Pre-conditioned time domain elastic medium multi-parameter full-waveform inversion method

Abstract

The invention discloses a pre-conditioned time domain elastic medium multi-parameter full-waveform inversion method, which comprises the following steps of: S1, selecting a plurality of scale frequency groups to pre-process observation data and seismic wavelets; S2, calculating target seismic source wavelet and a plurality of parameter initial models through staggered grid finite difference forward modeling to obtain a simulated observation record, and acquiring a wave field residual error by subtracting an observation record under each scale from the simulated observation record under the corresponding scale; S3, solving a conjugate operator of a positive operator through adopting an adjoint state method, and acquiring a residual wave field through utilizing the wave field residual error;S4, calculating parameter gradients of a parameter initial model through using the residual wave field and the simulated observation record, and preprocessing all the parameter gradients; S5, optimizing the initial iteration step length through employing a parabola fitting method; and S6, updating a formula and all parameter models through adopting an LBFGS method model to obtain a multi-parameter inversion result. According to the pre-conditioned time domain elastic medium multi-parameter full-waveform inversion method, the efficiency, effect and stability of multi-parameter full-waveform inversion are effectively improved.

Description

technical field [0001] The invention relates to the field of oil and gas geophysical prospecting engineering, in particular to a preconditioned time domain elastic medium multi-parameter full waveform inversion method. Background technique [0002] At present, the focus of oil and gas exploration is shifting from structural exploration to lithological exploration. Compared with traditional migration imaging methods, multi-parameter elastic wave full waveform inversion can provide more accurate compressional and shear wave velocities, as well as better Abundant elastic parameters and other information are beneficial to seismic data interpretation and oil and gas development. [0003] Since the full waveform inversion theory is based on data fitting and relies heavily on the initial model, a low-precision model will cause the method to not converge. At the same time, due to the limitations of seismic data acquisition technology and other aspects, the lack of low-frequency inf...

AI Technical Summary

Problems solved by technology

[0003] Since the full waveform inversion theory is based on data fitting and relies heavily on the initial model, the low-precision model will cause the method to not converge

At the same time, due to the limitations of seismic data acquisition technology and other aspects, the lack of low-frequency information in actual data will make it difficult for gradient-guided full-waveform inversion methods based on numerical fitting to converge to the global minimum. The calculation of the inversion method is huge, which leads to the high calculation cost of the method

Images