Net pay determination by Dempster rule of combination: Case study on Iranian offshore oil fields

Abstract

International audienceNet pay detection is a key stage in reservoir characterization for several purposes: reserve estimation, reservoir modeling and simulation, production planning, etc. Determining productive zones always is simultaneous with some amount of uncertainty due to lack of enough data, insufficiency of knowledge and wild-nature of petroleum reservoirs. It becomes even more challenging in carbonates, because of their highly heterogeneous environment. Conventionally, evaluating net pays is done by applying petrophysical cutoffs on well-logs, which results in crisp classification of pay or non-pay zones. In addition, cutoff based method is developed in sandstones, and does not provide suitable results in carbonates at all. Proposed methodology of this work, Dempster-Shafer Theory, is a generalization of Bayesian Theory of conditional probabilities. Net pays are studied in two oil reservoirs by this theory; one of them is carbonate reservoir of Mishrif, the other is sandy Burgan reservoir. For validation, results 2 are compared to well tests and output of conventional cutoff method. The advantages of using Dempster-Shafer Theory, comparing to conventional cutoff based method in studying net pays is: to have a continuous fuzzy output, based on geological facts, with high generalization ability and more compatibility with well test data

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Petrophysical Analysis Based on Well Logging Data for Tight Carbonate Reservoir: The SADI Formation Case in Halfaya Oil Field

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Neural network applications to reservoirs: Physics-based models and data models

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