Pore Network Investigation in Marcellus Shale Rock Matrix

Abstract

The ever-growing energy demand and recent discoveries of vast unconventional oil and gas reservoirs have brought significant attention to shale oil and gas resources as potential game-changers for the petroleum industry and energy markets worldwide. The complex structural features and mineralogy of shale has broad implications on the development of the unconventional oil and gas industry. Although shale reservoirs are large in scale and offer the potential for long-lived production, extremely low matrix porosity and permeability, as well as complex heterogeneity, pose major challenges in obtaining economically viable oil or gas. A lack of predictive understanding of microstructure-based heterogeneity in shale limits the effectiveness of currently used production technologies. Hence, addressing the challenges of shale oil and gas production requires an in-depth understanding of microstructural features that control the oil and gas storage, release, and transport mechanisms.Because anisotropy of shale exists across multiple scales, determining changes in pore distribution has proven to be difficult. Recent studies have indicated that shale pores significantly vary in number, size (from nano-to micro-pores), and classification (organic and nonorganic). Thus far, the role of pore network and, more specifically, what pores contribute the most to the gas and/or oil storage or to the production process, is not well understood and remains largely unknown. Hence, it is vital to determine how well different pores are connected and how they create possible flow pathways for hydrocarbon migration.Here we present a comprehensive digital rock physics (DRP) framework for pore network investigation in a Marcellus Shale rock matrix. Pore networks within both organic and nonorganic matter are reconstructed from focused ion beam scanning electron microscopy (FIB-SEM) images of the shale specimen. Through this process, the pore size distribution, porosity, pore connectivity, and mineralogyorganic-matter-hosted and nonorganic-matter-hosted pores -of the sample are obtained. The impact of obtained parameters on fluid flow in shale is analyzed.

U.S. DOE NETL methodology for estimating the prospective CO2 storage resource of shales at the national and regional scale

“…Flow is governed by the multiphase fluid flow and capillary processes that control all porous media flow, with the added complication that diffusive and surface transport properties are non-negligible at nD permeabilities. Transport at the poreand sub-pore scales in shales should therefore be understood as occurring in a physical space containing all the different pore types present in shale with complex conductivities that are the subject of continuing research, see Goral et al (2015) or Zhang et al (2015). Currently, flow of CH 4 or CO 2 at the nm and sub-m scales cannot be directly imaged, and the complexities of shale pore geometries and sizes must therefore be visualized from static images such as the ones presented below.…”

Nanofabrication of synthetic nanoporous geomaterials: from nanoscale-resolution 3D imaging to nano-3D-printed digital (shale) rock

“…The first step in creating representative synthetic rocks is to extract information from geological samples at very high resolution. It has been shown in multiple previous studies on shale 3D-imaging/-modeling, that attaining nanoscale-resolution is crucial in being able to replicate fluid behavior [36][37][38][39][40][41][42] . Thus, reconstructing digital rock 3D models from high-resolution image datasets is an important step in the workflow described in this paper.…”

A GPU-accelerated package for simulation of flow in nanoporous source rocks with many-body dissipative particle dynamics

“…In particular, mDPD manifests a unique multiscale modeling capability that can model fluid-fluid/solid interfaces in pores at both continuum-and sub-continuum-scales, as demonstrated in Figure 1. data of shale core samples, which are generated from a focused ion beam scanning electron microscopy (FIB-SEM) digital rock imaging process [23] with voxel resolution at tens of nanometers or even a few nanometers. Each voxel contains local composition information that can be used to identify phase boundaries in shale, e.g.…”