Assessing Reservoir Compartmentalization Using Oil Geochemistry

For many years, a variety of companies have applied oil geochemistry (oil fingerprinting) to reservoir continuity assessment in a diverse range of geological settings (including a wide range of field sizes, structural environments, reservoir lithologies, and oil types). As demonstrated by numerous published and unpublished case studies, petroleum geochemistry provides an effective tool for identifying vertical and lateral fluid flow barriers within oil and gas fields. The technique is especially useful because it provides an independent line of evidence for evaluating the reservoir continuity implications of other data types (data such as RFT pressures, pressure decline curves, oil-water contact depths, fault juxtaposition or Allen diagrams, etc.).

At OilTracers, we assess reservoir compartmentalization by integrating geochemical, geological, and engineering data to determine the sealing capacity of potential no-flow barriers. Oil geochemistry typically provides a very inexpensive key to interpreting ambiguous geological and/or engineering information. This approach is described below.

Description of the Oil Fingerprinting Approach for Assessing Reservoir Continuity

In a series of five papers published over a 14-year period, scientists from Chevron described and demonstrated an oil fingerprinting technique for assessing reservoir continuity based on integration of oil geochemistry with geological and engineering information (e.g., Slentz, 1981; Kaufman et al., 1990; Hwang and Baskin, 1994; Hwang et al., 1994; Sundararaman et al., 1995). Variations on this technique are currently used by a variety of oil companies (as detailed in the case studies). The technique put forward by these five papers is described in this section. The individual published case studies that illustrate the use of oil geochemistry in reservoir continuity assessment are described on our case studies page.

The approach described in the five papers mentioned above is based on the proposition that oils from discrete reservoirs almost always differ from one another in composition. The technique assesses whether or not two oils are in fluid communication by comparing for each oil the relative abundances of the several hundred "inter-paraffin" peaks identifiable on a whole oil gas chromatogram or "GC". Inter-paraffin peaks are those compounds that elute from the GC between the normal-paraffins. The patterns for each sample are compared as follows:

1. Corresponding inter-paraffin peaks are identified in all samples.
2. For a given sample, several hundred ratios of closely spaced inter-paraffin peaks are compared with the corresponding ratios in the other samples.
3. The ratios that differ the most between samples are identified.
4. Values for these ratios for each sample are plotted on polar or "star" plots. On such diagrams, the composition of each oil is represented by a "star" in which each point on the star corresponds to the value for a given peak ratio.

Star plots constructed in this way maximize the apparent differences between samples. By stripping away what samples have in common and focusing on how they differ, such plots allow discrete groups of samples to be readily, visually identified. To arrive at an assessment of reservoir compartmentalization, these data must be integrated with any other available and relevant geological and/or engineering information (such as fault distributions, fault throws, fault shale/sand gouge ratios, lateral changes in reservoir lithology, RFT or DST pressure data, pressure decline curves, oil-water contact depths, etc.). Commonly, in oils which are in fluid communication, none of the several hundred inter-paraffin compound ratios will differ by more than 10% from the corresponding ratios in oils with which they are in fluid communication. In contrast, when a lack of fluid communication exists between two samples, a large number of ratios (typically >10) in one oil will differ by >10% from the corresponding ratios in the second oil. These ratios will commonly be distributed throughout the C₈-C₂₀ range, and will not be restricted to a narrow portion (e.g., a one or two carbon number range) of the chromatogram (differences restricted to a narrow portion of the chromatogram are a symptom of sample contamination with substances such as drilling additives and typically do not imply reservoir continuity barriers). The analytical reproducibility for ratios of closely spaced inter-paraffin peaks is typically 1-3% (Kaufman et al., 1990). As the number of ratios with significant differences between the samples decreases, the geochemical case for lack of communication becomes less strong. Exceptions to these guidelines exist in cases of certain thick, gravitationally segregated oil columns, where reservoir discontinuities must be identified from discontinuities in otherwise gradational changes in composition with depth. The C₈ to C₂₀ molecular weight range on the GC is typically the most diagnostic range for reservoir continuity assessments. The distribution of lower molecular weight compounds is usually not compared, since they can be more readily affected by evaporative losses during sample handling.

