Managing Risk in a Thermal Oil Sands Development Project Through Appropriate Technical and Well Operating Design
Bibliographic record
Abstract
Abstract Oil sands bitumen deposits in western Canada represent the third largest hydrocarbon resource in the world and with most requiring in-situ recovery technology, the safe and environmentally-responsible development of this resource is a key opportunity for Canada and the energy industry. Shell Canada Energy has operated thermal wells in Alberta for over 50 years in a number of different, steam- or other energy-based, recovery projects. Facing an ever-increasing regulatory demand for thermal wells that will provide safe long-term operation and stable hydraulic isolation from the thermal zone after abandonment, while meeting Shell's operating principles in protecting groundwater and air and a minimized surface footprint, the technical demands to achieve this continue to grow. The key to overall technical success and reliable well integrity has been a systematic understanding of the parameters that lead to an appropriate and safe casing design, despite the need to operate the well casing at above-yield conditions. Through a combination of controlled materials testing, evaluation of full-scale connection behaviour under dynamic live conditions, and well monitoring during the operating phase, Shell Canada has been able to develop a comprehensive knowledge base over the past years that has enabled it to achieve a near-zero well failure rate. This has been complemented by a comprehensive well integrity monitoring program that not only allows periodic confirmation of mechanical integrity of well components, but also detection of inter-well formation anomalies that may lead to well failure or loss of hydraulic isolation if left unidentified. The know-how will be leveraged in the Carmon Creek thermal development project which is currently in detailed engineering design and, if approved, will start with two back-to-back development phases, each with a nominal target oil production rate of 40,000BPD. Background As defined today, the Carmon Creek project will consist of phased development of a very large oil sand deposit requiring in-situ recovery technology. The recovery process will utilize a combination of cyclic steam stimulation (CSS) and steam drive (SD) processes to mobilize and produce bitumen from the reservoir, which is located approximately 575m below surface. Wells will be drilled directionally from surface pads containing up to 48 operating and two observation wells (Figure 1). Aside from the wells, the surface pads will also contain associated facilities to produce and test fluids, and pipelines for steam and produced fluids / gases to/from the pad respectively. Co-generation will be used for power generation and steam production, using recycled produced water for steam and natural gas as fuel (Figure 2). Beam lift will be used for producing the wells when artificial lift is required.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".