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Record W1982286368 · doi:10.2118/165264-ms

Case Study of the Mannville B ASP Flood

2013· article· en· W1982286368 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSPE Enhanced Oil Recovery Conference · 2013
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsHusky Energy (Canada)
Fundersnot available
KeywordsFlood mythInfillEnvironmental scienceOil in placeDrillingPetroleum engineeringWater injection (oil production)Hydrology (agriculture)Water resource managementGeologyEngineeringGeographyCivil engineeringPetroleumGeotechnical engineeringArchaeology

Abstract

fetched live from OpenAlex

Abstract In May 2006, the Warner Mannville B ASP flood was the first field wide ASP flood implemented in Canada. The objective was to successfully implement a commercially viable ASP flood. In this project produced water is treated and reinjected into the reservoir. As of December 2012, an incremental 420 103m3 (2.65 million bbl) of oil has been recovered with an expected total incremental recovery of 777 103m3 (4.89 million bbl), which represents 11.1% of the OOIP. In October 2008, after 0.35 pore volume of ASP injection, the project moved into the Polymer only injection phase. Polymer injection will continue as long as is economically feasible. A comprehensive monitoring and testing program was implemented to evaluate flood response and performance. This allowed for the optimization of the flood through continuous adjustment to flow rates and led to successful infill drilling locations. Many challenges have been encountered during this project, including: silicate scale production, treating issues related to the water quality of the recycled injection water, and loss of injectivity in many injection wells. The challenges were overcome and it has been an economic success with a cumulative positive cashflow within 5 years. The results of this flood have led to the implementation of an additional four floods. The lessons learned from this project have improved numerous aspects of how future floods are designed and implemented.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.548

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)0.0000.000

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 head0.189
Teacher spread0.178 · 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