[First Hit]

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Relationship Between Previous HitPoreNext Hit Geometry and Previous HitPoreNext Hit-Previous HitThroatNext Hit Geometry as a Means to Predict Reservoir Performance in Secondary Recovery Programs for Carbonate Reservoirs*

By

Christina M. Dicus1


Search and Discovery Article #40318 (2008)

Posted October 24, 2008


*Adapted from oral presentation at AAPG Annual Convention, San Antonio, Texas, April 20-23, 2008.

1 Petrophysical Analysis Subsurface Technology, ConocoPhillips, Houston, TX ([email protected])

Abstract

The purpose of this study was to develop a method by which a detailed porosity classification system could be used to understand the relationship between Previous HitporeNext Hit/Previous HitporeNext Hit-Previous HitthroatNext Hit geometry, genetic porosity type, and facies. This study also investigated the relationships between Previous HitporeNext Hit/Previous HitporeNext Hit-Previous HitthroatNext Hit geometry, petrophysical parameters, and reservoir performance characteristics. The focus was on the Jurassic Smackover reservoir rocks of Grayson field, Arkansas. This three part study developed an adapted genetic carbonate Previous HitporeNext Hit type classification system and used petrographic image analysis and mercury-injection capillary pressure tests to calculate Previous HitporeNext Hit/Previous HitporeNext Hit-Previous HitthroatNext Hit Previous HitsizesNext Hit. These were compared to facies, Previous HitporeNext Hit type, and each other showing that Previous HitporeNext Hit-Previous HitthroatNext Hit size is controlled by Previous HitporeNext Hit type and that Previous HitporeNext Hit size is controlled primarily by facies. Previous HitPoreNext Hit size range can be estimated from Previous HitporeNext Hit type and median Previous HitporeNext Hit-Previous HitthroatNext Hit aperture. Capillary pressure data was used to understand the behavior of the dependent rock properties. It was determined that size-reduced samples tend to show similar dependent rock property behavior, but size-enhanced samples show dispersion. Capillary pressure data was used to understand fluid flow behavior of Previous HitporeNext Hit types and facies. Oncolitic grainstone samples show unpredictable fluid flow behavior compared to oolitic grainstone samples, yet oncolitic grainstone samples will move a higher percentage of fluid. Size-enhanced samples showed heterogeneous fluid flow behavior while the size-reduced samples could be grouped by the number of modes of Previous HitporeNext Hit-Previous HitthroatNext Hit Previous HitsizesNext Hit. Finally, this study used petrographic image analysis to determine if 2-D porosity values could be compared to porosity values from 3-D porosity techniques. The heterogeneous Previous HitporeNext Hit network found in the Grayson reservoir rocks prevents the use of petrographic image analysis as a porosity calculation technique.

Selected Figures

Figure 1 Location map and columnar section.
Figure 2 Previous HitPoreNext Hit type classification, with recommendation for a more detailed scale for Hybrid 1 Previous HitporeNext Hit types.

Conclusions

Previous HitPoreNext Hit typing through descriptive characterization of the degree and type of diagenetic processes distinctly separates different rock types by their dependent rock properties, petrophysical parameters, and flow capacity.

Key is: spatial distribution.

Why? Both J-function and Lorenz curves show that enhanced and reduced Previous HitporeNext Hit type groups have distinctly unique dependent rock properties and fluid flow characteristics.

Goal: With the help of a detailed chronostratigraphic study, correlate Previous HitporeTop type locations across the field (from facies) and by extension determine the spatial distribution of the dependent rock properties and fluid flow behavior.

References

Moore, Clyde H., and Yehezkell Druckman, 1981, Burial diagenesis and porosity evolution, Upper Jurassic Smackover, Arkansas and Louisiana: AAPG Bulletin, v. , p. 597-628.

Ahr, Wayne, M., 1973, The carbonate ramp: An alternative to the shelf model: GCAGS Transactions, v. 23, p. 221-225.

Lorenz, M.O., 1905, Methods of measuring the concentration of wealth: Publications of the American Statistical Association, v. 9, p. 209-219.

Acknowledgments

Anderson Oil & Gas and Petro-Chem Operating for research sponsorship and guidance.

Dr. Wayne Ahr for life-long mentorship.

ConocoPhillips for the opportunity to attend this meeting.

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