Chaotic behavior of geophysical logs for stratigraphic hiatuses: A case study from Upper Assam Shelf, India

We propose a novel fractal analysis-assisted approach for stratigraphic characterization to understand the in-situ subsurface geology of hydrocarbon reservoirs. By employing correlation dimension and multifractal detrended fluctuation analysis, we quantify the self-similarity and long-range dependencies in the geophysical logs, reflecting the unique sedimentation processes inherent in the stratigraphic formations of the Bhogpara oil field in the Upper Assam basin. The fractal properties of the logs associated with various stratigraphic units are used to establish a fractal-based stratigraphic signature. The hierarchy of the studied formations, based on the correlation dimension ranging from 1.98 to 1.13, is follows as: Girujan > Tipam > Barail > Kopili > Prang > Narpuh > Lakadong-Therria. Furthermore, the spectrum width values, was found to range from 0.70 to 2.04, reflecting the spatial correlation, geological complexity, and heterogeneity inherent in each formation as: Kopili > Prang > Narpuh > Barail > Girujan > Tipam > Lakadong-Therria. This method identifies common fractal patterns between wellbores and aids in determining the spatial continuity of stratigraphic units. Our approach effectively detects lateral variations in subsurface formations, linking well log fractality with depositional patterns through various transitional environments, such as lacustrine to shallow marine to fluvial, in presence of different fluids. The petroliferous formation exhibits lowest fractal dimension and weak multifractality. The research utilizes fractal analysis to improve stratigraphic correlation, enhancing subsurface characterization and reservoir delineation, particularly in complex geological environments, and enhancing reliability.