Frontiers in Earth Science (Jul 2024)
Pore structure characteristics and influencing factors of dolomite reservoirs: a case study of the lower Ordovician Majiagou Formation, Ordos Basin, China
Abstract
The evaluation of the pore structure in dolomite, particularly with regard to pore heterogeneity, geometry, and connectivity, is crucial for oil and gas field production and reservoir prediction. The subsalt dolomite reservoir in the Ordovician strata of the Ordos Basin has shown promising exploration results and is anticipated to have a high hydrocarbon potential. However, there has been limited research on the pore structure and primary controlling factors of the Ordovician Majiagou reservoir in the south-central Ordos Basin. Therefore, we conducted a comprehensive analysis of the pore structure and fractal characteristics using routine petrophysical measurements, thin-section analysis, and high-pressure mercury injection (HPMI) data. We also discussed the relationship between fractal dimension, reservoir physical properties, and pore structure, along with exploring the origin of potentially prolific reservoirs. Our observations from the thin section identified four main pore types: intercrystalline pores, intercrystalline dissolved pores, dissolved pores, and micro-fractures. The data from HPMI revealed that the average pore–throat radii range from 0.009 μm to 0.015 μm with porosity ranging from 0.4% to 5.26%, and permeability ranging from 0.011 mD to 0.059 mD. They were further categorized into three reservoir types: dissolved pore type, intra-crystalline (dissolved) pore type, and micro-porous type. The fractal dimension was calculated based on HPMI data, and the reservoir’s fractal characteristics were divided into two segments. The dissolved pore type was identified as the potentially prolific reservoir due to its larger pore size and volume, moderate permeability, and homogeneity on pore structure. Additionally, the fractal dimension is negatively correlated with porosity and permeability and positively correlated with sorting coefficient and skewness, suggesting that fractal dimensions are valuable for evaluating reservoir quality and quantitatively characterizing pore networks.
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