Pore Scale Characterisation of Coal: An Unconventional Challenge

Abstract

Coal seam gas is an unconventional resource for natural gas that is becoming popular due to its environmental benefit and abundance. This paper reviews recent developments on the pore-scale characterisation of coal from coal seam gas reserviors. The development of micro-computed tomography (micro-CT) imaging has enabled for the 3D characterization of the fracture system in coals. This provides detailed insights into understanding flow in these unconventional reservoirs. A novel image calibration method in which the skeleton of the fracture system is obtained from micro-CT imaging while the fracture apertures are measured from scanning electron microscopy (SEM) is described. We also show the application of micro-CT imaging for studying diffusion processes in ultralow permeability matrices and discuss the incorporation of the data into calculations of gas production from unconventional reservoirs. The extraction of statistical information from micro-CT images to reconstruct coal cleat system are also demonstrated. This technique allows for preserving the key attributes of the cleat system while the generated fracture network is not limited in terms of size nor resolution. The developments of microfluidic methods for understanding the complex displacement mechanisms in coal seams are also described. These low-cost experimental methods can provide unique information about the displacement mechanisms occurring during gas production from coal seam reservoirs. Variation of coal contact angle with pressure is analysed and results demonstrate important wettability processes that occur in coal seams. We describe numerical methods for prediction of petrophysical properties from micro-CT images of coal and discuss the associated limitations when dealing with coal samples. The paper concludes by addressing the challenges faced when characterising coal at the micro-scale and approaches for population of coal data into reservoir simulators for relaible prediction of reservoir behaviour during gas production as well as CO2 sequestration in coalbeds.

Hybrid pore-network and lattice-Boltzmann permeability modelling accelerated by machine learning

“…The main limitation of direct methods is the high computational cost [1], which could be a major obstacle when we are dealing with large-sized and high-resolution volumetric images of porous material. As a solution to this size and time limitation, domain decomposition and parallel computation have been comprehensively hired to increase the models efficiency and scalability [32,33,34,35,36]. Additionally, as another solution to deal with computational limitations, machine learning can be employed to mimic the behaviour of the complex solid/fluid systems.…”

Rock Characterization Using Gray‐Level Co‐Occurrence Matrix: An Objective Perspective of Digital Rock Statistics

“…Petrophysical properties of rocks are highly affected by image resolution. While low-resolution images might be sufficient for rocks with large pores and throats such as sandstones (Peng et al, 2014), for rocks with microfractures and microporosity such as coal (Mostaghimi et al, 2016(Mostaghimi et al, , 2017, high-resolution images are essential for accurate pore-scale modeling and numerical simulation. For the same rock sample, a higher-resolution micro-CT image will reveal more details than a low-resolution image and hence, the petrophysical properties derived from each of these images will be different.…”

“…This calls for a need to develop techniques to estimate pore-scale properties that are independent of segmentation and incorporate the variation in the gray-level intensities. Incorporating information from the grayscale images of porous media provide a basis to thoroughly understand the pore/grain structure especially in highly heterogeneous porous media such as chalk (Bruns et al, 2017) and coal (Mostaghimi et al, 2016(Mostaghimi et al, , 2017. Wildenschild and Sheppard (2013) have discussed several challenges associated with any analysis based on grayscale images and hence, recommended the use of multiple-point statistics on segmented images.…”

“…This calls for a need to develop techniques to estimate pore‐scale properties that are independent of segmentation and incorporate the variation in the gray‐level intensities. Incorporating information from the grayscale images of porous media provide a basis to thoroughly understand the pore/grain structure especially in highly heterogeneous porous media such as chalk (Bruns et al, ) and coal (Mostaghimi et al, , ).…”

Insights, Trends and Challenges Associated with Measuring Coal Relative Permeability

“…Coal fractures are void space and their permeability is high compared to the matrix making them the main pathways for flow in the formation (Seidle et al, 1992). These fractures, known as cleats, can be divided into two sets of distinctly different fracture types identified as face cleats that are parallel to the bedding plane and butt cleats that run orthogonal to the bedding plane (Mostaghimi et al, 2016). When studying coal relative permeability under production conditions, fractures likely dominate the relative permeability behaviour due to their absolute permeability being greater than that of the matrix.…”