Method for estimating successive difference evolution of medium quality factor

Abstract

The invention provides a method for estimating successive difference evolution of a medium quality factor. The method comprises the steps of 1, preprocessing an actual VSP channel set to remove non-consistency of different wavelets; 2, creating an initial group X containing M units; 3, dividing an underground medium into different stratums according to the distance of two adjacent wave detectors, treating each channel as a sub-component, and defining local adaption function of the k unit through L1 norm so as to obtain the local adaption value of each channel; 4, optimizing and updating each sub-component in the initial group X according to the actual VSP channel and the local adaption of each channel; solving the quality factor and speed to be estimated after variation according to the variation strategy; 5, repeating step 4, updating the whole group, and selecting the optimal unit according to the global adaption value so as to obtain the quality factor and speed of underground medium. The method is fast to calculate, high in convergence, and free of dependence on the initial value.

Description

technical field [0001] The invention relates to the technical field of seismic exploration, in particular to a successive differential evolution estimation method of a medium quality factor. Background technique [0002] With the development of oil and gas exploration technology and the further deepening of oil and gas field exploration, oil and gas exploration has developed from conventional oil and gas reservoirs to unconventional oil and gas reservoirs. Exploration objects are becoming more and more complex, and exploration technology is facing new challenges. How to accurately describe the subsurface structure, lithology and fluid saturation is an important problem to be solved in seismic exploration. When a wave propagates in a subsurface medium, the viscoelasticity of the medium dissipates the energy of the wave gradually. The inherent absorption of this medium is usually characterized by the medium quality factor Q, and the estimated Q value can be used for hydrocarbo...

AI Technical Summary

Problems solved by technology

[0006] The local optimization waveform inversion method has a very strong dependence on the initial value, and it is difficult to select a high-precision initial value, resulting in a decrease in the inversion accuracy. Therefore, it is necessary to study a global optimization waveform inversion method that does not depend on the initial value.

Existing global optimization algorithms have achieved great success when applied to high-dimensional separable model spaces, but for inseparable model spaces spanned by parameters to be estimated in viscoelastic media, global optimization algorithms still need further research

Images