Geostatistical Bayesian Inersion - A Case History in a Complex Reservoir

By huge consumption of the hydrocarbon source energy, exploration of the remained reservoir is getting more expensive and may have complexity in structure or stratification. In this techniques which bring us more information about reservoir properties in higher resolution and provides contained error in estimation are valuable. In this paper a Geostatistical Bayesian Inversion with maximum posteriori is introduced, which build prior model distribution from background knowledge and by using forward seismic modeling calculate likelihood function of model parameters. Maximum posterior estimation, estimates the model parameters,here acoustic impedance of P-wave and total Porosity, and finally results are compared with model based inversion for acoustic impedance and kriged total porosity in one of complex reservoirs in Mid-East.