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Title: A Geostatistical Study in Support of CO 2 Storage in Deep Saline Aquifers of the Shenhua CCS Project, Ordos Basin, China

The Shenhua Carbon Capture and Storage (CCS) project at the Shenbei Slope injection site in North Yulin is the first 100,000 ton-per-year scale CCS pilot project in China with an injection operation lasting nearly 3 years. In this study, we investigate various geostatistical methods and their impact on the respective geologic models on which simulation is performed to understand the phenomena observed during 3 years of Shenhua CCS operations. Although there was a brief period of wellhead pressure increase at the injection well, it unexpectedly dropped for most of the time. Another interesting observation showed that the majority of CO 2 gas injection was received by the topmost sandstone Liujiagou formation instead of the basement limestone Majiagou formation, which was predicted to have much more injectivity and storage capacity. Based on the current geostatistical methods and available data, 3 steps of reservoir modeling and flow simulation are carried out and they go from having homogeneous property models to incorporating standard 2-point geostatistical methods to using object-based models. The layer-cake models generate a rather uniform plume shape and increased pressure response. Meanwhile, two-point statistical models add more complexity to the size and shape of CO 2 plume, however are not capablemore » of reproducing the pressure decline behavior. These results demonstrate homogeneous and 2-point geostatistical models are inadequate in interpreting subsurface heterogeneity, both due to their method and data limitations. Further work is being done with object-based models to produce a system of meandering rivers based on the geological concept of Shenhua injection site. This will help offset the data limitation and bring our model closer to geologic reality.« less
Authors:
 [1] ;  [2] ;  [3] ;  [3] ;  [3] ;  [3] ;  [3] ;  [4]
  1. Univ. of Wyoming, Laramie, WY (United States). Dept. of Geology & Geophysics; Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Univ. of Wyoming, Laramie, WY (United States). Dept. of Geology & Geophysics
  3. Chinese Academy of Sciences (CAS), Wuhan (China). Inst. of Rock & Soil Mechanics
  4. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Report Number(s):
LA-UR-16-27179
Journal ID: ISSN 1876-6102
Grant/Contract Number:
AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
Energy Procedia
Additional Journal Information:
Journal Volume: 114; Conference: 13. International Conference on Greenhouse Gas Control Technologies, Lausanne (Switzerland), 14-18 Nov 2016; Journal ID: ISSN 1876-6102
Publisher:
Elsevier
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Univ. of Wyoming, Laramie, WY (United States); Chinese Academy of Sciences (CAS), Wuhan (China)
Sponsoring Org:
USDOE; US-China Clean Energy Research Center
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; geostatistics; modeling; CO; injection; pilot project
OSTI Identifier:
1467367

Nguyen, Minh C., Zhang, Ye, Li, Jun, Li, Xiaochun, Bai, Bing, Wu, Haiqing, Wei, Ning, and Stauffer, Philip H.. A Geostatistical Study in Support of CO2 Storage in Deep Saline Aquifers of the Shenhua CCS Project, Ordos Basin, China. United States: N. p., Web. doi:10.1016/j.egypro.2017.03.1720.
Nguyen, Minh C., Zhang, Ye, Li, Jun, Li, Xiaochun, Bai, Bing, Wu, Haiqing, Wei, Ning, & Stauffer, Philip H.. A Geostatistical Study in Support of CO2 Storage in Deep Saline Aquifers of the Shenhua CCS Project, Ordos Basin, China. United States. doi:10.1016/j.egypro.2017.03.1720.
Nguyen, Minh C., Zhang, Ye, Li, Jun, Li, Xiaochun, Bai, Bing, Wu, Haiqing, Wei, Ning, and Stauffer, Philip H.. 2017. "A Geostatistical Study in Support of CO2 Storage in Deep Saline Aquifers of the Shenhua CCS Project, Ordos Basin, China". United States. doi:10.1016/j.egypro.2017.03.1720. https://www.osti.gov/servlets/purl/1467367.
@article{osti_1467367,
title = {A Geostatistical Study in Support of CO2 Storage in Deep Saline Aquifers of the Shenhua CCS Project, Ordos Basin, China},
author = {Nguyen, Minh C. and Zhang, Ye and Li, Jun and Li, Xiaochun and Bai, Bing and Wu, Haiqing and Wei, Ning and Stauffer, Philip H.},
abstractNote = {The Shenhua Carbon Capture and Storage (CCS) project at the Shenbei Slope injection site in North Yulin is the first 100,000 ton-per-year scale CCS pilot project in China with an injection operation lasting nearly 3 years. In this study, we investigate various geostatistical methods and their impact on the respective geologic models on which simulation is performed to understand the phenomena observed during 3 years of Shenhua CCS operations. Although there was a brief period of wellhead pressure increase at the injection well, it unexpectedly dropped for most of the time. Another interesting observation showed that the majority of CO2 gas injection was received by the topmost sandstone Liujiagou formation instead of the basement limestone Majiagou formation, which was predicted to have much more injectivity and storage capacity. Based on the current geostatistical methods and available data, 3 steps of reservoir modeling and flow simulation are carried out and they go from having homogeneous property models to incorporating standard 2-point geostatistical methods to using object-based models. The layer-cake models generate a rather uniform plume shape and increased pressure response. Meanwhile, two-point statistical models add more complexity to the size and shape of CO2 plume, however are not capable of reproducing the pressure decline behavior. These results demonstrate homogeneous and 2-point geostatistical models are inadequate in interpreting subsurface heterogeneity, both due to their method and data limitations. Further work is being done with object-based models to produce a system of meandering rivers based on the geological concept of Shenhua injection site. This will help offset the data limitation and bring our model closer to geologic reality.},
doi = {10.1016/j.egypro.2017.03.1720},
journal = {Energy Procedia},
number = ,
volume = 114,
place = {United States},
year = {2017},
month = {8}
}