The Plains CO2 Reduction (PCOR) Partnership: Progressing Geologic Storage Through Applied Research
Bibliographic record
Abstract
Abstract The Energy & Environmental Research Center (EERC) is focused on solving the world's energy and environmental challenges. Through its Center for Climate Change & Carbon Capture and Storage, the EERC is engaged in research activities in direct support of carbon management. One significant carbon management effort led by the EERC is the Plains CO2 Reduction (PCOR) Partnership. The PCOR Partnership is one of seven regional partnerships established by the U.S. Department of Energy National Energy Technology Laboratory to assess and develop carbon storage opportunities. The PCOR Partnership, comprising state agencies; coal, oil and gas, and other private companies; electric utilities; universities; and nonprofit organizations, covers an area of over 1.4 million square miles in the central interior of North America and includes all or part of nine states and four Canadian provinces. The PCOR Partnership region has stable geologic basins that are ideal storage targets for carbon capture and storage (CCS). These basins have been well-characterized because of commercial oil and gas activities and have very significant CO2 storage capacities. The region's energy industry is evaluating carbon management options including CCS. Many of the region's oil fields could develop carbon dioxide (CO2)-based enhanced oil recovery (EOR) projects if CO2 were more readily available. CO2-based tertiary EOR projects offer a means of developing the expertise and infrastructure required to make geologic CCS a commercial reality. The PCOR Partnership is teaming with industrial partners to conduct two commercial-scale (greater than 1 million tons a year) CCS demonstrations in its region. One of the large-scale tests will demonstrate CO2 storage in a saline formation, while the other will be a combined CCS and EOR demonstration. The sources of CO2 in both demonstrations are natural gas-processing facilities. The commercial-scale demonstration tests are designed to establish the technical and economic efficacy of CCS in the region, and injections are planned to begin between 2012 and 2014 for both projects. INTRODUCTION The Plains CO2 Reduction (PCOR) Partnership is one of seven regional partnerships operating under the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) Regional Carbon Sequestration Partnership (RCSP) Initiative. The PCOR Partnership is led by the Energy & Environmental Research Center (EERC) at the University of North Dakota in Grand Forks, North Dakota, and includes stakeholders from the public and private sector. The PCOR Partnership was established in the fall of 2003. Phase I focused on characterizing CO2 storage opportunities in the region. In the fall of 2005, the PCOR Partnership launched its 4-year Phase II program, which focused on carbon storage field validation projects that were designed to develop the regional technical expertise and experience needed to facilitate future large-scale CCS efforts in the region's subsurface and in terrestrial settings. In the fall of 2007, the PCOR Partnership initiated its 10-year Phase III program, which is focused on implementing two commercial-scale geologic carbon storage demonstration projects in the region. The project sites are located 1) in the Bell Creek oil field in Powder River County in southeastern Montana and 2) near Spectra Energy's Fort Nelson gas-processing facility, situated near Fort Nelson, British Columbia, Canada (Figure 1).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".