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3D large residual static corrections based on first breaks in CMP gather

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The near-surface of the Earth is highly irregular in western china which leads to severe statics problem. The tomography static correction can solve the long wavelength component statics well, but the short wavelength statics is not well solved. Due to the large value of residual statics, high resolution imaging is difficult. Aiming at solving the problem of large residual statics in complex areas, a novel approach based on first breaks in common-midpoint (CMP) gather is proposed in this paper. First, apply datum statics to the picked first breaks, and then fit the picked first breaks to calculate the residual trace time shifts in CMP gather, which is used to establish the objective function of residual statics. Second, use Gauss-Seidel iterative method to decompose the residual trace time shifts into shot and receiver’s residual statics. Taking an example in complex areas in Western China, real data processing shows that the serious problem of large residual statics is well solved and the imaging quality is improved significantly.
Title: 3D large residual static corrections based on first breaks in CMP gather
Description:
The near-surface of the Earth is highly irregular in western china which leads to severe statics problem.
The tomography static correction can solve the long wavelength component statics well, but the short wavelength statics is not well solved.
Due to the large value of residual statics, high resolution imaging is difficult.
Aiming at solving the problem of large residual statics in complex areas, a novel approach based on first breaks in common-midpoint (CMP) gather is proposed in this paper.
First, apply datum statics to the picked first breaks, and then fit the picked first breaks to calculate the residual trace time shifts in CMP gather, which is used to establish the objective function of residual statics.
Second, use Gauss-Seidel iterative method to decompose the residual trace time shifts into shot and receiver’s residual statics.
Taking an example in complex areas in Western China, real data processing shows that the serious problem of large residual statics is well solved and the imaging quality is improved significantly.

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