skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

This content will become publicly available on June 24, 2020

Title: Characterization of CO 2 storage and enhanced oil recovery in residual oil zones

Abstract

Residual oil zones (ROZs) are reservoirs in which oil is swept over geologic time period and exists at residual saturation. The oil in such reservoirs cannot be commercially exploited using conventional oil recovery methods as the oil exists at residual oil saturation. Instead, enhanced oil recovery methods such as CO 2 injection are required. Recently, ROZs have been increasingly studied as potential CO 2 storage targets. In spite of increased interest in ROZs, there are significant gaps in the knowledge of parameters and processes that impact CO 2 storage and oil recovery. In this work, we identify key geologic and operational characteristics that affect CO 2 storage capacity and oil recovery potential by performing Monte Carlo simulations and sensitivity analysis. In addition to CO 2 storage capacity, we also characterize the long-term CO 2 fate in ROZs. The distinction of CO 2 storage in ROZs from conventional oil reservoirs and saline aquifers are also characterized. Furthermore, predictive models based on machine learning techniques are developed to estimate CO 2 storage and oil production potentials for ROZs. The applicability of the predictive models is demonstrated for five ROZs in the Permian Basin.

Authors:
ORCiD logo [1]; ORCiD logo [1]
  1. 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 Office of Fossil Energy (FE)
OSTI Identifier:
1530797
Report Number(s):
LA-UR-18-30868
Journal ID: ISSN 0360-5442
Grant/Contract Number:  
89233218CNA000001
Resource Type:
Accepted Manuscript
Journal Name:
Energy (Oxford)
Additional Journal Information:
Journal Name: Energy (Oxford); Journal Volume: 183; Journal Issue: C; Journal ID: ISSN 0360-5442
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Earth Sciences

Citation Formats

Chen, Bailian, and Pawar, Rajesh J. Characterization of CO2 storage and enhanced oil recovery in residual oil zones. United States: N. p., 2019. Web. doi:10.1016/j.energy.2019.06.142.
Chen, Bailian, & Pawar, Rajesh J. Characterization of CO2 storage and enhanced oil recovery in residual oil zones. United States. doi:10.1016/j.energy.2019.06.142.
Chen, Bailian, and Pawar, Rajesh J. Mon . "Characterization of CO2 storage and enhanced oil recovery in residual oil zones". United States. doi:10.1016/j.energy.2019.06.142.
@article{osti_1530797,
title = {Characterization of CO2 storage and enhanced oil recovery in residual oil zones},
author = {Chen, Bailian and Pawar, Rajesh J.},
abstractNote = {Residual oil zones (ROZs) are reservoirs in which oil is swept over geologic time period and exists at residual saturation. The oil in such reservoirs cannot be commercially exploited using conventional oil recovery methods as the oil exists at residual oil saturation. Instead, enhanced oil recovery methods such as CO2 injection are required. Recently, ROZs have been increasingly studied as potential CO2 storage targets. In spite of increased interest in ROZs, there are significant gaps in the knowledge of parameters and processes that impact CO2 storage and oil recovery. In this work, we identify key geologic and operational characteristics that affect CO2 storage capacity and oil recovery potential by performing Monte Carlo simulations and sensitivity analysis. In addition to CO2 storage capacity, we also characterize the long-term CO2 fate in ROZs. The distinction of CO2 storage in ROZs from conventional oil reservoirs and saline aquifers are also characterized. Furthermore, predictive models based on machine learning techniques are developed to estimate CO2 storage and oil production potentials for ROZs. The applicability of the predictive models is demonstrated for five ROZs in the Permian Basin.},
doi = {10.1016/j.energy.2019.06.142},
journal = {Energy (Oxford)},
number = C,
volume = 183,
place = {United States},
year = {2019},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on June 24, 2020
Publisher's Version of Record

Save / Share: