Earthquake Fault Identification Method And Its Application

The faults is the main factor that controls the formation and distribution of oil and gasfields, and it is the most important task to identify the morphology and distribution of faults inoil and gas exploration. Traditional method of fault interpretation is influenced by subjectivefactors, so that the reliability and accuracy is not high, and the efficiency of the work is low.With the continuous of improvement, the method of fault description makes it possible toidentify faults automatically. According to the main problems existing in the fault automaticidentification technology, this study proposed an improved ant colony algorithm for fault lineautomatic tracking.The main content is divided into three parts:The first part introduced three generations coherency cube algorithm, GST coherencycube algorithm and variance data cube algorithm, then adopted the improved third generationcoherency cube as fault attributes cube of fault automatic identification, providing a basis forthe later track of faults.The second part focuses on the improved ant colony algorithm based on images.Considering certain convergences of the fault identification and image edge detection, thispaper proposed the application principle and the realization process of ant colony algorithm inthe edge detection of the noise image, By improving the algorithm, and realized theapplication of ant colony algorithm to extract the fault line. Through the instance parameter inthe algorithm is discussed, verified the effectiveness of the proposed algorithm.The third part introduced the optimization method of fault line, including the dilation,erosion, corrosion, opening operation and closing operation of mathematical morphology,also the graph thinning technology of image processing. The study optimizd the fault line ofthe ant tracking results through using the appropriate structural elements according to thetracking result, and could get binary used to extract fault.Through processing the actual oilfield data, verified the effectiveness of the methodthrough discussing the tracking strategy according to the track of horizontal slice and vertical slice.