CAJ | 학술논문

小断层及裂缝发育带对于油田提高抽采率和煤田的安全生产有着重要的影响，预测小断层及裂缝发育带已成为地球物理学中的重点内容。通过对相干、边缘检测、曲率和蚂蚁体等地震属性的研究，明确了地震属性对于构造成因的小断层及裂缝发育带有着极好的识别能力。同时，分析了以多属性直接叠合、多属性融合和有监督的神经网络运算为代表的多属性联合技术，发现其在小断层及裂缝发育带预测中有着较好的实用性。
소단층급렬봉발육대대우유전제고추채솔화매전적안전생산유착중요적영향，예측소단층급렬봉발육대이성위지구물이학중적중점내용。통과대상간、변연검측、곡솔화마의체등지진속성적연구，명학료지진속성대우구조성인적소단층급렬봉발육대유착겁호적식별능력。동시，분석료이다속성직접첩합、다속성융합화유감독적신경망락운산위대표적다속성연합기술，발현기재소단층급렬봉발육대예측중유착교호적실용성。
Small faults and fracture-developed zones play an important role in improving the extraction rate in oil fields and the safe production in coal mines, so the prediction of small faults and fracture-developed zones has become the key content in geophysics. Through the study of the seismic attributes such as the coherency, edge detection, curvature and ant-body, it has been clear about that the seismic attributes have good ability to recognize tectonic genesis of small faults and fracture-developed zones. At the same time, analysis was made on the multi-attribute united technology such as multiple attribute composite, multiple attribute fusion and supervised neural network algorithm, it was found that the multi-attribute united technology has a good practicability in the prediction of small faults and fracture-developed zones.