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Wettability Alteration during Low-Salinity Waterflooding and the Relevance of Divalent Ions in This Process

2015· article· en· W2511508631 on OpenAlexafffund
Jie Yang, Zhaoxia Dong, Mingzhe Dong, Zihao Yang, Meiqin Lin, Juan Zhang, Chen Chen

Bibliographic record

VenueEnergy & Fuels · 2015
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
FundersChina Scholarship CouncilChina University of Petroleum, BeijingUniversity of Calgary
KeywordsBrineImbibitionWettingDivalentSalinityChemistryAdsorptionChemical engineeringEnhanced oil recoveryDesorptionPorous mediumMineralogyInorganic chemistryEnvironmental chemistryPorosityGeologyOrganic chemistry

Abstract

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From laboratory and field test results, it is now largely agreed that reducing the overall salinity, especially the concentration of divalent ions of the injected water, can markedly improve the oil recovery. However, as a result of the complexity of the crude oil–brine–rock (COBR) system, there is no clear explanation of why the divalent cations (Ca 2+ ) are of major significance in a low-salinity water effect (LSWE). In the present paper, spontaneous imbibition, ζ-potential measurements, static adsorption/desorption of benzoic acid (BA) onto crushed Berea, and BA self-assembled layers on silica wafer have been performed to correlate macroscopic wettability alteration during low-saline water flood with the microscopic release of the hydrophobic layers (organic acid layers) on mineral surfaces and explain the relevance of active cations (Ca 2+ ) in this process, thereby providing a better understanding of the underlying mechanisms of a LSWE. Spontaneous imbibition results show that initial wettability of the COBR system was dominantly controlled by the initial concentration of Ca 2+ rather than Na + in brine; i.e., the initial wettability changed to be more oil-wet with an increasing concentration of CaCl 2 in initial water, while changing the concentration of NaCl in initial water had little effect on initial wettability. Moreover, reducing salinity of imbibing brine can outstandingly improve oil recovery of cores aged by CaCl 2 brine, whereas no obvious enhanced oil recovery (EOR) by low-salinity water was observed for cores aged by NaCl brine. Decreasing the concentration of either CaCl 2 or NaCl brine was able to make the oil/brine and brine/rock interfaces become less positively charged or even more negatively charged, observed by ζ-potential measurements, resulting in increased electrostatic repulsive forces between the oil/brine and brine/rock interfaces. These results suggest that the anionic groups of organic acid from crude oil, such as carboxylate, adsorb onto negatively charged mineral surfaces mainly through calcium bridges instead of van der Waals forces or sodium bridges and reducing salinity is able to increase the electrostatic repulsive forces between mineral surfaces and carboxylate groups and then break calcium bridges to change the wettability of the rock surface to be less oil-wet, and as a result, EOR occurs. These suggestions were supported by the static adsorption/desorption studies and self-assembly experiments. After sorption to crushed Berea, the varied BA concentration in the supernatant analyzed by total organic carbon (TOC) reveals that the presence of the background electrolyte Ca 2+ largely enhanced sorption in comparison to Na + . Lowering salinity was able to desorb BA from crushed Berea. Field emission scanning electron microscopy (FESEM) was used to obtain the microchemical composition and morphology of the wafer surface interacted with BA under different ionic strengths and solution cations (Ca 2+ and Na + ). Ca 2+ ions were found to enhance the adsorption of BA self-assembled layers on a silica wafer compared to Na +, which directly demonstrates that BA molecules mainly self-assemble on SiO 2 by calcium bridges rather than sodium bridges or van der Waals forces. The BA self-assembled layers were released after immersing organo-wafer into deionized water.

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How this classification was reachedexpand

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 score0.214
Threshold uncertainty score0.321

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 head0.235
Teacher spread0.224 · 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 teacher head, 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".

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Citations70
Published2015
Admission routes2
Has abstractyes

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