Reservoir Characterization: Electromagnetic Imaging of CO2 for EOR Processes
Lawrence Livermore National Laboratory is currently involved in a long term study using time-lapse multiple frequency electromagnetic (EM) imaging at a carbon dioxide (CO{sub 2}) enhanced oil recovery (EOR) site in the San Joaquin Valley, California. The impetus for this proposed research project is to develop the ability to image subsurface CO{sub 2} during EOR processes while simultaneously discriminating between background heavy petroleum and water deposits. Using field equipment developed at Lawrence Livermore National Laboratory in prior imaging studies of EOR water and steam injection, this research uses multiple field deployments to acquire subsurface image snapshots of the CO{sub 2} injection and displacement. Laboratory research, including electrical and transport properties of fluid and CO{sub 2} in saturated materials, uses core samples from drilling, as well as samples of injection and formation fluid provided by industrial partners on-site. Our two-fold approach to combine laboratory and field methods in imaging a pilot CO{sub 2} sequestration EOR site using the cross-borehole EM technique is to (1) improve the inversion process in CO{sub 2} studies by coupling field results with petrophysical laboratory measurements and (2) focus on new gas interpretation techniques of the field data using multiple frequencies and low noise data processing techniques. This approach is beneficial, as field and laboratory data can provide information on subsurface CO{sub 2} detection, CO{sub 2} migration tracking, and the resulting displacement of petroleum and water over time. While the electrical properties of the brine from the prior waterflooding are sharply contrasted from the other components, the electrical signatures of the formation fluid (oil) and CO{sub 2} are quite similar. We attempt to quantify that difference under multiple conditions and as a function of injection time. We find that the electrical conductivity signature difference increases over time and we should thus expect to discriminate CO{sub 2} as a function of time based on the time scales calculated from linear extrapolation of laboratory data.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 15002021
- Report Number(s):
- UCRL-JC-150551; TRN: US200408%%41
- Resource Relation:
- Conference: Society of Petroleum Engineers-Department of Energy 13th Symposium on Improved Oil Recovery, Tulsa, OK (US), 04/13/2002--04/17/2002; Other Information: PBD: 14 Oct 2002
- Country of Publication:
- United States
- Language:
- English
Similar Records
Electromagnetic Imaging of CO2 Sequestration at an Enhanced Oil Recovery Site
Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques