Crack Detection Method Based on Hessian Matrix for Seismic Coherent Data
A coherent data and detection method technology, applied in the field of seismic exploration, can solve problems such as incomplete morphological features, inaccurate crack detection, and noise interference, and achieve the effects of automation, good continuity, and noise suppression
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Embodiment 1
[0077] The Hessian matrix-based seismic coherent data crack detection method provided by the preferred embodiment of the present invention, such as figure 1 shown, including the following steps:
[0078] Step 1: For the seismic coherent data with extremely low signal-to-noise ratio, poor continuity of fractures and incomplete morphological features, anisotropic diffusion filter based on structure tensor is used to denoise and protect the continuity of fractures;
[0079] Step 1.1: Calculate the structure tensor of the input 2D seismic coherent volume slice;
[0080] Step 1.1.1: Calculate the input as figure 2 The structure tensor T of the 2D seismic coherent volume slice shown,
[0081]
[0082] Among them, I x , I y represent the first-order partial derivatives of the slice along the x direction and the y direction respectively, F represents a Gaussian kernel function, and the variance of the Gaussian kernel function is 10;
[0083] Step 1.2: Anisotropic diffusion fi...
Embodiment 2
[0114] The Hessian matrix-based seismic coherent data crack detection method provided in this embodiment includes the following steps:
[0115] Step 1: For the seismic coherent data with extremely low signal-to-noise ratio, poor continuity of fractures and incomplete morphological features, anisotropic diffusion filter based on structure tensor is used to denoise and protect the continuity of fractures;
[0116] Step 1.1: Calculate the structure tensor of the input seismic 3D coherent data;
[0117] Step 1.1.1: Calculate the structure tensor T of the input seismic 3D coherent data,
[0118]
[0119] Among them, I x , I y represent the first-order partial derivatives of the slice along the x direction and the y direction respectively, F represents a Gaussian kernel function, and the variance of the Gaussian kernel function is 10;
[0120] Step 1.2: Anisotropic diffusion filtering is obtained according to the heat conduction equation;
[0121] Step 1.2.1: Calculate the he...
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