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Record W2035326053 · doi:10.2118/137460-pa

Study of Alkaline/Polymer Flooding for Heavy-Oil Recovery Using Channeled Sandpacks

2011· article· en· W2035326053 on OpenAlexafffundabout
Yongge Wu, Mingzhe Dong, Ezeddin Shirif

Bibliographic record

VenueSPE Reservoir Evaluation & Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of CalgaryUniversity of Regina
FundersPetroleum Technology Research CentreNorthwest UniversityCanadian Natural Resources Limited
KeywordsOil in placeResidual oilBrinePetroleum engineeringPermeability (electromagnetism)Saturation (graph theory)PorosityGeologyPetroleumChemistryGeotechnical engineering

Abstract

fetched live from OpenAlex

Summary For heavy oils with viscosities ranging from 1000 to 10 000 mPa·s in western Canada, primary production and waterflood together can recover only 8–15% of original oil in place (OOIP) at their economic limits because of the adverse mobility ratio, severe water channeling, low reservoir pressure, and formation voidage. These heavy oils usually have a relatively high content of acids that can react with alkalis to form in-situ surfactants. The loosely consolidated sandstone formations in which these oils are deposited are characterized by high porosity, high permeability, and low reservoir temperature. These reservoir conditions are favorable for polymer application. Therefore, there is a potential to improve waterflood in these reservoirs by applying alkaline/polymer (A/P) flooding. This paper presents the results of a laboratory study of A/P flooding for heavy-oil recovery, including viscosity measurements, flood tests conducted in channeled sandpacks, residual-resistance-factor (FRR) determination, and residual-oil-distribution tests. A heavy oil with a viscosity of 1,202 cp and an acid number of 1.07 (mg of KOH/g of oil) and produced brine collected from a heavy-oil reservoir in Alberta are used in this study. We found that the distribution of the injected chemical solution within the high-permeability channels leads to the diversion of the subsequently injected chemical solution to low-permeability zones with higher oil saturation because of the formation of blockage in the channel zones. Consequently, pressure buildup during chemical-slug injection is the key to the improvement of displacement efficiency. Flood tests also show that A/P flooding is more efficient than either alkaline flooding or polymer flooding. The optimal formulation for the heavy oil used in this study is 0.4% NaOH + 0.2% Na2CO3 + 1000 mg/L polymer, with a tertiary oil recovery of 25–30% of OOIP above that from waterflooding. Analysis of the results of the residual-oil distributions in the channeled sandpacks at the end of A/P flooding show that A/P flooding can effectively improve the sweep efficiency of waterflooding for the heavy oil.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 head0.094
GPT teacher head0.311
Teacher spread0.217 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations47
Published2011
Admission routes3
Has abstractyes

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