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

Abstract

Abstract Net 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 the wild nature of petroleum reservoirs. It becomes even more challenging in carbonates, because of their highly heterogeneous environment. Conventionally, net pays are evaluated by applying petrophysical cut-offs on well-logs, which results in crisp classification of pay or non-pay zones. In addition, the cut-off-based method is developed in sandstones, and does not provide suitable results in carbonates at all. The proposed methodology of this work, the Dempster–Shafer Theory, is a generalization of the Bayesian Theory of conditional probabilities. Net pays are studied in two oil reservoirs by this theory: one of them is the carbonate reservoir of Mishrif and the other is the sandy Burgan reservoir. For validation, results are compared to well tests and output of the conventional cut-off method. The advantages of using the Dempster–Shafer Theory, compared to the conventional cut-off-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.