Xinjiang Petroleum Geology ›› 2026, Vol. 47 ›› Issue (4): 506-514.doi: 10.7657/XJPG20260415

• APPLICATION OF TECHNOLOGY • Previous Articles     Next Articles

A 3D Quantitative Characterization Method for Fragmentation Degree of Deep Fault- Controlled Reservoirs: A Case Study of the Yijianfang-Yingshan Formation in the Shunbei Area

XIA Yang1(), XIANG Jian1(), JIN Yan1, CHEN Xiuping2, ZHAO Zhen1, HAN Zhengbo1   

  1. 1 College of Petroleum Engineering, China University of Petroleum (Beijing), Beijing 102249, China
    2 Research Institute of Petroleum Engineering, Northwest Oilfield Company, Sinopec, Urumqi, Xinjiang 830011, China
  • Received:2025-04-30 Revised:2025-08-10 Accepted:2025-08-29 Online:2026-08-01 Published:2026-07-30

Abstract:

Deep drilling in the Shunbei area is confronted with a complex geological environment where reservoirs are controlled by strike-slip fault zones. In addition, the strata in this area are highly fragmented, posing a significant risk of deep wellbore instability. However, no quantitative method is currently available to characterize the fragmentation degree, leaving the instability mechanism unclear. This paper presents a 3D quantitative method to characterize the degree of fragmentation in deep strata based on seismic data, as demonstrated by a case study of the Ordovician Yijianfang-Yingshan formation in the Shunbei area. First, an index for the degree of rock mass fragmentation was established using acoustic wave dynamics. Second, wave impedance inversion was performed on seismic data that had been processed by Gaussian filtering and normalization. Third, fault identification results from 3D seismic data were transformed into threshold-type weight function to constrain the fragmentation degree index. Finally, 3D seismic imaging technology was integrated with the time-depth relationship, together with well location, inclination, and azimuth data, to achieve spatial matching between the 3D wellbore trajectory and fragmented zones. The fragmentation degree index was then validated through laboratory experiments and individual-well logging data. The proposed method was further validated by comparison with fault identification models including edge detection and ant tracking. The predicted rock-mass fragmentation profile matches the borehole enlargement log with an agreement rate of 89% for actual wells in the Shunbei area. This method provides a reference for predicting the degree of fragmentation in deep strata.

Key words: Shunbei area, Ordovician, fault-controlled reservoir, fragmentation degree, quantitative characterization, seismic data

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