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基于优势方位RGB融合的低序级断层识别技术
Low-Order Faults Recognition Technology Based on Dominant Azimuth RGB Fusion

DOI: 10.12677/ag.2025.156084, PP. 881-888

Keywords: OVT数据,RGB融合,低序级断层识别
OVT Data
, RGB Fusion, Low-Order Faults Recognition

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Abstract:

低序级断层的识别对于发现剩余油有利富集区、提高油气采收率具有重要的研究意义,渤南地区北部断裂系统发育,常规叠后资料上低序级断层的反射特征不明显,识别精度低,制约着该区域的勘探开发。针对以上问题,文章基于五维地震数据,划分优势偏移距和方位扇区,结合现有地质认识,优选断层法向方位,并通过RGB属性融合技术,有效提高了低序级断层的识别精度,明晰了断层展布特征,为研究区的构造精细描述和滚动开发提供了技术支撑。
The identification of low-order faults is of significant research importance for discovering favorable accumulation areas of remaining oil and improving oil and gas recovery rates. In the northern part of the Bonan region, a fault system is well developed, but the reflection characteristics of low-order faults in conventional post-stack data are not obvious, resulting in low identification accuracy, which restricts exploration and development in this area. To address these issues, this paper focuses on five-dimensional seismic data, categorizes dominant offset distances and azimuth sectors, and combines existing geological knowledge to optimize the fault-normal azimuth. By employing RGB attribute fusion technology, the identification accuracy of low-order faults has been effectively improved, clarifying the fault distribution characteristics and providing technical support for the fine structural description and rolling development of the research area.

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