- https://www.onepetro.org/conference-paper/URTEC-2697437-MS?sort=&start=0&q=2697437&from_year=&peer_reviewed=&published_between=&fromSearchResults=true&to_year=&rows=10#
- 10.15530-urtec-2017-2697437
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Abstract — Reliable characterization of complex reservoirs is tightly coupled to studying their microstructure at a variety of scales and requires departure from traditional petrophysical approaches and deepening into the world of nano-scale. A promising method of retaining representatively large volume of a rock sample while achieving nanoscale resolution is based on multiscale digital rock technology. The smallest scale of this approach is often realized in the form of several 3D FIB-SEM models, registration of these models to larger volume of rock sample, as well as estimation and upscaling of models’ local properties to the volume of the entire sample. However, justified and automated selection of representative regions for building FIB-SEM models poses a big challenge to a researcher. In this work, our objective was to integrate advanced multiscale SEM technology and modern mineral mapping technology, to make a justified decision on location of representative zones for FIB-SEM analysis of a rock sample. The procedure is based on two experimental methods. The first method is an automated quantitive mineralogy and petrography scanning method that allows covering sample’s cross-section with a mineralogy map, having resolution down to 1 μm/pixel. The second method targets automated mapping of sample’s surface area with the use of backscattered electrons and secondary electrons; this method has resolution down to nanometers and spatial coverage up to centimeters (large-area high-resolution SEM imaging). Data gathered with both methods on millimeter-sized cross-sections of rock samples were registered and integrated in the paradigm of joint data interpretation, augmented with image processing techniques, to provide a reliable classification of nanoscale and microscale features on samples’ cross-section. The superimposed SEM and mineral map images were combined with physics-based selection criteria for reasonable selection of FIB-SEM candidates out of a great number of potential sites. In the result, an automated workflow was built. Demonstration of the workflow is made on one of Russian most promissing tight gas formation, where pore space includes objects ranging from single nanometers up to millimeters. An example of optimal site selection for FIB-SEM operations, as well as an example of a typical FIB-SEM model are discussed. Basic correlation to petrophysical properties of rock is performed.