22 Carbon Storage Research (Posters)
Thursday, 7 April 2022
1:30 PM - 5:30 PM
Junior Ballroom B
VUG AND FRACTURE CHARACTERIZATION OF TRENTON-BLACK RIVER RESERVOIRS THROUGH CT SCAN AND IMAGE LOG ANALYSIS IN THE SOUTHERN MICHIGAN BASIN
Paper number: 22-3
Program: Theme Sessions
Time: 1:30 PM – 5:30 PM
Authors
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Laura KeisterBattelle, Columbus, OH
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Autumn HaagsmaBattelle, Columbus, OH
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Srikanta MishraBattelle, Columbus, OH
Abstract
To address these challenges, image logs and 3D computed tomography (CT) scans that depict secondary porosity features (i.e., vugs and fractures) were compiled. Image logs provide high-resolution, 360-degree wellbore images that can be used to derive planar structural and sedimentary features for detailed reservoir characterization, such as faults, fractures, bedding, stress fields, and pores. Flags were developed to identify and classify vugs and fractures, and the frequency and orientations were analyzed. The 3D CT scans capture high-resolution images of whole core that represent variations in density, indicating changes in composition and porosity. We developed a technique which isolates specific rock density ranges, quantifies the percent of each feature, and creates 3D visualizations. Image logs and CT scans were compared for wells that had both datasets.
The results produced quantitative size, orientation, and distribution for thousands of secondary porosity features in the TBR. The features varied greatly from well to well but had the highest concentration within dolomitic intervals. Total porosity increased where features were present, indicating an important role in reservoir quality. Overall, this study quantitatively detailed the distribution of these complex porosity networks. These results will be integrated into a 3D static earth model and will inform the dynamic model to address the complex geology and test injection scenarios of CO2-EOR feasibility in the TBR.
Project is funded through U.S DOE-FOA-0001988
Geological Society of America Abstracts with Programs. Vol. 54, No. 4
doi: 10.1130/abs/2022NC-375502
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