Fault identification by orientation constraint ant colony algorithm
Yan Zhe1,2, Gu Han-ming1, Cai Cheng-guo1, Mu Xing3
1. Institute of Geophysics and Geomatics, China University of Geosciences(Wuhan), Wuhan, Hubei 430074, China;
2. Key Laboratory of Tectonics and Petroleum Resource of Ministry of Education, China University of Geosciences(Wuhan), Wuhan, Hubei 430074 China;
3. Research Institute of Geological Science, Shengli Oilfield Company, Sinopec, Dongying, Shan Dong 257015, China
Abstract：The attribution value at the location of fault generally shows itself as local maximum or minimum.For instance,local minimum indicates the fault in the coherence cube.Furthermore,the fault extension has a certain direction,but noise does not.In this paper,we present a fault automatic tracking and identifying approach named orientation constraint ant colony algorithm(OCACA).We apply the proposed approach in actual coherence cube.Automatic tracking results with different parameters show the influence of the parameters.The processing results demonstrate that OCACA is an accurate and effective approach for fault automatic tracking and identification.And for noise reduction and fault continuity enhancement,OCACA obtains better performances than Petrel.
