基于测井-地震信息的碳酸盐岩储层裂缝预测方法

碳酸盐储层裂缝发育、非均质性强，单一测井或地震方法识别裂缝存在局限性，为此提出了测井-地震信息融合预测碳酸盐岩储层裂缝的方法。首先，将粗糙集理论与裂缝发育程度划分相结合，把权系数问题转化为粗糙集中属性重要性评价问题，根据钻井取心对测井识别的裂缝进行刻度；其次，基于叠前地震方位各向异性预测裂缝发育优势方位及裂缝密度；最后，通过井震标定完成测井与地震尺度匹配，拟合测井裂缝可拓识别结果与叠前地震各向异性检测强度的函数关系，划分地震边缘检测裂缝级别。以实际工区资料为例，进行了碳酸盐岩裂缝测井-地震信息融合的裂缝预测，结果表明:该方法既能提高裂缝预测结果的可靠性，又能对纵向及横向不同尺度的裂缝进行有效识别。研究结果可为碳酸盐岩储层的裂缝预测提供有益的借鉴。 

Fracture Prediction in a Carbonate Reservoir Based on Logging-Seismic Data

Carbonate reservoir formations are characterized by the development of fractures and strong heterogeneity.Under such circumstances, singular logging or seismic techniques have limitations in the identification of fractures.In the concerned study, a method involving a combination of logging and seismic data was proposed for predicting fracture development in carbonate reservoir formations.First of all, the rough set theory could be combined with development of fractures to transform weight coefficient problem into the attribute evaluation in rough set.In this way, fractures identified by using logging data could be calibrated by using drilling and coring data.Second, based on azimuthal anisotropy of pre-stacking seismic data, the fracture development, dominant azimuth and fracture growth density could be predicted;Finally, the matching of logging and seismic scale was completed through drilling-seismic calibration.In addition, the functional relationship between the logging fracture extension recognition results and pre-stack seismic anisotropy detection intensity could be matched to highlight extent of the seismic data and grades of fractures.Field data were used to predict fracture development in carbonate reservoir formations through a combination of logging-seismic data.Research results showed the proposed method could effectively enhance the reliability of prediction.In addition, fractures of various scales in both horizontal and vertical directions could be identified effectively.Relevant research might provide valuable references for prediction of fracture development in carbonate reservoir formations.