A Study Of Automatic Identification Of The3D Fault Based On Seismic Data

Fault interpretation is an important part of the seismic data interpretation. Mostcommercial software only provides human-computer interaction to explain the data. A studyof automatic identification of the3D fault based on seismic data is a research that hastheoretical and practical value.Seismic data often contain various noise and singular values that effect Datavisualization and not conducive to fault identification. This paper analyzed the features of theseismic singular values, giving a Culling algorithm of the singular values. The paper usedEdge preserving filtering and Anisotropic Diffusion tensor filtering algorithm to filter outnoise in3D seismic data and achieved a good result.The connection relationship between the fault pillars should be given in faultinterpretation. In this paper, the principle of minimum spanning tree was used to realize theautomatic connection of fault pillars. The paper has researched the algorithm of the fault planegeneration and gave a special Smooth algorithm.Coherence is the core technology in the fault interpretation, this paper focus on the threegeneration coherence algorithm and put forward an algorithm based on the feature structureof angle scanning. It summarized the advantage of C2and C3coherence algorithm, improvedthe quality of coherent computation and the robust to noise. Algorithm in the application ofthe fast computing technology improved the efficiency of coherent computation.The paper introduced the basic principle of ant colony algorithm and researched theproblems in automatic tracking and identification in fault. Then, it discussed the parametersetting and algorithm step. Finally, using the block direction restrained the ants’ search pathsto improve the tracking quality and enhanced the stability of the algorithm.The paper studied the adaptive combination technology of fault plane, proposed amethod of fault plane combination based on Curve similarity and achieved a good result.