Empirical mode decomposition-refined composite multiscale dispersion entropy analysis and its application to geophysical well log data

Abstract Oil and gas exploration activities often face great challenges due to the nonlinear behavior of the reservoir's physical properties, which is commonly defined as “heterogeneity”. Currently, well log data analysis techniques are a novel approach to unravel such nonlinear behavior, because well log data incorporates considerable geological information that determines reservoir property. However, the current complexity analysis techniques face two challenges: 1) the spatiotemporal multiscale nature of complex geological systems and 2) the superposition of the trends in the geophysical well log data on the analysis results. To fill the research gap, we propose an empirical mode decomposition-refined composite multiscale dispersion entropy analysis (EMD-RCMDEA) to eradicate trends and obtain the complexity results with spatiotemporal characteristics. The proposed method produces more accurate results, and its effectiveness, stability, and efficiency are also verified by the simulation signals and the gamma-ray (GR) well log signals. Compared to previous refined composite multiscale entropy analysis (RCMSEA), the EMD-RCMDEA enhances the stability by 69.3% and efficiency by 53.5%. Additionally, using the GR well log data for reservoirs, this method is also applied to explore the heterogeneity of strata with diverse depositional environments and different composite patterns and acquire the following results. 1) The EMD-RCMDEA values of the GR well log data are positively correlated with the heterogeneity of the strata. 2) The reservoir developed in a delta-front depositional environment has the strongest heterogeneity. 3) The heterogeneity of the composite patterns is much stronger than that of the single heterogeneity patterns. 4) Among the heterogeneities of the composite patterns, the pattern consisting of different facies is stronger than that for single facies.