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Record W2745038187 · doi:10.2118/182655-pa

Equation of State for Relative Permeability, Including Hysteresis and Wettability Alteration

2017· article· en· W2745038187 on OpenAlexfundno aff
Saeid Khorsandi, Liwei Li, Russell T. Johns

Bibliographic record

VenueSPE Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersAbu Dhabi National Oil CompanyCMG Reservoir Simulation FoundationPennsylvania State University
KeywordsRelative permeabilityWettingPermeability (electromagnetism)Saturation (graph theory)Porous mediumHysteresisPetroleum reservoirMaterials scienceMultiphase flowMechanicsGeologyThermodynamicsPorosityMineralogyGeotechnical engineeringPetroleum engineeringChemistryMathematicsComposite materialPhysics

Abstract

fetched live from OpenAlex

Summary Commercial compositional simulators commonly apply correlations or empirical relations that are based on fitting experimental data to calculate phase relative permeabilities. These relations cannot adequately capture the effects of hysteresis, fluid compositional variations, and rock-wettability alteration. Furthermore, these relations require phases to be labeled, which is not accurate for complex miscible or near-miscible displacements with multiple hydrocarbon phases. Therefore, these relations can be discontinuous for compositional processes, causing inaccuracies and numerical problems in simulation. This paper develops for the first time an equation-of-state (EOS) to model robustly and continuously the relative permeability as a function of phase saturations and distributions, fluid compositions, rock-surface properties, and rock structure. Phases are not labeled; instead, the phases in each gridblock are ordered on the basis of their compositional similarity. Phase compositions and rock-surface properties are used to calculate wettability and contact angles. The model is tuned to measured two-phase relative permeability curves with very few tuning parameters and then is used to predict relative permeability away from the measured experimental data. The model is applicable to all flow in porous-media processes, but is especially important for low-salinity polymer, surfactant, miscible gas, and water-alternating-gas (WAG) flooding. The results show excellent ability to match measured data, and to predict observed trends in hysteresis and oil-saturation trapping, including those from Land's model and for a wide range in wettability. The results also show that relative permeabilities are continuous at critical points and yield a physically correct numerical solution when incorporated within a compositional simulator (PennSim 2013). The model has very few tuning parameters, and the parameters are directly related to physical properties of rock and fluid, which can be measured. The new model also offers the potential for incorporating results from computed-tomography (CT) scans and pore-network models to determine some input parameters for the new EOS.

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 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)0.001
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 score0.391
Threshold uncertainty score0.255

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.054
GPT teacher head0.319
Teacher spread0.264 · 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".

Quick stats

Citations52
Published2017
Admission routes1
Has abstractyes

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