Fracture Characterisation Through Image Log Conductive Feature Extraction

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Abstract An approach is presented for fracture porosity, fracture aperture and permeability evaluation through extracting conductive image features from FMITM borehole image logs. The methodology of image feature and in particular fracture recognition, extraction and characterisation is based on the borehole image tool button response simulation model originally developed by Luthi (1990) for the water-based mud system and the principle of 2D fracture intensity (P32) to 3D fracture intensity/volume (P33) transformation. The extracted conductive image features allow us to distinguish open fractures and karst features. Fracture aperture is calculated as a function of the button resistivity, tool current & voltage, mud resistivity and background rock resistivity. Fracture porosity is computed with consideration of fracture type, well type and condition. Fracture permeability is estimated by taking fracture aperture, type and intensity into account. The results for naturally fractured tight carbonate reservoirs are demonstrated. Various types of conductive features are successfully recognised and characterised using the new approach. Sedimentary features like bedding and shale boundaries are identified too. Drilling induced or borehole breakout features have been distinguished and excluded from true nature formation features. The robustness of the fracture characterisation can be demonstrated through various field examples and reservoir model implementation. The new approach provided independent fracture characterisation inputs for discrete fracture network (DFN) and dynamic models of the fractured reservoir examples shown.