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Record W2060548423 · doi:10.2118/117700-ms

In-situ Water Vaporization Improves Bitumen Production During Electrothermal Processes

2008· article· en· W2060548423 on OpenAlex
Jie Wang, Bruce C. W. McGee, Apostolos Kantzas

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.

Bibliographic record

VenueInternational Thermal Operations and Heavy Oil Symposium · 2008
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
FundersCanada Research Chairs
KeywordsOil sandsAsphaltSteam-assisted gravity drainagePetroleum engineeringSteam injectionVaporizationEnvironmental scienceOil fieldEnhanced oil recoveryThermal energyWaste managementMaterials scienceGeologyEngineeringChemistry

Abstract

fetched live from OpenAlex

Abstract Thermal methods for heavy oil and bitumen recovery include the injection of steam as in the SAGD (Steam Assisted Gravity Drainage), CSS (Cyclic Steam Stimulation), and steam flooding processes. Thermal energy increases the temperature of the oil, reducing its viscosity and thereby allowing it to flow efficiently towards a production well. The electro-thermal process is an alternative (possibly a compliment) to steam injection processes. With ever-increasing natural gas prices, or corresponding reduction of natural gas supply, electro-thermal processes can be economically competitive compared to other thermal methods. An optimized electrothermal process can bring over 75% of heavy oil or bitumen to the surface as demonstrated by a recent field pilot in the Athabasca oil sands. This study aims at optimizing electrothermal processes by vaporizing water in-situ. The Computer Modeling Group (CMG) reservoir simulation software is used to perform a series of preliminary simulation studies of electro-thermal heating in the Athabasca oil sands. First of all, the incremental oil recovery by vaporization is estimated based on a three block conceptual model. Secondly, a field scale model is set up to evaluate the effect of electrode spacing, water injection rate and electrical heating rate on the ultimate bitumen recovery. A statistic tool is used to analyze the simulation results in order to spot the optimum condition for maximizing bitumen production with water vaporization in-situ. Simulation results showed that the incremental recovery brought by the water vaporization could be as high as 25% OOIP for Athabasca oil sands reservoirs based on the conceptual model. A sensitivity study on the field scale model, showed that the combination of medium electrical heating rate, low water injection rate, and small electrode spacing can maximize bitumen production economically with mild water vaporization in-situ. The study demonstrated a promising technique for the future heavy oil / bitumen production. It also showed that electro-thermal processes could be operated independently and produce considerable amount of bitumen economically.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.516

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 communication0.0000.001
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 head0.005
GPT teacher head0.211
Teacher spread0.205 · 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