Multi-point geostatistical pre-stack inversion method based on constant update probability ratio theory

Abstract

The present invention discloses a multi-point geostatistical pre-stack inversion method based on the constant update probability ratio theory, which includes the following steps: collating data, gridding and allocating well data, assigning initial attribute values ​​to the simulated work area, and selecting data of appropriate size Modeling, inversion and judgment iteration terminate; it overcomes the increasing difficulty of oil and gas exploration and development in the existing technology, the degree of exploration is getting higher and higher, it is becoming more and more difficult to find new oil and gas reservoirs, and the inaccurate reservoir parameters are obtained , the disadvantage of increasing the uncertainty of exploration has the advantage of using multi-point geostatistics method to obtain prior information, and then screening through the minimum objective function, which reduces the complexity of seismic inversion.

Description

technical field [0001] The embodiments of the present disclosure relate to the technical field of oil and gas exploration and development, more specifically, a multi-point geostatistical pre-stack inversion method based on the constant update probability ratio theory. Background technique [0002] Nowadays, oil and gas exploration and development are becoming more and more difficult, the degree of exploration is getting higher and higher, and it is becoming more and more difficult to find new oil and gas reservoirs. This requires accurate reservoir parameters to reduce the uncertainty of exploration. [0003] Seismic stochastic inversion is under the constraints of seismic data, fused with logging data, which can broaden the frequency spectrum of inversion results, improve resolution, and search for thinner and smaller reservoirs all at once. Hass and Dubrule (1994) first proposed the prototype of stochastic inversion, combining sequential Gaussian simulation method with sei...

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Problems solved by technology

[0004] The seismic random inversion method has gradually matured in the past two decades of research, but there are still many defects, such as low computational efficiency and poor lateral continuity. Therefore, more in-depth research on the random inversion method is still needed , so as to better predict the reservoir and improve the accuracy of exploration and development

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