Closing Date: January 6, 2022
This Research Opportunity will be filled depending on the availability of funds. All application materials must be submitted through USAJobs by 11:59 pm, US Eastern Standard Time, on the closing date.
Background: A residual oil zone (ROZ) is an interval of reservoir rock containing immobile oil that cannot be produced by primary and secondary recovery methods due to oil saturation levels that may be similar to a waterflooded oil reservoir. However, as demonstrated in multiple recent oil field projects (e.g. Kuruskraa and others, 2017), incremental oil can be produced from ROZs by injecting carbon dioxide (CO2) associated with the enhanced oil recovery (CO2-EOR) process. Moreover, if anthropogenic CO2 is injected and stored within the ROZ interval, the carbon intensity or the amount of CO2 emitted from the use of the produced oil is usually much less than the oil produced by traditional methods. Oil produced through CO2-EOR from ROZs may even store more CO2 than is emitted from the use of the produced oil (negative-emission oil) during the first several years of production (Núñez-López and Moskal, 2019). Residual oil zones are important in the context of sustaining energy independence and the urgency to apply climate change mitigation processes to reduce emissions of anthropogenic greenhouse gases. Therefore, exploring ROZ resources and assessing their CO2-EOR and CO2 storage potential may offer significant opportunities for anthropogenic CO2 sequestration and for the decarbonization of oil by achieving a balance between CO2 emissions from oil use and the ROZ sinks utilized to reduce and remove these emissions.
Description of the Research Opportunity: Currently, there are several knowledge gaps to successfully identify and assess ROZ potential for oil recovery and CO2 sequestration. A first step should include identification of locations of ROZ fairways, area and thickness of ROZ intervals, oil saturation and porosity, as well as incremental oil recovery and CO2 storage factors. One of the largest knowledge gaps that affects all regional ROZ resource evaluations is the lack of geologic understanding of the formation of ROZs in relation to the geologic history of different basins, including tectonics, hydrodynamic activity, and structural features that are affected by these events. Therefore, the candidate needs to evaluate selected basins to identify individual reservoirs and/or potential ROZ fairways using various indicators. Such identification should also delineate the area and thickness of the ROZ intervals, as well as their reservoir rock properties, such as oil saturation and porosity for oil recovery and associated CO2 storage. The candidate will be expected to develop novel approaches using USGS and publicly available data sources, such as well logs, well data or other data that may be obtained using collaborative research agreements, to estimate reservoir properties of the ROZ intervals.
Considering that data may be incomplete, or relationships may be complex, it may be advantageous to leverage from machine learning methods to identify ROZs and to predict properties using proxy data and other indicators of ROZs that are determined from regional basin studies. A machine learning system may be helpful to identify ROZs and to estimate porosity and fluid saturations when data for direct analysis methods are not available. The candidate will need to explore the possibility of using such an approach for the goals of the study and will be responsible for selecting the best machine learning system and any indicators.
Probabilistic volumetric assessments are also dependent on the recovery and CO2 utilization factors for site specific conditions, and when fields are to be managed using different production and injection designs. The candidate will perform necessary research for development of a life-cycle-analysis approach to optimize oil production while maximizing CO2 storage to ensure that the produced oil will be net-zero carbon for as long as possible from selected fields of an initial basin case study. Various modeling tools, correlations built using literature data or leveraging from injection and production data, or others that the candidate will find more applicable, can be options that the candidate may need to consider and develop a quantitative approach.
Interested applicants are strongly encouraged to contact the Research Advisor(s) early in the application process to discuss project ideas.
Kuuskraaa, V., Petrusak, R., Wallace, M., 2017. Residual oil zone “fairways” and discovered oil Resources: Expanding the options for carbon negative storage of CO2. Energy Procedia 114, 5438 – 5450, https://doi.org/10.1016/j.egypro.2017.03.1688.
Nuñez-López, V., Moskal, E., 2019, Potential of CO2-EOR for near-term decarbonization: Frontiers in Climate, v. 1, article 5, 14 p. https://doi.org/10.3389/fclim.2019.00005.
Proposed Duty Station: Reston, Virginia
Areas of PhD: Geology, physical science engineering, or related fields (candidates holding a Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).
Qualifications: Applicants must meet the qualifications for: Research Geologist
(This type of research is performed by those who have backgrounds for the occupations stated above. However, other titles may be applicable depending on the applicant's background, education, and research proposal. The final classification of the position will be made by the Human Resources specialist.)
Human Resources Office Contact: Audrey Tsujita, 916-278-9395, firstname.lastname@example.org