Improving the accuracy of geological model by using seismic forward and inverse techniques

Abstract

Abstract: Sequential Gaussian simulation method is taken as an example to analyze the characteristics and defects of stochastic simulation methods, and a modeling strategy is proposed that is based on the results of seismic inversion to improve modeling accuracy. Stochastic simulation can only achieve “mathematical reality” by recovery of parameter's macro statistical regularity through examples, and seismic forward model can verify whether the simulation results deviate from the “geological reality”. Seismic forward modeling can verify the reliability of the geological model, and the results of geological modeling constrained by seismic inversion can improve the accuracy of the model to achieve the “geological reality”. For braided river delta, a modeling strategy constrained by seismic inversion results in the condition of “multi-levels” and “multi-conditions” is put forward. For lithofacies modeling, division of lithofacies in single well acts as the first variable; in the stage of exploration and development, lithology probability and lithology body act as the second variable respectively, and then establish facies models. For property modeling, take lithofacies model and the seismic impedance as the first variable and the second variable respectively to create property model, in the condition of horizontal and vertical impedance constraints. The proposed modeling strategy maintains the statistical regularities of input data, keep a better consistency with seismic data, and match with dynamic field production. Key words: stochastic simulation, variogram, seismic forward, seismic inversion, facies-controlled modeling, seismic constraint, constraint modeling