CO2 Injection in the Weyburn Field of Canada: Optimization of Enhanced Oil Recovery and Greenhouse Gas Storage With Horizontal Wells
Bibliographic record
Abstract
Abstract Recently, a billion-dollar CO2 injection project has been launched to increase oil recovery in the Weyburn field of Canada. Initially, the project will use 5000 tonnes of CO2 daily in 19 patterns. The background economic calculations use the assumption that miscibility will be achieved and a steady supply of CO2 at a cost of $35/tonne will be available. This paper provides detailed results of a comprehensive reservoir simulation study using a fully compositional model, in order to optimise the pattern and injection/production strategies. The prototype reservoir models developed are by integrating geologic and petrophysical data available in the literature (1960-1998) for the Weyburn unit, in the southeastern part of Saskatchewan, Canada. The models provide successful history matching, optimise secondary and tertiary recovery schemes, predict an incremental oil recovery through improved oil recovery, and give an estimate of the subsurface storage capacity of greenhouse gases (GHG). The validity of the models developed is evident from the agreement obtained and the conclusions drawn from these diverse data sources that enabled a successful history match of the fluid movement in the reservoir. The models developed are robust in nature and helped determine key parameters controlling miscible CO2 flood. The effects observed due to the contaminated gas stream highlight several of the significant unexplained phenomena, faced by the industry. They are: role of impurities in controlling mobility of the injected gas, effect of impurities in the GHG stream, effect of the loss of miscibility, effect of gas injection directly into the bottomwater zone and the effect of bottomwaters transmissivity on oil recovery. A technical conflict is encountered towards the optimal operating conditions for simultaneous objectives of higher recovery and higher CO2 storage. In this study, horizontal injection wells have proved to be efficient for CO2 flooding process to improve recovery while increasing the storage of anthropogenic CO2. Twenty-one different scenarios for two different schemes have been simulated and investigated simultaneously for storage and recovery. The incremental recovery is related to the flood injection operating strategies employed, introducing back pressure on the reservoir through injectors and producers. The CO2 flood front is controlled through horizontal well adjusting pressure, simultaneously adjusting water injection in the offsetting vertical injection wells and holding back pressure on the associated production wells. Efficient back pressure, achieved is by limiting high operating bottom hole pressure of the producers corresponding to those of injectors that helped maximise the vertical sweep. In addition, opting GOR strategy, location of the horizontal well, optimal injection rates helped to achieve conformance within the reservoir that enabled one to overcome the conflict of achieving the simultaneous objectives.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".