L-BFGS initial matrix solving method applied to least square reverse time migration
A technology of L-BFGS and least squares, which is applied in the field of seismic exploration migration imaging, can solve problems such as accelerated convergence speed, insufficient geometric diffusion compensation, and unbalanced illumination, and achieves improved imaging accuracy, uniform underground illumination, and accurate correction factors Effect
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[0039] The present invention adopts the L-BFGS algorithm of optimizing the initial matrix to realize the least squares reverse time migration, and the specific process is as follows figure 2 shown. The present invention adopts the Marmousi model to describe the specific implementation. The Marmousi model is one of the commonly used standard models in the field of seismic exploration, and it is often used to test the feasibility and accuracy of algorithms under complex media conditions. In order to improve the calculation efficiency, under the premise of ensuring the complexity of the model, the original Marmousi model is thinned out. The Marmousi true velocity model after thinning is as follows image 3 As shown, Gaussian smoothing can be performed on it to obtain the thinned Marmousi background velocity model (such as Figure 4 shown), the theoretical reflection coefficient model can be obtained from the real velocity model and the background velocity model (the Marmousi ...
specific Embodiment approach
[0041] (1) Based on the thinned-out Marmousi velocity model, the seismic data collection is carried out in a full-array observation mode. There are 116 shots in total, 576 traces are received for each shot, the shot interval is 40m, and the trace interval is 8m. The shot points and receiver points are at Surface, with a depth of 0m. The least squares reverse time migration imaging is performed based on the velocity model and the acquired seismic data.
[0042] (2) In the kth iterative calculation of the least squares reverse time migration, k>=1, based on the background velocity model v obtained after velocity model smoothing 0 , taking the source wavelet w as the disturbance, according to formula (1), we can get the timing wave field P 0 .
[0043]
[0044] In formula (1), v 0 is the background velocity model, t is time, x and z are space coordinates respectively, P 0 is the simulated positive wave field, w is the source wavelet;
[0045] (3) Based on the positive wav...
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