Optimization and application of discontinuity detection in multi-frequency domain in ant-tracking

Abstract

The application of ant-tracking in seismic interpretation shows its advantages in fault characterization.However, this technology is limited by the quality of seismic data, the selection of ant-tracking input data, and multi-solution caused by single attribute.Thus, how to improve the accuracy of ant-tracking has been the hot issue and hard nut to crack in the industry.This paper takes well-block 1 in Shunbei area of Tarim Basin as the research object, and analyses the differences and application potential of chaos, variance, and the maximum positive curvature theories in fault detection.Besides, based on generalized S transform spectral decomposition, we compare discontinuity detection effects of chaos, variance and the maximum positive curvature attributes in different frequencies.Next, the data is processed after discontinuity detection with ant-tracking and optimize the best date for each frequency.Finally, RGB fusion is carried out after occurrence control.Results show that chaos in low frequency, variance in medium frequency and the maximum positive curvature in high frequency respond well with big, medium and small faults.The ant-tracking aided with multi-frequency domain and different fault detections can display multi-scale fracture distribution and enrich the underground geological information.

Keywords

• seismic exploration
• multi-scale fault detection
• optimized ant-tracking
• discontinuity detection
• spectral decomposition