MA Jin-ping, FAN Hong-yao, SANG Shu-yun, WANG Qing-zhen, SHI Rui-qi. Complicated Fault Identification Study and Application[J]. CT Theory and Applications, 2018, 27(1): 27-34. DOI: 10.15953/j.1004-4140.2018.27.01.04
Citation:
MA Jin-ping, FAN Hong-yao, SANG Shu-yun, WANG Qing-zhen, SHI Rui-qi. Complicated Fault Identification Study and Application[J]. CT Theory and Applications, 2018, 27(1): 27-34. DOI: 10.15953/j.1004-4140.2018.27.01.04
MA Jin-ping, FAN Hong-yao, SANG Shu-yun, WANG Qing-zhen, SHI Rui-qi. Complicated Fault Identification Study and Application[J]. CT Theory and Applications, 2018, 27(1): 27-34. DOI: 10.15953/j.1004-4140.2018.27.01.04
Citation:
MA Jin-ping, FAN Hong-yao, SANG Shu-yun, WANG Qing-zhen, SHI Rui-qi. Complicated Fault Identification Study and Application[J]. CT Theory and Applications, 2018, 27(1): 27-34. DOI: 10.15953/j.1004-4140.2018.27.01.04
Now more and more traps are faulted trap, so the fault recognition is very important. By project study we think that:1).The combine of coherence and sup retrace technique can make big faults more clear. 2).The attribute fusion of different curvature attributes can improve small faults identification. 3).The gradient vector technique can make fault image clearer. 4).This technique already has very good application in study area. 5. This technique can be applied in other similar area.