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Record W3207228014 · doi:10.2118/206403-ms

Electromagnetic Induction Heating for Bitumen Recovery: A Case Study in Athabasca Oil Sands

2021· article· en· W3207228014 on OpenAlex
Ahmed Sherwali, Mehdi Noroozi, William G. Dunford

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSPE Russian Petroleum Technology Conference · 2021
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOil sandsSteam-assisted gravity drainageAsphaltPetroleum engineeringElectric heatingEnvironmental scienceSaturation (graph theory)Steam injectionEnhanced oil recoveryHeat exchangerGeologyMaterials scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract This paper demonstrates how electromagnetic induction heating is used for bitumen recovery from the Athabasca oil sands in Alberta with minimal external water requirements. The paper addresses the setup requirements and the necessary parameters for this method to achieve an economic energy to oil ratio. An iterative process is followed to couple the heat rate generated by electromagnetic induction heating to the reservoir model over a defined period. The reservoir model represents a 33 meter payzone with properties for the lower McMurray formation in an area north of Fort McMurray within the Athabasca oil sands deposit. Several scenarios are extensively explored to reach the most practical and feasible setup for oil recovery. The process enables operators to monitor and control reservoir pressure and temperature, liquid production, and energy to oil ratio to maximize recovery from oil sands and heavy oil reservoirs. The results show an expected ultimate oil recovery factor of +70% with an average energy to oil ratio that is lower than the average ratio associated with steam assisted gravity drainage. It is observed that the amount of energy required by the process correlates with water saturation in the near wellbore region, higher water saturation levels are preferred for enhanced oil recovery. It is also noticed that majority of the electromagnetically induced heat rate is generated in the near wellbore region vaporizing any existing water in that region, which eventually slows down the heating process. However, water injection improves the heat convection further into the reservoir, and therefore is essential for establishing a steam chamber using this method. Nevertheless, the volume of injected water required to establish a steam chamber is comparable to the overall volume of water produced from the reservoir, and thus minimal external water is necessary in this process. Moreover, the method is emissions free because heat is generated in the reservoir using an electrically powered downhole inductor (patent pending) that transfers electromagnetic energy to heat. In conclusion, this novel method shows high potential for responsible oil recovery from oil sands and heavy oil reservoirs while meeting economic and environmental expectations. This paper presents the use of a novel clean energy technology to recover bitumen from the Athabasca oil sands in Alberta. Furthermore, the technology is of high value to oil production from heavy oil reservoirs around the world and therefore provides large benefits to the energy industry.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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