基于常规测井与电成像测井多信息融合的裂缝识别

四川盆地普光气田区的碳酸盐岩储层具有溶蚀孔洞发育、裂缝张开度低、常规测井响应不明显等特征, 直接利用各种常规测井曲线识别裂缝时存在局限性。为此提出基于常规测井与电成像测井多信息融合的裂缝识别方法,对多种常规测井曲线进行重构, 充分突显裂缝在常规测井曲线上的响应特征, 同时对电成像测井进行孔隙度谱分析, 从孔隙度谱中提取反映裂缝的熵、能量等谱特征, 构建多信息融合的裂缝发育概率预测模型, 对储层裂缝进行识别。岩心观察和成像测井描述裂缝结果的对比表明, 文中方法取得了良好的效果。

Fracture identification based on information fusion of conventional logging and electrical imaging logging

Fractures cannot be well identified with conventional logging curves due to dissolved pores development and low fracture opening degree in carbonate reservoir in Sichuan Basin. We propose in this paper an approach for fracture identification based on information fusion of conventional logging and imaging logging. We first reconstruct conventional logging curves to fully amplify fracture response. And then we analyzed porosity spectrum of the electric imaging logging, and extract spectrum characteristics such as entropy and energy from the spectrum of porosity. Finally we construct a probabilistic model based on multi-information fusion for reservoir fracture identification. Comparisons with core fracture observation and imaging logging verify the effectiveness of the proposed approach.