A DFA approach in well-logs for the identification of facies associations

Abstract

Well-log analysis is a useful tool for the lithological description of wells. Its adequate interpretation allows determining different rock properties such as permeability, density, resistivity and porosity among others. However, given the complexity inherent in the signals, the identification of lithological properties from well-log analysis is not an easy task. In this work, an alternative methodology for sedimentary facies identification based on the detrended fluctuation analysis (DFA) is presented. Our methodology has been calibrated using information from a reference well located at the Chicontepec formation of the Tampico-Misantla basin in Mexico. Its characterization includes the interpretation of different well-logs and cores. Our results indicate that well-log signals present fractal characteristics exhibiting long-range memory. For the gamma ray, resistive and sonic logs a direct relationship between the scaling exponent as a function of the depth and rock types is observed. In this way, the fractal scaling exponents estimated with DFA can be used to identify different sedimentary facies.