The star diagram approach for assessing fluid communication is effective for comparing GC data for a small number of samples. As the number of samples increases, the number of possible compartments increases, and a single star diagram may no longer be able to summarize all the compositional variability between the samples (e.g., the dozen GC peak ratios that differ most between oils A and B may be different than the dozen ratios that differ most between oils A and C which may differ from the ratios that best separate A from D). Therefore, the samples compared on a given star diagram are chosen so as to answer a specific question, such as: "is this fault sealing?" Only the samples relevant to answering that question should be included on that diagram. Therefore, compositional variability in large sample sets may have to be evaluated with several star diagrams in which each diagram is designed to answer a different, specific question about the reservoir architecture. To make a general comparison of GC data for a large number of samples, the GC peak ratio data used to construct the several star diagrams can be compared statistically and used to construct a single cluster analysis diagram (e.g., Hwang and Baskin, 1994).

The differences observed among the star diagrams for a group of samples are the result of compositional differences among the samples, and these compositional differences exist for one or more of the following reasons (e.g., Hwang et al., 1994):

1. The oils may be derived from different source rocks, or may have differing contributions of oil from multiple source rocks. (Note on terminology: a "source rock" has nothing to do with the reservoir rock that contains the oil in the oil field; the source rock is the rock that generated the oil that later migrated into the reservoir rock. The source rock may be 10's of miles away from the oil field). Oils derived from different source rocks differ in composition. Since oils from different source rocks have different times of generation and/or different migration paths, the presence of more than one source rock in a basin may cause different reservoir compartments to fill with different mixes of oil from the respective sources. For example, oil in Prudhoe Bay is known to be a mixture of petroleum from three source rocks of very different age (Masterson et al., 1997; 2001), and source variations are therefore a likely cause of the compositional differences among oils from discrete fault blocks in that field. A second example can be found in Schoellkopf et al. (1998 and 2000) where the authors discuss variations in charges from three different source rocks in offshore Cabinda, west Africa; those source variations result in both lateral and vertical variations in oil fingerprints within and among the offshore oil fields in that area.
2. The oils may be derived from the same source rock but at a different level of thermal maturity. Oil which a source rock generates at a given time differs slightly both from subsequently generated oil and previously generated oil due to continuous, subtle changes in the maturity of the source rock and changes in precisely which part of the source rock is in the oil window.
3. Post-emplacement alteration processes. Identically sourced oils that reside in separate reservoir compartments may have had a different exposure to processes that affect oil composition after the oil enters the reservoir (e.g., processes such as biodegradation, water washing, and evaporative fractionation).
4. Filling history considerations. Since no two compartments are of identical geometry, and since no two compartments have exactly the same filling history, it is difficult to achieve precisely the same composition in two separate compartments, even with oil from the same source.

An important aspect of this oil fingerprinting approach is that a given star diagram can only be constructed from data acquired from the same instrument within a several day analytical period. For a given diagram, data cannot be compared between instruments because differences in analytical conditions (e.g., different GC columns, different carrier gas pressures, or different column ages) will cause subtle differences in peak resolution that may show up as large differences in the peak ratios. Data collected from the same instrument several months apart also cannot be compared on a single diagram, since analytical conditions may have changed during the analysis of the intervening samples (conditions such as GC column characteristics).

Assessing Reservoir Continuity in a Gas Accumulation

A similar approach is used to assess continuity in gas accumulations. However, a greater range of geochemical analyses may be brought to bear, including:

• Gas chromatography data for the gas condensates (with the data being processed using the inter-paraffin peak ratio method described above for oils)
• Gas composition (e.g., relative abundance of each gas present, including trace gases, such as helium)
• Isotopic composition of carbon and/or hydrogen in specific gas species (methane, ethane, CO₂, etc.)
• Isotopic composition of carbon and/or hydrogen of the paraffins in the gas condensate

Case Studies

Case studies in which geochemistry is used as part of a reservoir continuity assessment include: Slentz (1981), Kaufman et al. (1990), Lindberg et al. (1990), Hwang and Baskin (1994), Hwang et al. (1994), Sundararaman et al. (1995), Ross and Ames (1988), Nederlof et al. (1994; 1995), Westrich et al. (1996; 1999), Noyau et al. (1997), Kaufman et al. (1997), Edman and Burk (1999), Smalley et al. (1992; 1994), England et al. (1995), Smalley and Hale (1996), and Halpern (1995). A summary of some of these case studies is available elsewhere on this site.

