High-resolution seismic impedance inversion using improved CEEMD with adaptive noise

Seismic impedance inversion is an inevitable step in reservoir characterization required in both exploration and field works. It provides layer-based acoustic impedance property of rocks by imaging subsurface through the integration of data derived from seismic and well logging investigations. Recent studies providing subsurface rocks’ properties have highlighted the need to resolve seismic data’s nature, which is the limited frequency bandwidth. Although a significant amount of work has been done in the previous years by geophysicists, this problem continues. In this study, by implementing a powerful and robust time-frequency signal processing method, namely improved complementary ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), we propose a seismic inversion algorithm in order to overcome the mentioned problem. In other words, we propose an algorithm that improves the seismic impedance inversion in order to obtain subsurface images with higher resolution than other common impedance inversion methods. For a dataset, the proposed method resulted in a 98.44(%) correlation coefficient with 164.82 RMS error between the original log and inverted log while the commercial Band-limited, hard and soft constrained Model-based inversion methods resulted in a 91.29(%), 91.12(%) and 93.05(%) with 345.33, 322.39 and 295.48 RMS errors, respectively. Results demonstrate the resolution enhancement in impedance inversion by our proposed method in comparison to previous approaches.
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