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Low-noise least square reverse time migration method

A least squares, reverse time migration technology, applied in the fields of exploration geophysics and inversion synthesis, which can solve problems affecting iterative convergence speed and imaging results, etc.

Pending Publication Date: 2022-07-01
CHINA UNIV OF PETROLEUM (BEIJING)
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Problems solved by technology

[0003] The purpose of the present invention is to provide a low-noise least squares reverse time migration method to solve the problem that the above-mentioned noise will affect the convergence speed and imaging results of iterations in the iterative process of least squares reverse time migration

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Embodiment 1

[0059] Embodiment 1 provides a low-noise least squares reverse time migration method, comprising the following steps:

[0060] First, establish the function F(m) of the least squares inverse time offset, and its expression is:

[0061]

[0062] In the formula, F(m) is the function of least squares inverse time migration; m represents the reflection coefficient model, which is a matrix; d and d obs represent the predicted and observed data, respectively.

[0063] Among them, the observation data d obs The forward model is obtained by solving the two-way wave equation for the true velocity model, and the predicted data d is obtained by applying the Kerchhoff approximation forward model to the migration velocity model and the reflection coefficient model m, such as figure 1 and 2 shown.

[0064] Then, by adding a sparse constraint term R(m) to the function F(m) of the least squares inverse time migration, the side lobes caused by the limited frequency band of the data and ...

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Abstract

The invention discloses a low-noise least square reverse time migration method. The method comprises the following steps: establishing a least square reverse time migration function; a sparse constraint term is added to a least square reverse time migration function to suppress noise, and a target function is obtained after sparse constraint of the Cauchy constraint term; and determining parameters of an objective function of the least square reverse time migration function after sparse constraint of the Cauchy constraint term, optimizing the gradient of the objective function, and performing minimization solution on the least square reverse time migration function by adopting a precondition nonlinear conjugate gradient method. According to the low-noise least square reverse time migration method disclosed by the invention, a new method for determining regularization parameters and hyper-parameters in Cauchy terms is provided, a better imaging result can be obtained, the convergence speed of inversion can be increased, and a method for determining step length is provided for an objective function containing Cauchy constraint terms.

Description

technical field [0001] The invention relates to the comprehensive technical field of exploration geophysics and inversion, in particular to a low-noise least squares reverse time migration method. Background technique [0002] Migration imaging technology is a key technology in seismic data processing. It images subsurface structures by restoring seismic reflection events received at the surface to their true locations underground. High-resolution migration imaging results can help geological interpreters to effectively find underground oil and gas reservoirs. Therefore, in order to obtain high-resolution subsurface imaging results, migration techniques were first developed from ray tracing-based Kirchhoff migration to Gaussian beam migration, and then from one-way wave migration based on the one-way wave equation to two-way-based migration. Reverse time migration of the wave wave equation. Currently, reverse time migration is one of the most popular migration techniques ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/28G06F17/15
CPCG01V1/28G01V1/282G06F17/15
Inventor 吴迪姚刚吴博
Owner CHINA UNIV OF PETROLEUM (BEIJING)
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