An improved ant-tracking workflow based on divided-frequency data for fracture detection. (17th October 2022)

• Record Type: Journal Article
• Authors: Xie, Qinghui; Zhao, Chunduan; Rui, Zhifeng; Guan, Shoujun; Zheng, Wenting; Fan, Hongche
• Is Part Of: Journal of geophysics and engineering. Volume 19:Number 5(2022)
• Page Start: 1149
• Page End: 1162
• Publication Date: 2022-10-17
• Subjects: ant-tracking -- divided-frequency -- auto extraction -- variance -- structure-guided; Geophysics -- Periodicals; Prospecting -- Geophysical methods -- Periodicals; Engineering -- Periodicals; 622.1505
• DOI: 10.1093/jge/gxac075
• Languages: English
• ISSNs: 1742-2132

Abstract

Abstract: The conventional ant-tracking technique often results in weak transverse continuity or unobvious plane fracture patterns. It also has limited ability to identify small-scale natural fractures. To improve the image quality of fractures, a spectrum decomposition technique has been used in ant-tracking. Although it has achieved good results, it also brings a high workload and judgment difficulty. To solve these issues, we proposed an improved ant-tracking workflow based on frequency filtering to improve the accuracy of fracture detection, in which the tracking was performed on low-, medium- and high-frequency cubes. The workflow was applied in the H area of the Sichuan Basin with good results: (i) more continuous, sharper and more small-scale fractures were detected by the proposed workflow than the ones with the full-band seismic data. (ii) Compared to the ant-tracking methods based on a series of single-frequency data cubes, this not only requires less computation time, but is also easier to distinguish the differences between the three divided-frequency cubes. (iii) Comparing the ant-tracking effect, the results of medium- and high- frequency cubes are much better than the low- frequency. (iv) Compared with the traditional methods, the time of automatic fracture extraction is obviously shortened. This provided a solid data foundation for subsequent reservoir production prediction and well deployment.