Seismic inversion method based on hybrid high order and fractional order Anisotropic Total p-variation (ATpV) sparse regularization

Abstract

The invention discloses a seismic inversion method based on hybrid high order and fractional order Anisotropic Total p-variation (ATpV) sparse regularization, belongs to the field of geophysical inversion and oil and gas reservoir forecasting, and solves the problems caused by existing calculation of a total variation by adopting a first-order difference. The seismic inversion method comprises thefollowing steps: preprocessing a seismic record, extracting horizon position, and then acquiring an initial model of a parameter to be inversed according to well-logging data after the horizon position is extracted; calculating an initial wave impedance logarithm based on the initial model of the parameter to be inversed and the preprocessed seismic record, and then building an inversion model based on the hybrid high order and fractional order ATpV sparse regularization; updating the initial wave impedance logarithm based on the seismic record and a seismic wavelet by combining an alternating direction multiplier method and a forward model to obtain an updated wave impedance logarithm and a parameter for updating a next wave impedance logarithm; and determining whether a not updated value and an updated value meet conditions, if YES, updating the next wave impedance logarithm, and if NO, acquiring the parameter to be inversed. The method is used for seismic inversion.

Description

technical field [0001] A seismic inversion method based on hybrid high-order fractional ATpV sparse regularization is used for seismic inversion and belongs to the field of geophysical inversion and oil and gas reservoir prediction. Background technique [0002] Seismic inversion is an important means of predicting oil and gas reservoirs. It is a process of establishing a forward modeling model based on the mathematical relationship between the detected seismic records and the physical quantities to be inverted, and using the optimization method to solve the forward modeling model. . Seismic inversion technology based on sparse regularization is an important method of seismic inversion. It introduces the sparse regularization constraint into the forward model, exploits the sparse information, and successfully improves the resolution and robustness of the inversion results. [0003] The seismic inversion method based on ATpV sparse regularization is an important method of s...

AI Technical Summary

Problems solved by technology

[0004] In view of the problems of the above research, the purpose of the present invention is to provide a seismic inversion method based on mixed high-order fractional ATpV sparse regularization, which solves the problem of using first-order difference to find total variation in the prior art, which leads to the step effect of the inversion result Serious, resulting in reduced resolution and poor robustness

Images