We present a new method and a field data example for creating reservoir models that simultaneously match seismic and geologic data. Our method combines geostatistical simulation and multi-objective optimization, and it is used to improve static reservoir model estimation by simultaneously integrating multiple datasets including well logs, geologic information and various seismic attributes. The main advantage of our approach is that we can define multiple objective functions for a variety of data types and constraints, and simultaneously minimize the data misfits. Using our optimization method, the resulting models converge towards Pareto fronts, which represent the sets of best compromise model solutions for the defined objectives. We test our new method on a producing reservoir offshore Western Australia. The results of our study indicate that improved reservoir models can be obtained using our method, compared to current geostatistical modeling methods.

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