Sinusoid recognition and texture analysis of Electrical Borehole Images

We propose an automatic Electrical Borehole Image (EBI) processing methodology to improve reservoir interpretation. Geologic features seen on EBI can be separated into planar and spot heterogeneities. Planes are represented by sinusoids on borehole images. We propose two sinusoid-recognition algorithms for bed boundaries, and bedding planes respectively. This separation of problem assures a better performance and efficiency of algorithms. A texture analysis procedure is then proposed for EBI textures quantification by use of texture analysis-synthesis technique and Self-Organizing Map. This procedure generates textural log which can be integrated with conventional logs. A 2-D synthetic texture map is created to facilitate the calibration of the textural log to cores. Our methods have been implemented and tested for several real field cases and proved their capacity to improve definition of facies.