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Record W2040060274 · doi:10.2118/166447-ms

Modeling Low Salinity Waterflooding: Ion Exchange, Geochemistry and Wettability Alteration

2013· article· en· W2040060274 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.

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2013
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWettingPetroleum engineeringEnhanced oil recoveryDissolutionSalinityIon exchangeGeologyEnvironmental scienceChemical engineeringChemistryIonEngineering

Abstract

fetched live from OpenAlex

Abstract Low salinity waterflood (LSW) has become an attractive enhanced oil recovery (EOR) method as it shows more advantages than conventional chemical EOR methods in terms of chemical costs, environmental impact, and field process implementation. Extensive laboratory studies in the past two decades have proposed several pore-scale mechanisms of oil displacement during LSW flooding, which are still open for discussion. However, the capability of reservoir simulators to model accurately this process is very limited. This paper provides a critical review of the state of the art in research and field applications of LSW. The focus is on a widely agreed mechanism that is the wettability alteration from preferential oil wetness to water wetness of formation rock surfaces. Ion exchange and geochemical reactions have been experimentally found to be important in oil mobilization due to enhanced water spreading at low salinity. To evaluate the significance of this surface wetting mechanism, a comprehensive ion exchange model with geochemical processes has been developed and coupled to the multi-phase multi-component flow equations in an equation-of-state compositional simulator. This new model captures most of the important physical and chemical phenomena that occur in LSW, including intra-aqueous reactions, mineral dissolution/precipitation, ion exchange and wettability alteration. The proposed LSW model is tested using the low-salinity core-flood experiments reported by Fjelde et al. (2012) for a North Sea reservoir and the low-salinity and high-salinity heterogeneous core-flood experiments by Rivet (2009) for a Texas reservoir. Excellent agreements between the model and the experiments in terms of effluent ion concentrations, effluent pH, and oil recovery were achieved. In addition, the model was also proved to be highly comparable with the ion-exchange model of the geochemistry software PHREEQC for both low salinity and high salinity (Appelo, 1994). Important observations in laboratory and field tests such as local pH increase, decrease in divalent effluent concentration, mineralogy contributions, and the influence of connate water and injected brine compositions can be reproduced with the proposed LSW model. Built in a robust reservoir simulator, it serves as a powerful tool for LSW design and the interpretation of process performance in field tests.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.669

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 communication0.0000.001
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 head0.015
GPT teacher head0.236
Teacher spread0.221 · 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