Shale reservoir inversion model establishment method based on structural deformation

Abstract

The invention discloses a shale reservoir inversion model establishment method based on structural deformation. The method comprises the following steps of: 1) performing fine seismic target horizon interpretation on a shale reservoir in a depth domain to obtain corresponding reservoir burial depth, dip angle and seismic curvature; 2) according to multi-well data, obtaining the relationship between the velocity variation of the vertical well longitudinal wave logging velocity or core velocity test data and the reservoir burial depth, the dip angle and the seismic curvature; 3) obtaining the seismic wave velocity after structural deformation deweighting; 4) calculating a construction trend surface; and 5) obtaining a seismic inversion attribute model, wherein an inversion velocity model is established based on a reservoir velocity trend surface by taking actual well data as input. According to the invention, the inversion precision is effectively improved by establishing the inversion initial parameter model close to the actual geologic model.

Description

technical field [0001] The invention relates to shale exploration technology, in particular to a method for establishing a shale reservoir inversion model based on structural deformation. Background technique [0002] Seismic pre-stack inversion of shale reservoirs is an important part of the prediction of formation pressure, rock mechanics and other gas reservoir sweet spots, and the initial inversion model has a great influence on the inversion attribute results. Therefore, it should be as close as possible to the actual geological model The inversion initial parameter model to improve the inversion accuracy. [0003] At present, the establishment of seismic pre-stack inversion models of shale gas reservoirs adopts the same method as that of conventional reservoirs, and no method specific to the geological characteristics of shale reservoirs has yet appeared. In conventional modeling methods, data such as seismic, drilling and logging, and geological structures are compre...

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Problems solved by technology

In conventional modeling methods, data such as seismic, drilling and logging, and geological structures are comprehensively used to interpolate spatially. These interpolation methods only consider spatial distribution factors. In regions with complex structures, the spatial distribution of model attributes is unreasonable. , does not conform to the geological law

Among them, the stochastic simulation method has high precision. According to the stochastic function theory, the known reservoir data is used to establish a probability distribution model such as spatial wave impedance. By controlling the spatial variation function and the relevant radius, the disadvantage is that abundant drilling and logging data are required. , and the variation parameter is not easy to choose

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