Application of wavelet transform to detect fractured zones using conventional well logs data (case study: southwest of Iran)

Abstract

Detection of fractured zones is an indisputable challenge in fractured reservoir characterisation. Although fracture identification from core data and image logs are direct and effective, they are costly and not commonly used. In this study, the discrete wavelet transform (DWT) was applied to decompose water saturation log data to detect fractured zones and calculate the number of fractures. Herein, the energy matching strategy and wavelet packet were used to select the optimum mother wavelet. The uranium log was applied as a filter to reduce errors which improved the accuracy of results for prediction of fractured zones by 90%. Finally, the relationship between signal energy of water saturation log and the number of fractures in each fractured zone was studied. The proposed method was successfully tested in wells in the Asmari formation (South Western Iran) and provides significant scope for application in other analogous field.