Additional Considerations When Applying Oil Fingerprinting to Continuity Assessment

Throughout the literature on oil fingerprinting, a common caveat is that oil fingerprinting is most successful as a technique for assessing reservoir continuity when it is applied in conjunction with other lines of evidence, such as:

• RFT/ DST pressure data

• Pressure decline curves

• Dew-point calculations (for gas continuity studies)

• Reservoir descriptions (from core, cuttings, and log data)

• Oil-water contact depths

• Fault sand/shale gouge ratios

• Fault juxtaposition (Allen) diagrams

This caveat to integrate disparate data types applies to all lines of evidence for reservoir continuity assessment. This is true because these data types are independent of one another, and hence provide valuable crosschecks. Crosschecks are important because every technique is subject to potential pitfalls. Some such potential pitfalls associated with the application of oil fingerprinting to assessment of reservoir continuity are discussed in the sections below.

Very Unusual Filling Histories

Very unusual scenarios could exist where nearly identical oils are found in separate compartments. For example, two pools could have the same composition if they were originally in communication, but then achieved separation do to a poor seal causing a reduction in overall pool size (creating two pools out of one). Alternatively, tilting of a large, homogenous pool could conceivably cause oil of a given composition to spill into two neighboring traps. Several other such scenarios can be imagined. As a result, to interpret reservoir continuity, we integrate geochemical information with what is known about the geology and geological history. An example of unusual filling history was presented by Patterson et al. (2003) where an oil field located in the near-shore Nigerian swamp consisted of two stacked reservoirs bisected by a fault. Oil fingerprints, water chemistry, and engineering data suggested that gas and then oil had leaked from the deeper reservoir into selective areas of the shallow reservoir due to poor fault seal and fault-induced juxtaposition of the two reservoirs.

Very Young Reservoirs

At a recent conference, a case study was presented (Beeunas et al., 2000) in which oil reservoired in a very young sandstone (the reservoir rock was deposited on the 1.86 million year sequence boundary) was found to have heterogeneous oil fingerprints within a single compartment. The speaker pointed out how very unusual this situation was, and pointed to the extremely recent timing of the oil emplacement based on burial history and thermal maturation models as the cause for the heterogeneity (generation possibly extends to the present). In cases such as this, where the charge is very recent, care should be used in interpreting the reservoir continuity implications of differences in oil fingerprints.

Gravitationally Segregated Oil Columns

Very thick oil columns are often gravitationally segregated (e.g., Creek and Schrader, 1985). Perhaps the most obvious expression of such segregation is a progressive increase in API gravity with decreasing reservoir depth. Such segregation often does not change the oil fingerprint substantially (Kaufman et al. 1990), because compound ratios selected for the star diagrams are of closely spaced inter-paraffin peaks, and the similar molecular weight of such closely spaced compounds greatly reduces the effect of gravitational segregation on the peak ratio values. Nonetheless, we have sometimes observed progressive changes in peak ratios with depth in very thick oil columns (McCaffrey et al., unpublished data). In such cases, vertical continuity barriers can best be identified by plotting compound ratio values vs. depth and then inspecting these plots for discontinuities in an otherwise gradual trend. In other words, if a compound ratio is changing progressively with depth, and this progressive change is broken by a sudden, large change in value across a potential barrier, then that large change would be evidence for that feature being a fluid-flow barrier.

Actively Biodegrading Oil Reservoirs

In actively biodegrading oil accumulations, biodegradation typically occurs at the oil/water contact (e.g., Dahl and Speers, 1985; Larter et al., 2006). Mixing processes are commonly unable to homogenize the perturbation in composition being introduced by this biodegradation process, and, as a result, a compositional gradient away from the oil-water contact may develop in the oil column. In such cases, vertical or lateral compartment boundaries are revealed as vertical or lateral discontinuities in the biodegradation-induced compositional gradient.

Very Tight Reservoirs

McCaffrey et al. (1996) discussed extreme variability in oil fingerprints within a very shallow, very tight reservoir (diatomite rock, <1 md permeability) in the Cymric Field, Kern County California. That reservoir contained very heavy (12o API), very viscous oil that may have been undergoing active biodegradation right up until the initiation of the current steam flood. The oil fingerprint data reported by McCaffrey et al. (1996) may initially seem to be at odds with the assertion that oils within a reservoir have nearly identical fingerprints. However, there is no conflict here at all. In very tight reservoirs, the concept of "reservoir continuity" is not applicable: the whole oil-bearing unit can be thought of as one giant no-flow barrier. In fact, the only way that the Cymric field produces oil at all is by steam-fracturing the diatomite to create permeability. Therefore, in an engineering sense, the "reservoir" is CREATED by the fracturing process: the body of rock that eventually produces into a Cymric well is defined by the artificial fracturing process used to stimulate that well. Compositional variability in this field has no relevance at all to the oil fingerprinting technique for assessing reservoir continuity: there is no reservoir continuity in a very tight reservoir.

