at least three different types of oils in the studied reservoirs.

Figure 13. Variation of Optical Density with Depth.

The results defined by the DFA data makes that

more rigorous analysis of the fluid composition gradients and the effect of the biodegrading phenomena has been undertaken to validate the known reservoir compartmentalization in these reservoirs and the effect that this has over the fluids.

The association of this DFA information (including GOR and viscosity that has been started to be evaluated under in-situ conditions) allows that for the first time the asphaltene concentration gradient and the oil biodegrading phenomena mapping within these reservoirs can be established.

Finally DFA data is a strong reference to validate the consistency of the SARA analysis which is seriously flawed as a predictive tool because it utilizes only four pseudo components for a dead crude oil, it is based on cursory chemical properties and does not differentiate the different chemical moieties in the heavy ends [16]. SARA results by themselves are notorious for being inaccurate. However, if both DFA and SARA provide the same result, the conclusions are greatly strengthened.

This DFA fluid mapping confirming the

existence of vertical and areal compositional gradients and compartmentalization support the current reservoir management’s strategies of these reservoirs. In this sense, well placement and completion strategies are aligned to the compositional gradients identified for optimum reservoir management.

Figure 14. Variation of Fluorescence with Oil Channel Optical Density (OD (8)).

Well completions should try to focus in similar

oils types to avoid irregular fluid drainage and flow assurance problems as will be presented in the next section. DFA Fluid Mapping Example and Impact in Reservoir Management

As mentioned previously, the fluid properties and mitigating intervention methods are needed for optimal completions, facilities design and production strategies. Consequently, getting the correct answer in the first place is a necessity [11].

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A field example is presented in Figure 15, which corresponds to a 70 meters thickness virgin heavy oil reservoir affected by compositional grading, where the vertical oil column density varies from 0.9 to 0.92 g/cc and the down-hole oil viscosity changes from 90 to 180 cps from top to bottom. Therefore, it is now becoming increasingly clear that compositional grading is to be expected, mainly in viscous oils, whereas in the past compositional grading was viewed as an aberration [14]. In this reservoir it was found that the compositional grading was the result of biodegradation toward the WOC. Furthermore vertical interference tests performed with a combination of MDT* modules (probe and dual packer) in the interface of the WOC confirms the reduction in transmissibility between the oil zone and the aquifer due to the existence of very viscous ends (like tar). These heavy hydrocarbons have the ability to act as thin barriers to hold off depletion pressures and generate local compartmentalization.

A commercial reservoir simulator ECLIPSE* in

fully implicit, black oil mode is used to simulate the Horizontal / Slanted & MLT wells well completion strategies indicated in Figure 15 (right).

Rigorously calibrated near-wellbore reservoir models are used to evaluate different potential well placement and completion configurations in order to investigate commercial production rates and efficient drainage process in these heavy oil reservoirs. Figure 16 presents the expected irregular drainage with a slanted well configuration due to the reservoir compositional gradient. It is evident the difficulty in the vertical drainage, mainly at the heaviest oils levels, where the water flow from potential neighbor injectors would have a fast breakthrough. This phenomenon affects both the vertical and areal drainage. Therefore is suggested the placement of horizontal wells in top levels or multilaterals with control systems in the different branches. EOR methods are an option after a primary recovery period; intended for better injection and soaking process of the enhanced recovery fluids.

To reiterate, a rigorous approach should be constrain the geological model with the fluids model; which compound the reservoir model. This

can be accomplished only through DFA Fluid Mapping.

Figure 15. Vertical variation in a hydrocarbon column quality - biodegraded oil.

Figure 16. Slanted well irregular drainage in a viscous oil reservoir with compositional grading - biodegraded oil.

Conclusions - DFA is a process aimed to help building our reservoir models and change conventional work flows by reducing the risk associated with compositional grading and compartmentalization, which has a big impact on the petroleum industry. - Fluorescence proves to be very useful to support compositional variation analysis in conjunction with the optical absorption and can be used to map compositional gradients and detect compartmentalization. - DFA helps to understand asphaltene compositional grading. For middle to heavy density oils that tend to exhibit heavy end grading;

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biodegradation is thought to be a prime contributor here. Therefore, the integration of DFA into reservoir development activities under a repetitive process as new wells are drilled in these fields updating the fluids and geological models is needed to optimized the reservoir management of these fields. - DFA is a process aimed not only to get clean samples, but to utilize laboratory studies and real time down hole fluid data to build and constrain geologic and reservoir models.

- It is highly desirable to match the complexity of fluids in the reservoir with the complexity of the sampling and analysis job; this can be accomplished only through DFA. The final objective, a “continuous downhole fluid log,” can be constructed with proper use of DFA.

Acknowledgment The authors would like to thanks Schlumberger to publish this paper; however, the applied integration methodology and conclusions put forward in this paper are the responsibility of the authors alone. We would also like to thank Luiz R. Faria of Petrobras and Jay Dunlap of Schlumberger for his inputs and comments. References

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