多属性分析技术在碳酸盐岩断溶体预测中的应用

Fault-karst carbonate reservoir prediction with comprehensive multi-attribute analysis

随着勘探程度的提高,油田对断层识别的精度要求越来越高,小断层的识别以及缝洞的连通性是精细构造解释的难点。利用GeoEast系统构造导向滤波提高资料信噪比,利用相干、曲率以及纹理等几何类属性精细刻画工区断裂系统及预测缝洞发育,利用多属性融合技术预测断溶体的连通性,利用油气检测技术进行储层预测,为油田的勘探开发提供有力依据。

With the oilfield exploration development,minor fault and karst cave identification is one of difficulties in the seismic interpretation.To solve the problem we use some tools provided by GeoEast.We improve signal-to-noise ratio(SNR)with structure-guided filtering,describe fault systems with multiattributes such as coherence,curvature,and texture,and predict fault-karst connectivity with multi-attribute fusion.Our hydrocarbon detection and carbonate reservoir prediction provide a favorable basis for the oilfield future exploration and development.