CO2 Flooding Potential in West-Central Alberta: Generalized BusinessCase of a Medicine River/Gilby Area Mature Waterflooded Reservoir
Bibliographic record
Abstract
Abstract There are several maturing waterfloods in the Medicine River/Gilby region of West-Central Alberta which are operating at high reservoir pressures, and are suitable candidates for enhanced oil recovery (EOR) by CO2 flooding. Potential CO2 supplies also exist in the region from various petrochemical, as well as sour gas and solution gas processing plants. A prototype reservoir was selected for a detailed "business case" study. CO2 flooding and geological storage were seen to be feasible in the prototype reservoir based on geological/ reservoir reviews, laboratory testing and reservoir simulation. Economic parameters (payout periods for the investment, rates of return) on risk-weighted basis were moderate in light of front-end capital requirements for extraction, recycle and transportation facilities. The situation would change for the better if regional infrastructure for CO2 capture, extraction and transport is developed. This, in turn, is dependent upon adequate assured demand. On the other hand, demand won't develop unless there is appropriate infrastructure in-place. Fragmented ownership of the resource and of CO2-rich waste gas streams, as well as inertia favouring status quo, are some of the other challenges. We present here a generalized "business case" for illustrating some of the issues of CO2-EOR implementation. Introduction CO2-EOR is receiving increasing attention mainly because of the following emerging trends:Increasing awareness of potential reserves addition by CO2 flooding in mature sedimentary basins such as the Western Canadian Sedimentary Basin (WCSB), based on performance of Weyburn and Joffre Viking CO2 flooding projects in WCSB, and also in various oil fields of West Texas Permian Basin.Growing recognition of the importance of Carbon Capture and Storage (CCS) and anticipated incentives for CCS projects in value-added mode such as EOR.Consensus that the main barrier to widespread implementation of CO2-EOR in Alberta is lack of supply and transportation infrastructure for CO2.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".