An improved ant-tracking workflow based on divided-frequency data for fracture detection

Author:

Xie Qinghui12,Zhao Chunduan2,Rui Zhifeng3,Guan Shoujun2,Zheng Wenting1,Fan Hongche4

Affiliation:

1. Fujian Provincial Key Laboratory of Advanced Technology and Informatization in Civil Engineering, Fujian University of Technology , Fuzhou, 350118 , People's Republic of China

2. D&I Department, Schlumberger China , Beijing, 100016 , People's Republic of China

3. Beijing Hezhong Jiuding Energy Technology Research Co., Ltd , Beijing, 100023 , People's Republic of China

4. CNPC Beijing Richfit Information Technology Co. , Ltd, Beijing, 100010 , People's Republic of China

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.

Funder

Fujian University of Technology

Publisher

Oxford University Press (OUP)

Subject

Management, Monitoring, Policy and Law,Industrial and Manufacturing Engineering,Geology,Geophysics

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