Shale reservoir fracture and brittleness prediction method based on Bayesian inversion and system thereof

Abstract

The invention provides a shale reservoir fracture and brittleness prediction method based on Bayesian inversion. The method comprises the steps that azimuth part angle superposition seismic data, azimuth seismic wavelets and a model parameter low-frequency model are acquired; a prediction result is obtained according to the obtained azimuth part angle superposition seismic data, azimuth seismic wavelets, a model parameter low-frequency model and a preset shale reservoir fracture and brittleness prediction model; an establishment process of the shale reservoir fracture and brittleness prediction model comprises the following steps: deducing an HTI medium longitudinal wave azimuth reflection coefficient approximate equation containing a new brittleness indication factor and fracture density; and a shale reservoir fracture and brittleness prediction model can be established according to the relationship and a Bayesian AVAZ inversion method. According to the method, accumulative errors in the parameter indirect conversion process are effectively avoided, and the shale reservoir fracture and brittleness prediction precision is improved.

Description

technical field [0001] The present disclosure belongs to the technical field of shale reservoir inversion prediction, and in particular relates to a method and system for predicting fractures and brittleness of shale reservoirs based on Bayesian inversion. Background technique [0002] Shale reservoirs have the characteristics of low porosity, ultra-low permeability and tightness, and require fracturing to form a complex fracture network in order to obtain commercial production capacity. Fractability is defined as the property that shale reservoirs can be effectively fractured to obtain stimulation ability. The main factors affecting fractability include shale brittleness and natural fractures. Generally, the more natural fractures are developed in the reservoir, the better the brittleness, and the better the fractability. The brittleness index of shale is generally expressed by the brittleness index. The brittleness evaluation methods mainly include the mineral composition...

AI Technical Summary

Problems solved by technology

[0004] 1. Due to the influence of factors such as organic carbon content, porosity and fluid in shale reservoirs, in some cases Young's modulus is not enough to characterize shale brittleness

In addition, the elastic parameters (compressional and shear wave velocities and densities) obtained by traditional methods are indirectly converted into brittleness indicator factors, so cumulative errors are unavoidable;

[0005] 2. The traditional method indicates the development of fractures by inverting the anisotropy parameters. The anisotropy parameters are easily affected by fluids and cannot better indicate the development of fractures in the reservoir.

Images