Ma Chen, Huang Handong, Tang Youcai, Cheng Suo, Wang Chao, Wang Xin
State Key Laboratory of Petroleum Resources and Prospecting, College of Geophysics, China University of Petroleum, Beijing, China.
Exploration and Development Research Institute, PetroChina Tarim Oilfield Branch, Korla, China.
PLoS One. 2025 Mar 17;20(3):e0311079. doi: 10.1371/journal.pone.0311079. eCollection 2025.
The focus of oil and gas exploration in the Tarim Basin has shifted from interlayers to fracture-controlled karsts. A significant oilfield characterized by strike-slip faults was discovered in the Yueman area. However, identifying such fault zones is challenging because of the complex and chaotic seismic reflection characteristics, as well as the presence of seismic noise and other discontinuities. To improve oilfield production, the accurate identification of strike-slip fault zones in ultradeep tight limestone is a critical issue. The seismic anomalies of such fault zones exhibit diverse characteristics, with the low-velocity zone of the fault causing a "beaded" reflection pattern. Traditional coherent and curvature attribute methods have large errors in identifying strike-slip faults and cannot adequately characterize the contour features of fracture-karst traps. To address these challenges, this study proposed a multi-attribute optimal surface-based fracture identification technology based on forward simulation records. Seismic attributes that were sensitive to different types of strike-slip faults were selected, and multiple attributes were merged to obtain a fracture distribution map using the best surface voting algorithm. This method effectively suppresses noise that is irrelevant to fractures and is sensitive only to fracture information, allowing for the identification of subtle waveform changes caused by strike-slip faults. Thus, the accuracy and continuity of fracture identification were significantly improved.
塔里木盆地油气勘探重点已从层间转移至裂缝控制的岩溶地区。在玉满地区发现了一个以走滑断层为特征的重要油田。然而，由于地震反射特征复杂且混乱，以及存在地震噪声和其他不连续性，识别此类断层带具有挑战性。为提高油田产量，准确识别超深层致密灰岩中的走滑断层带是一个关键问题。此类断层带的地震异常表现出多样特征，断层的低速带会导致“串珠状”反射模式。传统的相干和曲率属性方法在识别走滑断层时误差较大，无法充分表征缝洞型圈闭的轮廓特征。为应对这些挑战，本研究提出了一种基于正演模拟记录的多属性最优曲面裂缝识别技术。选取了对不同类型走滑断层敏感的地震属性，并利用最佳曲面投票算法合并多个属性以获得裂缝分布图。该方法有效抑制了与裂缝无关的噪声，仅对裂缝信息敏感，能够识别走滑断层引起的细微波形变化。因此，显著提高了裂缝识别的准确性和连续性。
