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Record W1999209065 · doi:10.2118/117693-ms

Electro-Magnetic Heating in Viscous Oil Reservoir

2008· article· en· W1999209065 on OpenAlex
Swapan K. Das

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Thermal Operations and Heavy Oil Symposium · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPetroleum engineeringOverburdenViscosityProcess (computing)MechanicsSteam injectionThermalResistorJoule heatingMagnetic fieldResistive touchscreenMaterials scienceEnvironmental scienceGeologyComputer scienceElectrical engineeringVoltageThermodynamicsGeotechnical engineeringEngineeringPhysicsComposite material

Abstract

fetched live from OpenAlex

Abstract Formation resistive heating, commonly known as EM (Electro-Magnetic) heating, has been considered as a potential thermal recovery method in the viscous oil reservoirs for almost three decades. In situ viscosity reduction by the heat generated in the formation helps in the recovery process. The formation acts as a resistor in the current flow path. Numerous patents and reports have been published on this. Application in deep reservoir and negligible heat loss in the overburden, are the two most important features of this thermal recovery process. There are examples of few pilots in Canada, Brazil and elsewhere. This also has been proposed as an option to accelerate SAGD start up. This paper presents the limitation of EM heating in the formation and its applicability in few viscous oil reservoirs. It appears that in the EM heating process, heat penetration is significantly lower than that of a steam based process. Simulation of electrical heating in the simulator is tricky. The amount of estimated heat input is very sensitive to grid refinement. In reality, there is a potential for generating hot spots at the electrodes which was reported to be one of the reasons for failures in the field applications.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.843

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 integrity0.0000.000
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 head0.016
GPT teacher head0.251
Teacher spread0.235 · 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