A seismic prediction method for gravity-induced geostress parameters in TTI media

By establishing a computational model in TTI medium and utilizing Fourier coefficient data inversion technology, the problem that traditional methods cannot accurately predict the geostress parameters of inclined fractured reservoirs has been solved, achieving accurate parameter prediction and guiding fracturing development.

CN117784217BActive Publication Date: 2026-05-26UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Patent Information

Application Number
CN202311826815.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-12-27
Publication Date
2026-05-26
Estimated Expiration
2043-12-27

AI Technical Summary

Technical Problem

Existing technologies are insufficient to effectively predict the geostress parameters of unconventional reservoirs containing inclined fractures. Traditional methods assume a horizontally isotropic medium, which cannot accurately characterize the stress conditions of inclined fracture groups.

Method used

The seismic prediction method based on gravity-induced geostress parameters of TTI medium is adopted. By establishing a calculation model, using Fourier coefficient data and Bayesian inversion technology, combined with generalized Hooke's law and linear slip theory, equations for P-wave and S-wave modulus, density, crack density and tilt crack parameters are derived, thus realizing parameter inversion and prediction.

Benefits of technology

It provides stable and reliable prediction results of TTI medium in-situ stress parameters, guiding the fracturing development of unconventional reservoirs and improving the accuracy and reliability of predictions.

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Abstract

This invention discloses a seismic prediction method for gravity-induced geostress parameters in TTI media. The specific process includes: Step 1, establishing calculation models for the minimum and maximum horizontal stresses and DHSR of the TTI media; Step 2, performing discrete Fourier transform on partially stacked seismic data from different azimuths to obtain zero-order and second-order Fourier coefficient data volumes; Step 3, predicting TTI media model parameters: performing Bayesian Fourier coefficient inversion to predict P-wave and S-wave moduli, densities, fracture densities, and dip fracture parameters; and calculating fracture dip angles; Step 4, calculating TTI media geostress parameters: substituting the predicted TTI media model parameters into the calculation model established in Step 1 to calculate the minimum and maximum horizontal stresses and DHSR of the TTI media. This invention can provide stable and reliable prediction results for TTI media geostress parameters, which helps guide fracturing development operations in unconventional reservoirs.
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