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Title: Probabilistic Risk Assessment of CO2 Trapping Mechanisms in a Sandstone CO2-EOR Field in Northern Texas, USA

Abstract

This study employs a polynomial chaos expansion (PCE) technique to develop the reduced order models (ROMs) integrated with the Monte Carlo simulations to quantify uncertainties of CO 2 storage associated with enhanced oil recovery (EOR) in a commercial-scale CO 2-EOR field. The Morrow B sandstone at the Farnsworth Unit (FWU) EOR field in northern Texas was selected as a case study. A 3-D reservoir model, including simulation of a five-spot injection/production well pattern, was constructed based on the data from well logs and cores, and an updated seismic interpretation in the FWU. Porosity and permeability were considered as sources of uncertainty. The 1000-realization heterogeneous random fields of porosity and permeability were generated based on the variogram analysis on the core measurements of the FWU. Three model outputs of interest include the amount of CO 2 trapped by three trapping mechanisms, i.e. hydrodynamic trapping, oil dissolution trapping, and aqueous dissolution trapping. The total of 25 runs were conducted with the simulations of a 20-year CO 2-EOR period, and a 20-year monitoring period to develop the ROMs between uncertain model input parameters (i.e., porosity and permeability in this study) and model outputs at the end of simulation for each grid cell usingmore » PCE approach. The high coefficient of determination (R 2) and small normalized root mean square error (NRMSE) between the simulated (using reservoir modeling) and predicted (using ROMs) CO 2 storage indicate that the ROMs are acceptable and reliable to be used for the predictions. Given the 1000 Monte Carlo samplings of the model input parameters, cumulative distribution functions (CDFs) and uncertainty bounds (10 th and 90 th percentiles) of model outputs were estimated based on ROMs. At the end of simulation, the most injected CO 2 at the FWU was stored by hydrodynamic trapping (between 121,400 and 166,860 tonnes), followed by oil dissolution trapping (between 55,303 and 76,816 tonnes), and aqueous dissolution trapping (between 1979 and 2751 tonnes).« less

Authors:
 [1];  [2];  [3];  [1];  [1]
  1. Univ. of Utah, Salt Lake City, UT (United States)
  2. Utah Division of Water Resources, Salt Lake City, UT (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1557749
Report Number(s):
LA-UR-18-29425
Journal ID: ISSN 1876-6102
Grant/Contract Number:  
89233218CNA000001; FC26-05NT42591
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Energy Procedia
Additional Journal Information:
Journal Volume: 114; Journal Issue: C; Journal ID: ISSN 1876-6102
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 58 GEOSCIENCES

Citation Formats

Jia, Wei, Pan, Feng, Dai, Zhenxue, Xiao, Ting, and McPherson, Brian. Probabilistic Risk Assessment of CO2 Trapping Mechanisms in a Sandstone CO2-EOR Field in Northern Texas, USA. United States: N. p., 2017. Web. doi:10.1016/j.egypro.2017.03.1581.
Jia, Wei, Pan, Feng, Dai, Zhenxue, Xiao, Ting, & McPherson, Brian. Probabilistic Risk Assessment of CO2 Trapping Mechanisms in a Sandstone CO2-EOR Field in Northern Texas, USA. United States. doi:10.1016/j.egypro.2017.03.1581.
Jia, Wei, Pan, Feng, Dai, Zhenxue, Xiao, Ting, and McPherson, Brian. Fri . "Probabilistic Risk Assessment of CO2 Trapping Mechanisms in a Sandstone CO2-EOR Field in Northern Texas, USA". United States. doi:10.1016/j.egypro.2017.03.1581. https://www.osti.gov/servlets/purl/1557749.
@article{osti_1557749,
title = {Probabilistic Risk Assessment of CO2 Trapping Mechanisms in a Sandstone CO2-EOR Field in Northern Texas, USA},
author = {Jia, Wei and Pan, Feng and Dai, Zhenxue and Xiao, Ting and McPherson, Brian},
abstractNote = {This study employs a polynomial chaos expansion (PCE) technique to develop the reduced order models (ROMs) integrated with the Monte Carlo simulations to quantify uncertainties of CO2 storage associated with enhanced oil recovery (EOR) in a commercial-scale CO2-EOR field. The Morrow B sandstone at the Farnsworth Unit (FWU) EOR field in northern Texas was selected as a case study. A 3-D reservoir model, including simulation of a five-spot injection/production well pattern, was constructed based on the data from well logs and cores, and an updated seismic interpretation in the FWU. Porosity and permeability were considered as sources of uncertainty. The 1000-realization heterogeneous random fields of porosity and permeability were generated based on the variogram analysis on the core measurements of the FWU. Three model outputs of interest include the amount of CO2 trapped by three trapping mechanisms, i.e. hydrodynamic trapping, oil dissolution trapping, and aqueous dissolution trapping. The total of 25 runs were conducted with the simulations of a 20-year CO2-EOR period, and a 20-year monitoring period to develop the ROMs between uncertain model input parameters (i.e., porosity and permeability in this study) and model outputs at the end of simulation for each grid cell using PCE approach. The high coefficient of determination (R2) and small normalized root mean square error (NRMSE) between the simulated (using reservoir modeling) and predicted (using ROMs) CO2 storage indicate that the ROMs are acceptable and reliable to be used for the predictions. Given the 1000 Monte Carlo samplings of the model input parameters, cumulative distribution functions (CDFs) and uncertainty bounds (10th and 90th percentiles) of model outputs were estimated based on ROMs. At the end of simulation, the most injected CO2 at the FWU was stored by hydrodynamic trapping (between 121,400 and 166,860 tonnes), followed by oil dissolution trapping (between 55,303 and 76,816 tonnes), and aqueous dissolution trapping (between 1979 and 2751 tonnes).},
doi = {10.1016/j.egypro.2017.03.1581},
journal = {Energy Procedia},
issn = {1876-6102},
number = C,
volume = 114,
place = {United States},
year = {2017},
month = {8}
}

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