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A Basic Theory of Clastic Reservoir Stochastic Modeling and Its Practice

CHEN Gong yang (Jianghan Petroleum Institute, Jingzhou, 434102)  
A basic thought and a method system are briefly described for stochastic reservoir modeling The key of the method is to take the reservoir attributes on an arbitrary point in space as random variables for calculating the post conditional accumulative distribution function and realizing Monte Carlo simulation of output values Based on the practical geologic conditions and different needs for a model, the simulation methods include 5 types, such as Gauss simulation, indicator simulation, sequential simulation, Boolean simulation and annealing simulation A procedure for clastic reservoir modeling is put forward, which includes:①establishing prototype reservoir model or a reservoir geologic knowledge base;②establishing a stochastic reservoir model;③stochastic reservoir modeling Two basic procedures for building a lithofacies model and a reservoir parameter model by controlling the lithofacies are deployed during the simulation The method for realizing the procedures and process mentioned above is introduced specifically through an oilfield case study The result of modeling shows that the method is feasible and necessary
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