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Record W4392774900 · doi:10.4043/34752-ms

Smart Water Flood in Carbonate Reservoirs: an Integrated Analysis Through Zeta Potentiometric and Simulation Studies

2024· article· en· W4392774900 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

VenueOffshore Technology Conference Asia · 2024
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPotentiometric titrationCarbonateFlood mythZeta potentialComputer scienceEnvironmental sciencePetroleum engineeringGeologyMaterials scienceChemistryElectrodeNanotechnology

Abstract

fetched live from OpenAlex

Abstract Smart waterflooding (SWF) is the science of injecting water of reduced salinity or modified potential determining ions (PDI) concentration in petroleum reservoirs for a specific brine/oil/rock system to obtain higher oil recovery efficiency. The study validates the surface interactions by zeta potentiometric measurements, estimates oil recovery, and generates relative permeability by core flood simulation through laboratory inputs, using in-situ samples of oil, water, and rock samples from one of the Giant offshore fields of India. The main emphasis of this paper is on 1) Varying the ionic composition of the injection water and reducing salinity for injection purposes; 2) Tuning the concentration of PDI (Ca+2, Mg+2 & SO4-2) ions after fixing a reduced salinity, the surface ionic chemistry between carbonates and water results in altering the rock wettability; 3) Surface charge of oil-saturated whole core samples of rock in the presence of various diluted and smart brines were estimated by zeta potential measurements;4) Smart water flood for incremental recoveries; 5) Single porosity simulation model to match oil recovery and pressure profiles obtained from smart water floods. The main conclusions of the study are 1) Wettability alteration in the carbonate rock tested to a more water-wet state by tuning the ionic concentrations of injection brine; 2) Zeta potentiometric studies with low-salinity waterflood (LSWF) in carbonate reservoirs can achieve positive results by: Increasing the concentration of sulfate ion to increase the zeta potential of the rock surface to an optimum level above which the deposition of calcium sulfate will not become a problem;Tuning the concentration of divalent cations, preferably calcium, such that the value of zeta potential is close to zero. At this stage, a weak bond exists between the oil and the rock surface due to a weak negative charge on the oil and a weak positive charge on the rock surface;Increasing the hydrophobicity of oil by dilution of injected brine which seems to be responsible for increasing the zeta potential and detaching the oil from the rock surface. This is due to electrical double-layer expansion which is principally caused by reduced ionic strength. 3) Smart flooding experiments indicated an increase in the overall recovery factor; 4) A positive shift in the oil relative permeability curve towards the right. The novelty of the paper is manifested by the following findings: Potential of PDI for carbonate reservoirs at a high-temperature range and an optimum concentration of PDI, at which maximum oil recovery is possible.Confirmation of Smart water flood effect in offshore carbonate reservoir through wettability alteration.A more efficient method as compared to sequential dilution.Underlying mechanisms of waterflooding involving the chemistry of injection brine in a carbonate system are investigated.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.306
Teacher spread0.278 · 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