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The AAPG/Datapages Combined Publications Database
AAPG Bulletin
Abstract
AAPG Bulletin, V.
Rock types and permeability prediction from dipmeter and image logs: Shuaiba reservoir (Aptian), Abu Dhabi
S. Duffy Russell,1 Mahmoud Akbar,2 Badarinadh Vissapragada,3 Gordon M. Walkden4
1Saudi Arabian Oil Company, P.O. Box 5000, Dhahran 31311, Saudi Arabia; email: [email protected]
2Schlumberger-Reservoir Evaluation/Interpretation Development, P. O. Box 21, Abu Dhabi, United Arab Emirates; email: [email protected]
3Schlumberger-Reservoir Evaluation/Interpretation Development, P. O. Box 21, Abu Dhabi, United Arab Emirates; email: [email protected]
4Department of Geology and Petroleum Geology, University of Aberdeen, Meston Building, King's College, Aberdeen, AB24 3UE, Scotland, United Kingdom; email: [email protected]
AUTHORS
Duffy Russell is a senior carbonate geologist at Saudi Aramco in the Reservoir Characterization Department, Southern Fields Characterization Division. He received B.S. and M.S. degrees in geology from North Carolina State University in 1976 and Duke University in 1979 and a Ph.D. in geology from the University of Aberdeen in 2001. He started his career as a geophysicist with Amoco Production Company in 1979 and has worked nearly 21 years as a geologist for Mobil Oil Corporation and ExxonMobil, specializing in carbonate reservoir characterization.
Mahmoud Akbar is a principal geologist for Schlumberger working Iran, Qatar, the United Arab Emirates, Oman, and Yemen. He started his professional career with Schlumberger Wireline and Testing in 1985 in Pakistan. He received B.Sc. (1983) and M.Sc. (1985) degrees in applied geology from the University of Punjab, Pakistan. He has carried out research in the Lower Himalayas on factors controlling fractures and their effect on rock strength.
Badarinadh Vissapragada is a senior petrophysicist with Schlumberger Data and Consulting Services, Abu Dhabi, United Arab Emirates. He did his postgraduate study in geophysics at Andhra University, Waltair, India. He has more than 19 years of petrophysics experience in India and Middle East reservoirs from fieldwide petrophysical studies and reservoir characterization. His special interests are reservoir rock typing, permeability, and fracture detection.
Gordon Walkden is head of the Department of Geology and Petroleum Geology at the University of Aberdeen, Scotland. After receiving a degree from Quintin School in London, he obtained his Ph.D. in carbonate sedimentology from Manchester University, United Kingdom, in 1970. Gordon was appointed senior lecturer in 1988 and became department head in 1993. He has extensive field experience and supervision of research projects in Britain, Europe, North America, and the Middle East.
ACKNOWLEDGMENTS
We are grateful to the Abu Dhabi Company for Onshore Oil Operations (ADCO), Abu Dhabi National Oil Company (ADNOC), Mobil Oil Corporation, and Schlumberger for permission to publish this article. We thank Sandeep Chakravorty of Schlumberger-Geoquest for his assistance in preparing the software analyses. Peter Skelton and Jean-Pierre Masse provided valuable assistance in the identification of rudist assemblages. Helpful suggestions on the draft manuscript were made by AAPG reviewers Neil Hurley and Stephen Prensky.
ABSTRACT
The Shuaiba Formation is a complex carbonate reservoir characterized by small-scale geological heterogeneity primarily related to rudist macrofauna. The textural heterogeneity corresponds to extreme permeability variation that is the controlling factor in reservoir production. Because of the large vertical
resolution
contrast between cores (actual scale) and conventional logs (averaged responses over a few feet), extrapolation of small-scale heterogeneity into uncored wells using a traditional approach is unreliable. High-
resolution
log data, like dipmeters and image logs, are required to characterize small-scale heterogeneity that is essential to a good three-dimensional (3-D) geological model that predicts true reservoir behavior. Our study illustrates an approach to improve the reservoir characterization of the Shuaiba by quantifying small-scale heterogeneity using dipmeter and image logs.
A methodology is proposed to use the existing high-resolution
(High-
resolution
Dipmeter Tool [HDT], Stratigraphic High-
resolution
Dipmeter Tool [SHDT], and Formation MicroScanner [FMS]) and conventional log data to characterize and extrapolate geological heterogeneity. Texture and neural network analyses, derived from microresistivity variations and a multiregression approach, have been used in two wells to demonstrate the methodology. Both rock types and permeability are estimated for extrapolation into uncored wells. Although differences between the conductivity of conductive and resistive areas when normalized for background conductivity are an indirect measure of permeability for HDT and SHDT, the connectivity coefficient of conductive anomalies derived from textural analysis is related to permeability in the case of FMS. Reservoir rock types (RRT) obtained from the methodology correlate well with RRTs derived from the integration of core, special core analysis (SCAL), and conventional log data in two test wells. Permeability estimations, including small-scale
extreme variations from less than 1 md in tight mudstones to greater than 1 d in caprinid rudstones, are in good agreement with the core plug permeability measurements after a simple calibration. In one example, permeability trends in rudist RRTs, which are not discernible using core plugs and minipermeameter data, are clearly resolved using SHDT data. The degree of correlation between estimated and core permeabilities is greater with increased
vertical
resolution
of the tool (HDT, lowest; FMS, highest).
Distinct RRTs resulting from small-scale geological heterogeneity can be classified and permeability can be estimated with a high degree of confidence, providing a better pathway of extrapolating from core data to conventional logs for 3-D modeling. The methodology has potential application to other carbonate and siliciclastic reservoirs with appropriate calibration and scaling. Underused HDT, SHDT, FMS, and Fullbore Formation MicroImager (FMI) databases are available in many other areas that could be analyzed. An order of magnitude improvement in the ability to characterize small-scale heterogeneity has significant implications for future coring, logging programs, and reservoir characterization efforts.
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