Thin reservoir seismic prediction method based on high resolution sequence constraint
The Tarim oilfield has a large depth of clastic reservoirs with good physical properties and large hydrocarbon resources,but faces the difficulties of frequent interactive development of sandstone and mudstone,rapid lateral change of lithology,and thin thickness of a single reservoir.Conventional seismic inversion technology is difficult to meet the demand of deep thin reservoir prediction due to the low accuracy of low-frequency initial model and weak lateral constraints.In this paper,based on the Bayesian inversion theory and INPEFA(Integrated Prediction Error Filter Analysis)layer order division theory,a high resolution layer order constrained post-stack Bayesian inversion method is proposed.The method firstly establishes a high-resolution layer sequence grid on the wells by INPEFA technology,and establishes a high-accuracy low-frequency initial model by combining with the sequential Gaussian simulation method,and at the same time introduces lateral constraints operator in the seismic inversion by utilizing the proximity of the neighboring traces under the constraints of the high-resolution layer sequences,so that the inversion results of high-resolution and high-stability can be obtained in the end.The application of this method for deep clastic reservoir prediction in the Lungu area effectively improves the imaging accuracy of thin reservoirs,and the longitudinal results can identify 3 m thin reservoirs,while accurately portraying the transverse changes of the sand body,which solves the difficult problem of predicting the thin reservoirs of deep clastic rocks in the area,and provides a strong support for the further exploration and deployment in the study area.
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