Application of Electromagnetic Methods for Reservoir Monitoring with Emphasis on Carbon Capture, Utilization, and Storage

Author:

Barajas-Olalde César1ORCID,Adams Donald C.1,Curcio Ana2ORCID,Davydycheva Sofia3,Klapperich Ryan J.1,Martinez Yardenia3,Paembonan Andri Y.34,Peck Wesley D.1,Strack Kurt3ORCID,Soupios Pantelis5

Affiliation:

1. Energy & Environmental Research Center, 15 North 23rd Street, Stop 9018, Grand Forks, ND 58202, USA

2. Proingeo SA, Agüero 1995 6A, Ciudad Autónoma de Buenos Aires 1425, Argentina

3. KMS Technologies, Inc., 11999 Katy Freeway, Suite 160, Houston, TX 77079, USA

4. Sumatera Institute of Technology, Selatan 35365, Indonesia

5. Department of Geosciences, College of Petroleum Engineering and Geosciences, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia

Abstract

The Controlled-Source ElectroMagnetic (CSEM) method provides crucial information about reservoir fluids and their spatial distribution. Carbon dioxide (CO2) storage, enhanced oil recovery (EOR), geothermal exploration, and lithium exploration are ideal applications for the CSEM method. The versatility of CSEM permits its customization to specific reservoir objectives by selecting the appropriate components of a multi-component system. To effectively tailor the CSEM approach, it is essential to determine whether the primary target reservoir is resistive or conductive. This task is relatively straightforward in CO2 monitoring, where the injected fluid is resistive. However, for scenarios involving brine-saturated (water-wet) or oil-wet (carbon capture, utilization, and storage—CCUS) reservoirs, consideration must also be given to conductive reservoir components. The optimization of data acquisition before the survey involves analyzing target parameters and the sensitivity of multi-component CSEM. This optimization process typically includes on-site noise measurements and 3D anisotropic modeling. Based on our experience, subsequent surveys tend to proceed smoothly, yielding robust measurements that align with scientific objectives. Other critical aspects to be considered are using magnetotelluric (MT) measurements to define the overall background resistivities and integrating real-time quality assurance during data acquisition with 3D modeling. This integration allows the fine tuning of acquisition parameters such as acquisition time and necessary repeats. As a result, data can be examined in real-time to assess subsurface information content while the acquisition is ongoing. Consequently, high-quality data sets are usually obtained for subsequent processing and initial interpretation with minimal user intervention. The implementation of sensitivity analysis during the inversion process plays a pivotal role in ensuring that the acquired data accurately respond to the target reservoirs’ expected depth range. To elucidate these concepts, we present an illustrative example from a CO2 storage site in North Dakota, USA, wherein the long-offset transient electromagnetic method (LOTEM), a variation of the CSEM method, and the MT method were utilized. This example showcases how surface measurements attain appropriately upscaled log-scale sensitivity. Furthermore, the sensitivity of the CSEM and MT methods was examined in other case histories, where the target reservoirs exhibited conductive properties, such as those encountered in enhanced oil recovery (EOR), geothermal, and lithium exploration applications. The same equipment specifications were utilized for CSEM and MT surveys across all case studies.

Funder

U.S. Department of Energy (DOE) National Energy Technology Laboratory

Minnkota Power Cooperativeand the Energy & Environmental Research Center (EERC) of the University of North Dakota

King Fahd University of Petroleum and Minerals

Litica Resources SA

Publisher

MDPI AG

Subject

Geology,Geotechnical Engineering and Engineering Geology

Reference81 articles.

1. IEA (2023, February 01). Energy Technology Perspectives 2023, IEA, Paris. Available online: https://www.iea.org/reports/energy-technology-perspectives-2023.

2. IEA (2023, February 01). Energy Technology Perspectives 2020, IEA, Paris. Available online: https://www.iea.org/reports/energy-technology-perspectives-2020.

3. CO2 storage associated with CO2 enhanced oil recovery: A statistical analysis of historical operations;Azzolina;Int. J. Greenh. Gas Control,2015

4. CO2 Sequestration in Deep Sedimentary Formations;Benson;Elements,2008

5. (2023, January 15). Available online: https://www.netl.doe.gov/carbon-management/carbon-storage/faqs/carbon-storage-faqs.

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