Confusion Resulting From How the Term "Reservoir" is Used

The term "reservoir" is used differently by different authors, and, in some papers, the sense in which the term is being used is not immediately obvious. As a result, statements in some publications may initially seem to be at odds with the oil fingerprinting technique described above. However, in actuality, many of these apparent conflicts stem solely from the way the term "reservoir" is being used.

When discussing the oil fingerprinting technique, the term "reservoir" refers to an oil-bearing body of rock that is in fluid communication throughout its lateral and vertical extent. In this usage, a "reservoir" does NOT correspond to a stratigraphic unit. For example, "Oil Field A" may contain an oil-bearing stratigraphic unit called the "Alpha Sandstone." This sandstone may be cut by two sealing faults that divide the Alpha Sandstone into three compartments. In the sense in which "reservoir" is used with regard to oil fingerprinting, "Oil Field A" contains THREE reservoirs: one corresponding to each compartment. Although there is only one stratigraphic unit (the Alpha Sandstone) there are three reservoirs, because that sandstone is compartmentalized into 3 units that are not in communication with each other. This use of the word "reservoir" is consistent with how a production engineer uses the term. Geologists, however, may be prone to write: "The Alpha sandstone is the reservoir in Oil Field A", implying that there is one, not three reservoirs. As a result, when some authors report oil fingerprint variability within a "reservoir", they actually mean within a stratigraphic unit. That stratigraphic unit may consist of several compartments, each of which is internally homogenous with respect to oil fingerprints. Therefore, the fingerprint variability they are reporting is BETWEEN compartments, not within compartments.

Confusion Over the Terms "Composition" and "Fingerprint"

The "composition" of an oil refers collectively to the absolute concentrations of each compound in the oil. The term "oil fingerprint", as used with regard to the technique described is this article, refers to the relative abundances of closely spaced peaks on an oil GC (i.e., the values for ratios of closely spaced peaks). As noted by Kaufman et al. (1990):

"The term "uniform fingerprint" is not to imply uniform hydrocarbon composition. There are many factors that may affect the composition of oil within a pool, including gravity segregation (Creek and Schrader, 1985), degradation at the oil/water contact (Dahl and Speers, 1985), and migration effects (England et al., 1987). These effects can usually be normalized by using ratios of peaks corresponding to compounds of similar, if not identical, molecular weight in the n-C7+ region of the chromatogram"

No one disputes that the composition of oil in a very thick compartment can change with depth as a result of gravitational segregation. As noted in the previous section, perhaps the most obvious expression of such segregation is a progressive increase in API gravity with decreasing reservoir depth. However, as Kaufman et al. (1990) note, such segregation often does not change the oil fingerprint substantially because compound ratios selected for the star diagrams are of closely spaced inter-paraffin peaks, and the similar molecular weight of such closely spaced compounds greatly reduces the effect of compositional variations (such as gravitational segregation) on the peak ratio values. Therefore, when reading the literature, it is important to distinguish between what the authors mean by "fingerprint" vs. "composition".

This figure provides a simplified illustration of how oil geochemistry can be used to assess reservoir continuity. The sampling points of five oils (black boxes) in three wells are shown. The star plots of the five oils are depicted next to their sampling locations. Continuity of sand I between Wells B and C is suggested by the identical star plots for the sand I oils from those two wells. No communication between sands I and II in Well B is suggested by the different star plots for the Well B oils from those sands. Fault X is sealing where sands I and II are juxtaposed, since sand II and sand I oils from Wells A and B, respectively, have different star plots. Remember: geochemical data should be integrated with the geological, and engineering data (e.g., RFT pressure data, pressure decline curves, oil/water contact depths, GOR values, etc.) before arriving at a reservoir continuity interpretation.

Anthropogenic Chemical Tracers

The oil fingerprinting technique for assessing reservoir communication discussed in this article is entirely different than the technique of using anthropogenic chemical tracers as tools for assessing reservoir continuity. Anthropogenic chemical tracers are compounds that are added to injection fluid and are monitored in the production of associated producing wells in order to assess reservoir continuity between the injection well and the producing wells (e.g., Dugstad et al., 1999; Ali et al., 2000; Chopra and McConnell, 2004). In contrast, the approach discussed here uses naturally occurring compounds in the oil as natural tracers for assessing reservoir communication.

For more information on reservoir continuity assessment, or to discuss a specific project, e-mail us at info@oiltracers.com, or call us at (214) 548-9169.

References

Ali, E., C. Chatzichristos, T. Aurdal, and J. Muller, 2000, Tracer Simulation to Improve the Reservoir Model in the Snorre Field: SPE Paper No. 64796.

Beeunas, M. A., T. A. Hudson, J. A. Valley, D. K. Baskin, and W. Y. Clark, 2000, Identification of reservoir discontinuities using hydrocarbon compositional analyses, Genesis field (Green Canyon 205), Gulf of Mexico: AAPG Annual Meeting, New Orleans, Louisiana, April 16-19, 2000, AAPG Bulletin, Vol. 84, No. 13, Abstract.

Chopra, S., and I. McConnell, 2004, Using interwell chemical tracers and the coherence cube to understand reservoir communication: Oil & Gas Journal, v. 102.19 (May 17), p. 37-42.

Creek, J. L., and M. L. Schrader, 1985, East Painter reservoir, an example of a compositional gradient from a gravitational field: SPE, paper No. 14411.

Dahl, B., and G. C. Speers, 1986, Geochemical characterization of a tar mat in the Oseberg Field Norwegian Sector, North Sea: Org. Geochem., v. 10, p. 547-558.

Dugstad, Ø., T. Aurdal, C.Galdiga, I. Hundere, and H.J.Torgersen, 1999, Application of Tracers to Monitor Fluid Flow in the Snorre Field: A Field Study: SPE Paper No. 56427.

Edman, J. D., and M. K. Burk, 1999, Geochemistry in an Integrated Study of Reservoir Compartmentalization at Ewing Bank 873,Offshore Gulf of Mexico: SPE Paper No.57470.

England, W. A., A. H. Muggeridge, P. J. Clifford, and Z. Tang, 1995, Modelling density-driven mixing rates in petroleum reservoirs on geological time-scales, with application to the detection of barriers in the Forties Filed (UKCS), in J. M. Cubbit, and W. A. England, eds., The Geochemistry of Reservoirs, Geological Society Special Publication No. 86. The Geological Society of London, U.K., p. 185-201.

England, W. A., A. S. MacKenzie, D. M. Mann, and T. M. Quigley, 1987, The movement and entrapment of petroleum fluids in the subsurface: J. of the Geological Society, London, v. 144, p. 327-347. Halpern, H. I., 1995, Development and Applications of Light-Hydrocarbon-Based Star Diagrams: AAPG Bull., v. 79, p. 801-815.

Hwang, R. J., A. S. Ahmed, and J. M. Moldowan, 1994, Oil composition variation and reservoir continuity: Unity Field, Sudan: Org. Geochem., v. 21, p. 171-188.

Hwang R. J. and Baskin D. K. (1994). Reservoir connectivity and oil homogeneity in a large-scale reservoir. Middle East Petroleum Geoscience Geo94 2, 529-541.

Kaufman, R. L., A. S. Ahmed, and R. J. Elsinger, 1990, Gas Chromatography as a development and production tool for fingerprinting oils from individual reservoirs: applications in the Gulf of Mexico, in D. Schumaker, and B. F. Perkins, eds., Proceedings of the 9th Annual Research Conference of the Society of Economic Paleontologists and Mineralogists, October 1, 1990: New Orleans, p. 263-282.

Kaufman, R. L., H. Dashti, C. S. Kabir, J. M. Pederson, M. S. Moon, R. Quttainah, and H. Al-Wael, 1997, Characterizing the greater Burgan Field: Use of geochemistry and oil fingerprinting: SPE Paper No. 37803, p. 385-394. Lindberg, F. A., A. S. Ahmed, and D. C. T. Bluhm, 1990, The role of oil-to-oil correlation in the development of the Safah field (abstract): AAPG Bulletin, v. 74, p. 705.

Larter, S., H. Huang, J. Adams, B. Bennett, O. Jokanola, T. Oldenburg, M. Jones, I. Head, C. Riediger, and M. Fowler, 2006, The controls on the composition of biodegraded oils in the deep subsurface: Part II - Geological controls on subsurface biodegradation fluxes and constraints on reservoir-fluid property prediction: AAPG Bulletin, v. 90, p. 921-938.

