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Yang, Xiaoguang

Publications and source records attributed to Yang, Xiaoguang.

Micro- to nano-scale areal heterogeneity in pore structure and mineral compositions of a sub-decimeter-sized Eagle Ford Shale

Mineral and organic matter compositions & pore structures of fine-grained shale influence reservoir properties. To improve the understanding of spatial heterogeneity in core-sized samples, methods of microscale X-ray fluorescence (μXRF) mapping, (ultra-) small-angle x-ray scattering [(U)SAXS] and wide-angle X-ray scattering (WAXS) have been used to determine elemental, pore-structure variations at scales up to ~10 cm on two samples prepared at circular and rectangular orientations from a piece of Eagle Ford Shale outcrop in South Texas, USA. In addition, thin section petrography and field emission-scanning electron microscopy observations, X-ray diffraction (XRD), total organic carbon, and pyrolysis were utilized to investigate the potential spatial heterogeneity of pore types, mineral and organic matter compositions for cm-sized samples at both orientations. Overall, the siliceous-carbonate mineral contents in these two samples (8 cm×8 cm×0.08 cm and 5 cm × 8 cm × 0.08 cm, in terms of width×length×thickness) of carbonate-rich Eagle Ford Shale vary between laminations at mm scales. For the circular sample, porosity and specific surface area (SSA) variations range from 0.82 to 3.04% and 1.51 to 14.1 m 2 /g, respectively. For the rectangular sample, values for porosity and SSA vary from 0.93 to 2.50% and 3.95 to 10.8 m 2 /g. By analyzing six selected sub-samples on each of two samples with (U)SAXS and XRD techniques, nm-sized pores are mainly interparticle ones in the higher calcite regions, where the porosity is also relatively lower, while the lower calcite regions consist of both interparticle and intraparticle pore types with higher porosity. Lastly, the μXRF and (U)SAXS mappings are combined to generate porosity distribution maps to provide more insights about sample heterogeneity related to the laminations and fractures at our observational scales.

58 GEOSCIENCES↗

dbprocessing

dbprocessing is a python framework for automating data processing pipelines. The dbprocessing package uses a configuration file to define the input, intermediate, and output data products for a particular data type as well as the processes that connect those data products. In addition, dbprocessing uses python scripts called inspectors to determine if a particular file matches a configured data product. If a particular data product is found, it is ingested into the dbprocessing database (sqlite3 or postgres) which then triggers all of the chained processes to the final data product. While the framework is written in python, it can run software in any language but may require a “wrapper” to translate the dbprocessing command line arguments to the form expected by the software.

Walker, Andrew↗