Formation evaluation of rock material from unconventional reservoirs is challenging due to the rock's typically heterogeneous nature and low permeability. Measurements and descriptions of the pore network in shale/mudstone are especially difficult due to variations in mineralogy, texture and pore size. In the digital rock domain, high resolution imaging of core can be obtained from the meter to nanometer size range to create respective 3D models. Data obtained with these techniques can be integrated with other core analysis data (i.e. geochemistry, petrology, mechanical properties) to provide expanded modeling capabilities for integrated core studies of unconventional reservoirs.
This paper describes how an integrated imaging/sampling protocol serves to characterize unconventional reservoirs across a broad size range. High resolution digital imaging data derived from Helical Computed Tomography (HCT) and micro-CT captures meter- to millimeter-sized features, while Field Emission Scanning Electron Microscopy (FE-SEM), and Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) provide the means to characterize the rock fabric and pore network on a sub-micron (<nm) level. For this study, a 4-inch diameter core from a proprietary well in the Middle East was submitted to Weatherford Laboratories in Houston, Texas, for analysis.
Sections of core were first imaged/analyzed using HCT. Based on observations from HCT images, samples were subsequently selected for micro-CT, FE-SEM, and FIB-SEM. Though the HCT images were also used to select data points for traditional core analysis (i.e. thin section petrography, X-ray diffraction, geochemistry, etc.), those data sets will be presented at a later date, and the focus of this paper is the use of digital imaging to characterize selected samples. The resulting images and accompanying data sets acquired in this study illustrate how digital imaging methodologies can be used to characterize the controls on reservoir quality (including depositional fabrics, structural relatioinships, diagenetic relationships, and the pore network), and ultimately lead to a better understanding of well performance in unconventional reservoirs.