Developing SAGD Operating Strategy using a Coupled Wellbore Thermal Reservoir Simulator
Bibliographic record
Abstract
Abstract The MacKay River Project is located approximately 60 kilometers northwest of Fort McMurray, Alberta, Canada. The development consists of 25 well pairs and facilities to produce 30,000 bopd of bitumen from the McMurray Formation of the Athabasca Oil Sands Deposit over a 25 year life. An in-situ recovery process referred to as Steam Assisted Gravity Drainage (SAGD) is used. The SAGD process utilizes horizontal well pairs, drilled 5m vertically apart, to provide continuous steam injection into the upper well with continuous fluid production from the lower well. The initial phase of the MacKay River Project consists of two production pads that supply steam to the injection wells and accept return fluids from the production wells. Produced fluids are processed at the MacKay River central facility where the bitumen is shipped to market via an insulated pipeline. Solution gas is recovered for use in steam generation, while the water is treated and recycled. During the start-up at MacKay River, communication was initiated between each producer and injector by circulating steam in both of the wells. Once the reservoir between the two wells was sufficiently heated and bitumen mobility was evident, a pressure differential was applied between the wells for a short time after which the well pair was converted to SAGD mode. In SAGD mode the upper and lower wells be-came dedicated injection and production wells, respectively. In developing the start-up operating parameters for the MacKay River well pairs, a pseudo-compositional thermal reservoir simulator was used to perform sensitivities to deter-mine the optimum operating strategy. The reservoir properties in the model were imported from a geostatistical model that was developed for the area. A discretized wellbore using the as-drilled trajectory was also implemented in the model. This allowed for the implicit modeling of the pressure and heat transfer dynamics in the wellbore, which are very significant in a SAGD operation. The main objective when developing this strategy was how to initiate communication between the producer and the injector in the optimal time without causing adverse affects on the long term SAGD performance. The variables that were investigated during the operating strategy development included steam circulation rate, steam circulation pressure, the magnitude and timing of pressure differential implementation between the injector and producer and the optimum timing of SAGD conversion. This start-up operating strategy was successfully im-plemented in the field from September to November 2002. Subsequently, the models are being calibrated to the field measured start-up data. Upon completion, these coupled wellbore reservoir models will be used to define the optimal ramp-up operating strategy for the MacKay River SAGD well pairs. This paper will detail the sensitivities conducted and the start-up prediction that were generated through the coupled wellbore reservoir simulator with a comparison to actual field data.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".