Reservoir Simulation Modeling of the Mature Cold Lake Steaming Operations
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Bibliographic record
Abstract
Abstract While Imperial Oil continues to expand its heavy oil in situ thermal operations at Cold Lake (Fawcett et al., 2011), some cyclic steam stimulation (CSS) wells are evolving to a mature (late life) stage after decades of successful operation. One strategy that has been used in Cold Lake to improve recovery beyond CSS is to implement injector-only-infill (IOI) wells, targeting the cold reservoir region isolated from the CSS depleted zones. The cyclic IOI process can transition to a continuous, low pressure operation; i.e. infill steamflooding. A three year field trial at Cold Lake pads H01/H02 has demonstrated that an oil recovery level of 65% can be achieved by converting mature CSS areas to an infill steamflood (Stark, 2011). During the course of the trial operation and the subsequent commercial deployment of infill steamflooding, significant reservoir simulation studies have been conducted. Simulation has played an important role in providing a physics-based understanding of the infill steamflood process at Cold Lake by enhancing the understanding of how gravity drainage, inter-well communication, and out-of-pattern steam migration play key roles in the steamflooding recovery process. This paper focuses on validation of the reservoir simulation models through comparison to a variety of field performance data types (e.g. well production data, production well temperature logs). Optimization of the infill steamflood process remains a key focus area for maximizing oil recovery at Cold Lake with reservoir simulation providing guidance on various improvement opportunities including steam injection strategy, infill well and production well completion strategy and mitigation of out-of-pattern steam migration.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it