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Record W1987455428 · doi:10.2118/165455-ms

A Novel Solvent Injection Technique for Enhanced Heavy Oil Recovery: Cyclic Production with Continuous Solvent Injection

2013· article· en· W1987455428 on OpenAlex
Tao Jiang, Xu Jia, Fanhua Zeng, Yongan Gu

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

Bibliographic record

VenueSPE Heavy Oil Conference-Canada · 2013
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaPetroleum Technology Research Centre
KeywordsInjectorPetroleum engineeringSolventEnhanced oil recoveryOil in placeEnvironmental scienceWater injection (oil production)Oil fieldMaterials scienceChemistryPetroleumGeology

Abstract

fetched live from OpenAlex

Abstract Solvent-based in-situ enhance oil recovery (EOR) techniques are extensively studied to improve oil recovery factors (RFs) for heavy oil reservoirs. Continuous injection, such as vapour extraction (VAPEX), and cyclic injection, such as cyclic solvent injection (CSI) are two main categories of solvent EOR techniques. The production rates of VAPEX are low in field tests. CSI does not show exciting results due to the quick reservoir pressure depletion and the sudden reservoir energy loss, which causes the oil to regain its viscosity. A new enhanced heavy oil recovery technique, cyclic production with continuous solvent injection (CPCSI), is proposed in this paper. In this process, a vapour solvent is continuously injected into the reservoir to maintain reservoir pressure and also supply extra gas drive to flood the diluted oil out through an injector that is located on the top of the reservoir, while a producer, which is located at the bottom of the reservoir, is operated in a shut-in/open cyclic way. A series of experiments have been conducted to validate the CPCSI performance by using different sand-pack models with 4¬-5 Darcy permeability, and saturated with Western Canada heavy oil sample. Gaseous propane is continuously injected through an injector at a constant pressure, which is below the dew point pressure, and producer was operated with a cycle of 50-minute-shut-in/10-minute-open period. Experimental results show that, the oil is diluted and drained down by gravity during shut-in period, then produced in producer opening period by solution gas drive and gas flush. In comparison with VAPEX and CSI, CPCSI offers free gas driving, and still keeps oil diluted in the well opening period and produced by the gas flush. The RFs are up to 85% of OOIP in 1-D tests. Also, shorter height model has highest average production rate in comparison with others. Test results are also validated by 2-D physical model, in which the RF is improved by 11% by using the lateral CPCSI compared with classic lateral VAPEX. Well configurations and the shut-in/open scenarios are key optimization factors that affect CPCSI performance. This work shows that CPCSI could be an alternative optimization production scenario for applying solvent based in-situ EOR techniques for Western Canada heavy oil reservoirs.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.578
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.209
Teacher spread0.197 · 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