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Record W2025412950 · doi:10.2118/06-09-05

Optimization of Steam Assisted Gravity Drainage in McMurray Reservoir

2006· article· en· W2025412950 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsUniversity of Calgary
FundersUniversity of British ColumbiaUniversity of Minnesota
KeywordsSteam injectionSteam-assisted gravity drainagePetroleum engineeringVapor qualityEnvironmental scienceSaturation (graph theory)Natural gasOverburdenOil sandsThermalMaterials scienceGeologyWaste managementAsphaltEngineeringHeat exchangerGeotechnical engineeringMechanical engineering

Abstract

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Abstract Many field tests of the steam assisted gravity drainage (SAGD) process have been conducted and have shown that the process is a technically effective one at extracting oil from heavy oil and bitumen reservoirs. However, it has not been firmly established whether the technology is operated at optimized conditions to yield maximum economic returns. This is especially important because typically SAGD depends on the combustion of natural gas to generate steam and this is the dominant cost. The cost of natural gas can be significant when natural gas prices are high. This research evaluates the use of a genetic algorithm optimization scheme to control a commercially available thermal reservoir simulator in order to optimize the steam injection strategy to reduce the cumulative oil to steam ratio (cSOR). The reservoir description is typical of that from a low to medium quality Athabasca reservoir. The results show that the injection strategy can be altered to reduce the cSOR up to 50% from a uniform injection pressure strategy to 1 after the steam injection strategy has been optimized. The optimized profile has high steam injection pressure at the beginning of the process before the steam chamber reaches the top of the oil-rich zone. Before the chamber reaches the oil pay, with high injection pressure, the saturation temperature is high and there are no thermal losses to the overburden. After the chamber reaches the top of the formation, the injection pressure is lowered throughout the remainder of the process. This reduction of injection pressure implies that the saturation temperature falls and consequently the losses to the overburden are lowered. Thus the overall thermal efficiency of the process is enhanced. The optimized strategy is compared to processes operating at 1,000 and 2,000 kPa constant injection pressure. Introduction Steam assisted gravity drainage (SAGD) has now been extensively tested and put into commercial production in the Athabasca and Cold Lake regions of Alberta(1–5). The majority of existing SAGD projects are based in Alberta, Canada: more than nine are located in the Athabasca region (the McMurray formation); one in the Peace River region, (the Bluesky formation); four are in the Cold Lake region (the Clearwater formation and the Grand Rapids formation); and, five are in Saskatchewan (the Grand Rapids formation). The SAGD process, shown in Figure 1, was developed by Butler(2) while at Imperial Oil in the late 1970s. The process consists of two aligned horizontal wellbores. Steam is injected into the top one, whereas reservoir fluids are produced from the bottom one. The process is non-cyclic; that is, steam is continuously injected and fluids are continuously produced. Around and above the injection well, a steam chamber grows. The injected steam flows into the steam chamber and eventually comes into contact with oil sand at its edge. The steam then releases its latent heat to the oil sand, the oil heats up, its viscosity drops, and it flows (with water condensate) under gravity down the inclined chamber edge to the production well.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.223
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it