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Record W2560606144 · doi:10.1016/j.petlm.2016.11.005

CO2 flooding strategy to enhance heavy oil recovery

2016· article· en· W2560606144 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.

Bibliographic record

VenuePetroleum · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Regina
FundersPetroleum Technology Research Centre
KeywordsEnhanced oil recoveryPetroleum engineeringFlooding (psychology)Oil in placeEnvironmental scienceOil productionWater floodingBrineLight crude oilChemistryGeologyPetroleum

Abstract

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CO2 flooding is one of the most promising techniques to enhance both light and heavy oil recovery. In light oil recovery, the production pressure in CO2 flooding in general keeps constant in order to maintain the miscibility of injected CO2 and crude oil; while in heavy oil recovery, a depleting pressure scheme may be able to induce foamy oil flow, thus the oil recovery could be further enhanced. In this study, different pressure control schemes were tested by 1-D core-flooding experiments to obtain an optimized one. Numerical simulations were conducted to history match all experimental data to understand the mechanisms and characteristics of different CO2 flooding strategies. For the core-flooding experiments, 1500 mD sandstone cores, formation brine and a heavy oil sample with a viscosity of about 869.3 cp at reservoir condition (55 °C and 11 MPa) were used. Before each CO2 flooding test, early stage water-flooding was conducted until the water cut reached 90%. Different CO2 injection rates and production pressure control strategies were tested through core-flooding experiments. Experimental results indicated that a slower CO2 injection rate (2 ml/min) led to a higher recovery factor from 31.1% to 36.7%, compared with a high CO2 injection rate of 7 ml/min; for the effects of different production strategies, a constant production pressure at the production port yielded a recovery factor of 31.1%; while a pressure depletion with 47.2 kPa/min at the production port yielded 7% more oil recovery; and the best pressure control scheme in which the production pressure keeping constant during CO2 injection period, then depleting the model pressure with the injector shut-in yielded a recovery factor of 42.5% of the initial OOIP. For the numerical simulations study, the same oil relative permeability curve was applied to match the experimental results to all tests. Different gas relative permeability curves were obtained when the production pressure schemes are different. A much lower gas relative permeability curve and a higher critical gas saturation were achieved in the best pressure control scheme case compared to other cases. The lower gas relative permeability curve indicates that foamy oil was formed in the pressure depletion processes. Through this study, it is suggested that the pressure control scheme can be optimized in order to maximize the CO2 injection performance for enhanced heavy oil recovery.

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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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.992

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)0.0130.008

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 head0.013
GPT teacher head0.267
Teacher spread0.255 · 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