Angle domain least square reflectivity inversion method based on coherent superposition

Abstract

The invention discloses an angle domain least square reflectivity inversion method based on coherent superposition, which relates to the technical field of exploration geophysics, and comprises the following steps of: parameterizing and linearizing a wave equation by using an angle domain reflection coefficient as a reflectivity model, and constructing a linear positive operator based on Bern approximation; then, calculating the gradient of linear inversion by using an adjoint state method; and finally, updating the reflectivity model in an angle domain by using a precondition conjugate gradient method; and carrying out automatic event tracking on the reflection axis on the inverted angle domain reflectivity gather, and then carrying out coherent superposition along the tracked event to obtain a final superposition imaging result. The method has the beneficial effects that the problem of offset illusion caused by speed errors is avoided, and a deep high-quality imaging result is obtained; the sensitivity of the least square migration to the speed error is reduced, the deep-ultra deep oil gas target can be accurately imaged, and finally the practical process of the least square migration in deep oil gas exploration is promoted.

Description

technical field [0001] The invention relates to the technical field of exploration geophysics, in particular to an angle-domain least-squares reflectivity inversion method based on coherent superposition. Background technique [0002] Seismic exploration is one of the important means and technologies for deep oil and gas exploration. However, in deep seismic exploration, the velocity modeling error is large, the effective reflection energy is difficult to achieve coherent stacking, and the migration noise is serious, which makes the imaging quality of conventional seismic imaging methods poor in deep high-steep structures, complex fault blocks, and dissolution vugs. No imaging. The least square reflectivity inversion is based on the linear inversion framework, and through data fitting, the deep imaging resolution and amplitude balance can be greatly improved. However, in practical applications, the biggest problem of least squares reflectivity inversion is that it is too s...

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Problems solved by technology

[0005] In order to solve the technical problem that the conventional least squares migration method is too sensitive to the migration velocity error, a large amount of incoherent superposition noise makes the imaging accuracy of deep complex structures low, the present invention discloses an angle-domain least squares reflection based on coherent superposition rate inversion method

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