Multi-energy X-ray CT and data-constrained modeling of shale 3D microstructure

Abstract

Three Longmaxi Formation shale samples from different well depths were analyzed for their total organic carbon (TOC) content and mineral phases. Synchrotron-based multi-energy X-ray computed tomography (CT) slices have been acquired for these samples. Deviations of the sample center away from the harmonic trajectory during X-ray CT imaging were corrected to improve the accuracy of CT reconstructed tomographic slices. The three-dimensional (3D) distribution of porosity and mineral in the samples was derived using the data-constrained modeling (DCM) method. The equivalent spherical diameters of connected pore-organics clusters and the connection probabilities were calculated to evaluate the spatial agglomeration and the spatial correlation of pore-organics in the samples. Numerical results showed that the distribution of the connected regions size and the connection probabilities of pore-organics for three samples have similar characteristics. The connection probabilities versus the distance follow exponential law. The connection probability appeared to be positively correlated to the number of pore-organics connected clusters when the distance between the voxels is shorter than 10 μm. Comparing samples from the three well depths, both the numbers of connected regions and connection probabilities of the samples from a deeper well are higher. The approach would be applicable for structural characterization of other similar materials.