Masterson, W. D., L. I. P. Dzou, A. G. Holba, A. L. Fincannon, and L. Ellis, 2001, Evidence for biodegradation and evaporative fractionation in West Sak, Kuparuk, and Prudhoe Bay field areas, North Slope, Alaska: Org. Geochem., v. 32, p. 411-441.

McCaffrey, M. A., H. A. Legarre, and S. J. Johnson, 1996, Using biomarkers to improve heavy oil reservoir management: An example from the Cymric field, Kern County, California: AAPG Bull., v. 80, p. 904-919.

Nederlof, P. J., M. A. Gijsen, and M. A. Doyle, 1994, Application of reservoir geochemistry to field appraisal, in M. I.Al-Husseini, ed., The Middle East Petroleum Geosciences Geo'94, vol.2.Gulf-Petrolink, Bahrain, p. 709-722.

Nederlof, P. J. R., F. M. van der Veen, and G. A. van den Bos, 1995, Application of reservoir geochemistry in Oman, in J. O.Grimalt, and C. Dorronsoro, eds., Organic Geochemistry: Developments and Applications to Energy, Climate, Environment and Human History. Selected Papers from the 17th International Meeting on Organic Geochemistry, Donostia-SanSebastián, The Basque Country, Spain: San Sebastian, AIGOA, p. 329-331.

Noyau, A., P. Chavagnac, E. W. Tegelaar, and F. Daugas, 1997, Reservoir Characterization Applying Geochemical Techniques: Case Study From Yemen, Paper No. 37703: SPE.

Patterson, B., J. Garrity, and F. Kpenkaan, 2003, Two Reservoirs - Several Different Oil and Water Compositions, Swamp Field, Nigeria: in J. Cubbitt, W. England, S. Larter, and G. Macleod, ed., Conference Abstracts: Geochemistry of Reservoirs II: Linking Reservoirs Engineering and Geochemical Models (Geological Society of London, February 3-4, 2003).

Ross, L. M., and R. L. Ames, 1988, Stratification of oils in Columbus basin off Trinidad: Oil & Gas J., Sept. 26 issue, p. 72-76.

Schoellkopf, N. B., B. A. Patterson, and J. G. Gaulier, 1998, Unsnarling of Petroleum Systems Through Geochemical Methods, Offshore Cabinda, Angola, AAPG International Conference (Rio de Janeiro, Brazil, 11/8-11/11/1998), Conference abstract: AAPG Bulletin v.82 no.10 p. 1964.

Schoellkopf, N. B. and B. A. Patterson, 2000, Chapter 25 Petroleum Systems of Offshore Cabinda, Angola: in M. R. Mello and B. J. Katz, ed, Petroleum Systems of South Atlantic Margins: AAPG Memoir, v. 73: Tulsa, AAPG.

Slentz L. W. (1981). Geochemistry of reservoir fluids as unique approach to optimum reservoir management. SPE #9582. Presented at Middle East Oil Technical Conference, Manama, Bahrain.

Smalley, P. C., and W. A. England, 1994, Reservoir Compartmentalization Assessed with Fluid Compositional Data: SPE Res. Eng., v. August, p. 175-180.

Smalley, P. C., and N. A. Hale, 1996, Early Identification of Reservoir Compartmentalization by Combining a Range of Conventional and Novel Data Types, SPE Paper No. 30533.

Smalley, P. C., and W. A. England, 1992, Assessing reservoir compartmentalization during field appraisal: How geochemistry can help: SPE Paper No. 25005, p. 423-431.

Sundararaman, P., B. A. Patterson, and O. T. Udo, 1995, Reservoir geochemistry: applications and case studies in Nigeria, in J. O. Grimalt, and C. Dorronsoro, eds., Organic Geochemistry: Developments and Applications to Energy, Climate, Environment and Human History. Selected Papers from the 17th International Meeting on Organic Geochemistry, Donostia-SanSebastián, The Basque Country, Spain: San Sebastian, AIGOA, p. 369-371.

Westrich, J. T., P. O. Knigge, A. N. Feux, and H. I. Halpern, 1996, Evaluating reservoir architecture in the northern Gulf of Mexico using oil and gas chemistry: SPE Paper No. 36541, p. 513-519.

Westrich,J. T., A. M. Fuex, P. M. O'Neal, and H. I. Halpern, 1999, Evaluating Reservoir Architecture in the Northern Gulf of Mexico With Oil and Gas Chemistry: SPE Paper No. 59518.