Abstract

The formulation of an effective development plan, optimizing exploitation efficiency, relies heavily on accurate reservoir characterization. However, existing reservoir classification methodologies, which rely on macroscopic geological observations and well-logging data, have limitations in data availability and fail to capture micro-scale pore structure characteristics accurately. The emerging technology of digital rock, widely employed in the petroleum industry, also faces challenges in accurately capturing reservoir heterogeneity due to its single-scale nature and limited application for reservoir classification. To overcome these challenges, this study presents an innovative reservoir classification approach based on the multi-scale digital rock method. This approach integrates qualitative assessment of micro-CT images for particle contact relationships and pore types with quantitative evaluation of multi-scale characteristic parameters, obtained from micro-CT and scanning electron microscopy (SEM) images. The proposed classification method demonstrates excellent agreement with the prioritization of development and production data for offshore sandstone reservoirs. By establishing a robust evaluation methodology, this classification method facilitates exploration potential assessment and development strategy optimization within the field.

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