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Record W4212862532 · doi:10.9734/jerr/2021/v21i1017497

Critical Review of Polymer Flooding in Daqing Field and Pelican Field: Case Studies of the World’s Largest Polymer Flooding in Light and Heavy Oil Reservoirs, Respectively

2021· article· en· W4212862532 on OpenAlexaboutno aff
Okechukwu Ezeh, Sunday Sunday Ikiensikimama, Onyewuchi Akaranta

Bibliographic record

VenueJournal of Engineering Research and Reports · 2021
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsFlooding (psychology)Polymer solutionPetroleum engineeringEnvironmental scienceOil fieldPolymerGeologyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Aim: Polymer flooding is a promising chemical enhanced oil recovery. Originally it was thought that polymer flooding was not economical. The polymer flooding in Daqing field China has proved otherwise. After that, it was thought that polymer flooding could only be successful in light oil reservoirs, but then polymer flooding was implemented in Pelican field in Canada on a large scale and recorded success. Methodology: The methodology employed was to review polymer flooding from inception, beginning from the work of Kingsley Detling in 1944 who got a patent in the USA to late 1970’s, thus early history of polymer flooding was a good insight for this paper. The mechanism of polymer flooding was also captured; improving the mobility ratio of water with a water soluble polymer is what helps for better sweep efficiency. The successful polymer flooding in Daqing field China has made many companies to understand this technology and go for polymer flooding. Polymer flooding of Daqing field has helped China’s oil and gas industry. Polymer flooding is now used to recover heavy oil especially for deep reservoirs with thin pay zone. Pelican field in Canada has carried out the largest polymer flooding implementation in the world and has proven that polymer flooding can be used for heavy oil and given a new screening parameter for polymer flooding. Results: This review has captured the critical aspects of polymer flooding both in light oil reservoirs-Daqing field, China and heavy oil reservoirs-Pelican field, Canada. Conclusion: This review has proven that polymer flooding is a promising Chemical Enhanced Oil Recovery technology in both light oil and heavy oil reservoirs and it is used to increase the ultimate recovery of some fields and could help any country to remain relevant in the oil and gas sector. Using polymer flooding to recover heavy oil proves more efficient and more economical. Because, polymer flooding does not require a lot of heat as in thermal flooding, there is reduction in global green house gas effect. Recommendation: It is recommended that companies use polymer flooding to recover their oil from light oil reservoirs and most importantly increase production and recovery in heavy oil fields.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.356
Teacher spread0.323 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2021
Admission routes1
Has abstractyes

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