Study Of Microscopic Pore Structure Characterization And Digital Core Model Of Gas Shale

Because of the complex deposition and diagenesis, gas shale developed a large number of micropores and nanopores, resulting in gas shale has a low effective porosity, low permeability, strong heterogeneity and complex pore structure. Therefore, exploration and development of gas shale faces many challenges. Currently, there are many imperfections in gas shale reservoir evaluation. It is not clear enough for understanding of the microstructure of shale, and the pore microstructure characteristics is the core of reservoir studies, pore structure directly impact on reservoir capacity and flow capacity of reservoir, indirectly affecting the oil and gas well productivity and recovery, so more understanding of microscopic pore structure of gas shale is necessary. By combination of physical experiments and numerical analysis, we qualitatively and quantitatively characterize the microscopic pore structure of Southern Longmaxi shale, the achievements and awareness are listed as follows:(1) By combination of scanning electron microscopy, X diffraction, helium porosity method, pressure decay method, Langmuir adsorption model and NMR experiments, we obtain the petrological characteristics, the organic geochemical characteristics, the reservoir space characteristics and physical properties.(2) We obtain the pore type, pore volume, specific surface area and pore size distribution by high pressure mercury injection experiment, Nitrogen adsorption experiment and NMR experiment. Calculating the NMR conversion factor C of NMR pore diameter distribution based on integrated mercury-N2 adsorption pore diameter distribution curves, we find when C= 4.56, the error is minimum. Calculating pore structure characteristic parameters based on constructed mercury pressure curves. The results show that gas shale is high heterogeneity and the pore network is complex. This is disadvantage for gas flow. The research indicate that TOC is the main factor controlling the surface to volume ratio, illite/smectite and the pore volume of miropores and mesopores also affect the surface to volume ratio.(3) Longmaxi gas shale digital core model was established by Markov chain Monte Carlo (MCMC) method. The results show MCMC method is suitable for gas shale digital core model. 3D model is well consistent with 2D original image. The image resolution has a large influence on property of digital core model. Thus, for different research needs to select a suitable resolution. We use the maximum ball method to extract pore network model from 3D digital core model. The results show that the pore network model is well consistent with 3D digital core model. Calculating pore structure characteristic parameters based on pore network models, we find the resolution is lower, the property of pore structure characteristic parameters are worse. Overall the connectivity of gas shale pore network model is poor, and coordination numbers are few.(4) Based on fractal geometry method, we calculate pore size distribution fractal dimension, pore surface fractal dimension using FHH model, Box-counting dimension which represent pore space distribution. We have discussed the correlations between different fractal dimensions. The relationships between TOC, mineral components, pore structure parameters and fractal dimensions are discussed. TOC, clay mineral content and pore volume are key parameters affecting fractal dimension. The fractal expression of pore structure parameters are derived, the results show all parameters have fractal Characteristics.(5) Utilizing pore structure parameters and pore network model predict the absolute permeability of gas shale, we calculate the NMR prediction model parameters and improve the NMR prediction model. The optimal T2 cutoff time of shale was determined from centrifugal tests, and the results are largely different from the classical value for sandstone. We improve the SDR model. Two new models have been derived. The results obtained by the modified model and new models are closer to gas permeability. Fractal permeability prediction model have been derived, the results show average pore size ratio and fractal dimension have the largest influence on permeability. The prediction permeability is well consistent with gas permeability. Utilizing percolation theory to simulate the pore level flow, percolation theory has a well applicability in gas shale pore-scale flow simulation.In this paper, we obtain shale microscopic pore structure characteristics and establish a southern Sichuan Longmaxi shale digital core model. It is important and valuable for exploration and development of Sichuan Basin Longmaxi formation gas shale reservoir.