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Record W3120974249 · doi:10.11575/prism/38540

Energy Recovery from Oil Sands Reservoirs

2021· dissertation· en· W3120974249 on OpenAlexaboutno aff
Jingyi Wang

Bibliographic record

VenuePRISM (University of Calgary) · 2021
Typedissertation
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsOil sandsPetroleum engineeringEnvironmental scienceEnergy (signal processing)Natural resource economicsEnvironmental planningWaste managementEnvironmental resource managementGeologyGeographyEngineeringEconomicsArchaeologyAsphalt

Abstract

fetched live from OpenAlex

Alberta's oil sands are the third largest proven crude oil reserve in the world, after Saudi Arabia and Venezuela. The proven reserve is ~165.4 billion barrels. At original reservoir conditions, for in-situ methods, the bitumen is too viscous to extract directly with viscosities of the order of hundreds of thousands to millions of centipoise. To extract bitumen via in-situ recovery processes, the bitumen's viscosity must be lowered to less than 20 cP. In all current commercial oil sands recovery processes, this is done by injected high pressure and temperature saturated steam into the reservoir. One such process, Steam-Assisted Gravity Drainage (SAGD), has been proven to produce bitumen, but due to steam generation has high emissions intensity with large energy requirements. The research presented here studied the SAGD process from multiple angles. The first study is focused on the edge of steam chamber where both SAGD and Steam and Gas Push (SAGP) processes were compared to understand the impact of non-condensable gas on heat transport at the edge of the chamber. The second approach uses a detailed compositional model to exam the time scales for steam and bitumen flow within the depletion chamber. The approach used for multiple steam and multiple bitumen components is novel. The third study examined the instantaneous steam-to-oil ratio behavior when the steam chamber was exposed to different reservoir features. The last study explored the recovery of heat energy from post-SAGD chambers. The analysis reveals the following results. 1. non-condensable gas does improve the thermal efficiency of SAGD, but it changes the behaviour of the edge of the chamber by creating a more extensive depletion zone at the edge of the chamber. 2. the time scales for steam flow and bitumen mobilization, drainage, and production can be weeks to months to years depending on the stage of the process. This speaks to the 'thermal momentum' that is established in the reservoir during the process. 3. The SOR, in particular, the instantaneous SOR provides a signal that can be used to identify reservoir features. This could be used with multiple SAGD well pairs to determine reservoir features across pads. 4. A large fraction of the injected heat energy in the reservoir remains in the reservoir rock (sand grains) and the overburden and understrata. However, it is possible to extract a significant fraction of the energy remaining in the reservoir after SAGD operations have finished. This should be explored in the field since this provides a means to raise the overall energy efficiency of SAGD.

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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.182
Teacher spread0.177 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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