--> Quantitative Microporosity Evaluation Using Mercury Injection and Digital Image Analysis in Tight Carbonate Rocks: A Case Study From the Ordovician in the Tazhong Palaeouplift, Tarim Basin, NW China
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Quantitative Microporosity Evaluation Using Mercury Injection and Digital Image Analysis in Tight Carbonate Rocks: A Case Study From the Ordovician in the Tazhong Palaeouplift, Tarim Basin, NW China

Abstract

The heterogeneity of tight carbonate rocks is directly related to the morphology of micropores and the Previous HitconnectivityNext Hit of the Previous HitporeNext Hit network, which have a great influence on the intrinsic microporosity and fluid flow properties of porous media. However, neither can be quantitatively evaluated by conventional techniques. Based on core observation and thin section analysis, combined with high-resolution field emission-scanning electron microscopy (FE-SEM) and mercury injection capillary pressure (MICP) measurements, we can identify carbonate rock types, determine the microporosity and microstructure and calculate the Previous HitporeNext Hit structure parameters. Digital image analysis (DIA) and the fractal dimension (FD) method are used to study the relationship between the quantified Previous HitporeNext Hit structure parameters, heterogeneity and fluid flow properties. The results indicate that the microporosity of rock types has various microstructure characteristics. Crystalline types of microporosity (the small and large intercrystalline pores) increase Previous HitporeNext Hit network Previous HitconnectivityNext Hit whereas micromoldic pores show variations in Previous HitconnectivityNext Hit of different lithofacies. However, the small intercrystalline pores contribute little to the permeability because of narrow and complex Previous HitporeNext Hit networks for fluid flow. MICP data of samples reveal that the Previous HitporeNext Hit-Previous HitthroatNext Hit radius mainly ranges from 0.1 μm to 1.0 μm, which contributes the highest proportion of permeability to the samples. Fractal dimensions calculated from the “J-curve” models vary between 2.0746 and 2.8551 (avg. 2.331), indicating high heterogeneity. Moreover, the fractal dimension is strongly negatively related to the permeability, average Previous HitporeNext Hit Previous HitthroatNext Hit radius and separation coefficient. Additionally, quantified Previous HitporeNext Hit geometric parameters from DIA, including dominant Previous HitporeNext Hit Previous HitsizeNext Hit (DOMsize), perimeter over area (PoA), Previous HitporeNext Hit body-to-Previous HitthroatNext Hit ratio (BTR) and average roundness (γa), greatly influence the Previous HitporeNext Hit structure and fluid flow behavior. The samples with large DOMsize, high γa, low PoA and low BTR show a low fractal dimension and simple Previous HitporeNext Hit network but high permeability. Diagenesis can also affect the fractal Previous HitporeNext Hit space and self-smilarity Previous HitporeTop geometries of carbonates across all length scales. This information about the micropore geometry and microstructure of the carbonate rock will further improve the assessment of its reservoir properties.