MétaCan
Menu
Back to cohort
Record W2604243554 · doi:10.2118/185728-ms

Comparison of Steam and Polymer Injection for the Recovery of Heavy Oil

2017· article· en· W2604243554 on OpenAlex
Eric Delamaide

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSPE Western Regional Meeting · 2017
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSteam injectionPetroleum engineeringEnhanced oil recoveryOil fieldFlood mythEnvironmental scienceWater injection (oil production)Flooding (psychology)Oil viscosityCapital costProcess engineeringViscosityWaste managementEngineeringMaterials science

Abstract

fetched live from OpenAlex

Abstract Steam injection (including cyclic steam and SAGD) has long been recognized as the favored recovery method for heavy oil, with applications in many fields around the world in particular in California and Canada. More recently, polymer flooding has also become a relatively well accepted method to increase production and recovery in heavy oil fields. Numerous successful pilots have been reported these last few years and field expansions are currently ongoing in Canada, Oman, China and Albania for instance but surprisingly enough, there has been to the best of the author's knowledge no such application in the US. Both steam and polymer injection have their advantages and their limitations and simple screening criteria have been developed by several authors, however there has never been a detailed comparison of the two methods and this is what this paper proposes to do. The pros and cons of both steam injection and polymer flood are reviewed in light of fundamentals and field experience: reservoir depth, thickness, oil viscosity, expected recovery, water usage and economics of both processes (in particular capital requirements) are all addressed. Guidelines are then provided for the selection of the right process given the reservoir conditions and the capital constraints. Results show that while steam injection can achieve much higher recovery than polymer flood and is also applicable in much higher oil viscosity, polymer flooding is not limited by depth or reservoir thickness, has lower operating costs and is also less capital intensive. Thus, there is a large opportunity to develop heavy oil reservoirs using polymer where steam injection is not possible. Delamaide and Euzen (Delamaide & Euzen, 2014) estimated that in the US alone, over 5 billion bbl of oil could be targeted by this technique. This paper will provide guidance to engineers who need to select the optimum Enhanced Oil Recovery method to apply in given heavy oil fields, going beyond the standard screening criteria. It will also increase awareness on the possibilities of polymer flooding in some reservoirs, with a significant potential target not only in the US but also worldwide.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.308

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 head0.037
GPT teacher head0.309
Teacher spread0.272 · 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