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Record W2930195251 · doi:10.2118/193909-ms

Modeling the Effect of Reaction Kinetics and Dispersion during Low-Salinity Waterflooding

2019· article· en· W2930195251 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.

fundA Canadian funder is recorded on the work.
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 Reservoir Simulation Conference · 2019
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersEnergi SimulationJohn and Willie Leone Family Department of Energy and Mineral Engineering, College of Earth and Mineral Sciences, Pennsylvania State UniversityPennsylvania State University
KeywordsWettingSalinityDispersion (optics)KineticsChemical kineticsReaction rateChemistryChemical engineeringChemical reactionThermodynamicsMaterials scienceGeologyOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Abstract The objective of this paper is to model low-salinity waterflooding by honoring physico-chemical complexity, namely, the effects of reaction kinetics and dispersion. Recent literature provides evidence for the potential of low-salinity water injection to improve oil recovery through wettability alteration through a complex network of reactions. However, there is lack of consensus with respect to the exact chemical species that are responsible for the alteration process. Therefore, in this study, we develop a a simplified binary multiphase reactive transport model that honors the general surface reaction for wettability alteration, but at the same time includes effects of reaction kinetics and dispersion in the governing equations. We lump the reactants, such as sodium, calcium, and petroleum acids, into two characteristic components based on their contribution to oil or water wetness. The wettability alteration process is modelled as a competition between these primary characteristic components to occupy the rock surface as described by reaction kinetics. The simulation results show a significant impact of reaction kinetics on the rate of wettability alteration compared to assuming instantaneous equilibrium. In the limiting case of a very slow reaction rate (Da ~ 0), low-salinity injection does not alter the wettability. Particularly, no effect on ultimate oil recovery is observed, regardless of the injected salinity level. For the case of an instantaneous reaction the ultimate oil recovery is sensitive to the injected fluid salinity. Moreover, during fast reactions (Da ~ 10-4), the wettability alteration front moves slower than the injected fluid front caused by excess salt in the solution that desorbs from the rock surface. The delay in wettability alteration is crucial to consider for an appropriate slug size design of low-salinity injection. Lastly, we observe that dispersion does not affect the ultimate oil recovery during wettability alteration as compared to reaction kinetics.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.380

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 head0.014
GPT teacher head0.256
Teacher spread0.242 · 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