Role of Operating Practices on Performance of Waterfloods in Heavy Oil Reservoirs
Bibliographic record
Abstract
Abstract Identification of operating conditions that have been beneficial or injurious to overall performance of past waterfloods in heavy oil reservoirs is the first essential step towards optimization of similar projects in the future. Comparative analyses of performance of various waterfloods in a given region (deposited under similar conditions) can be very instructive to identify such conditions. Insights on performance of waterfloods in heavy oil reservoirs were derived from a comparative evaluation of recent performance history of three selected waterfloods. These waterfloods involved increasing, decreasing and steady water injection rates. It was seen that aggressive injection rates lead to increased oil rates, but at rapidly increasing water cuts. Decreasing water injection rates, on the other hand, lead to low oil rates, but with water cuts increasing relatively more gradually. There is, therefore, an economically optimal water injection rate strategy for each specific situation. Introduction In the current environment of volatile oil prices and economic uncertainties, there is a heightened need for reviewing the cost-effectiveness of ongoing waterflood and improved oil recovery (IOR) operations within the constraints of low incremental costs and risks. Some of the options being pursued include enhanced surveillance, benchmarking of performance against other successful projects in analogous reservoirs, intense characterization and simulation, upgrades to facilities, improvement in injection water quality and selective placement of additional injectors and producers. In viscous fingering-dominated waterfloods, aggressive water injection aggravates water channelling. High injection rates (sub-fracture) lead to high initial oil rates in the short-term, but they subsequently give rise to excessive water channelling which may result in loss of cost-effectiveness of the waterflood and, in some cases, premature abandonment. On the other hand, low injection-production rates (processing rates) in heavy oil waterfloods lead to relatively low oil rates, long payout periods and a long project life. There is, therefore, an optimal processing rate/strategy for each specific situation (based on technical and economic considerations) and, clearly, there is a need for systematically identifying it. Since the 1980s, over 70 waterfloods have been operated in the medium and heavy oil reservoirs of Alberta and Saskatchewan in Western Canada. Waterflooding in these reservoirs involves adverse mobility ratio and viscous fingering/water channelling leading to relatively early water breakthrough. Resulting requirements for handling large amounts of water poses formidable problems. This study was undertaken to explore whether a judicious scheduling of injection and production rates could improve cost-effectiveness of similar operations in the short- and long-term. We examined performance histories of several ongoing waterfloods, and three selected waterfloods are reviewed here. We did not have access to many details on these projects. We believe there is a persuasive case for our hypothesis. It is understood that the field data examined were, by no means, 'controlled' (i.e. there may possibly exist factors other than the ones we focused on in this review, and all cases may not strictly be comparable). Methodology We compared the performance of three selected waterfloods in the heavy oil reservoirs of Southern Alberta; namely, Jenner Upper Mannville O, Jenner Upper Mannville JJJ and Retlaw Mannville D8D.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 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".