A New Approach for Compressional Slowness Modeling Using Wavelet Coefficients

Abstract

Compressional slowness, which may be derived from sonic log, is an important parameter that can be used for determining physical rock properties, such as young modulus and Poisson's ratio. Since the sonic logs are not common in oil fields, modeling the compressional slowness indirectly seems to be a key approach in obtaining the required data for calculating mechanical properties. In this study, a new approach is introduced to construct synthetic models of sonic logs using wavelet coefficients and artificial neural network. Obtained results confirm the applicability of this model in sonic log prediction.