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Record W4220949443 · doi:10.2118/208913-ms

A New Insight into the Determination of True Residual Oil Saturation and Oil Relative Permeability from the Experimental Data in Heavy Oil/Water Systems

2022· article· en· W4220949443 on OpenAlexaff
Sajjad Esmaeili, Apostolos Kantzas, Brij Maini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRelative permeabilityPermeability (electromagnetism)Saturation (graph theory)ResidualApproximation errorPetroleum engineeringImbibitionDrop (telecommunication)Soil scienceChemistryMaterials scienceEnvironmental scienceMathematicsGeologyComposite materialStatisticsMembranePorosityEngineering

Abstract

fetched live from OpenAlex

Abstract Determination of true residual oil saturation and oil relative permeability curve for heavy oil/water systems requires extensive effort and time as the breakthrough time occurs early in the imbibition process and the history match techniques are not able to obtain these two parameters perfectly. The aim of this work is to provide a new insight into the determination of residual oil saturation and oil relative permeability from core flooding in heavy oil/water systems at different temperatures. Literature claimed that the ratio of water relative permeability to oil relative permeability should be considered besides the production and pressure drop data in history matching to determine the residual oil saturation more accurately. In this regard, different relative permeability curves from our previous experimental works are incorporated in a series of simulations that were run for up to 100 PV of water injection. Production and pressure drop data were generated where a normal error distribution is added to the input data. The history matching runs (considering relative permeability ratio) are carried out to examine how many pore volumes of water need to be injected to reach the true residual oil saturation accurately in different experiments. The history matching results (with a Corey relative permeability model), employing the production data, pressure drop data, and the ratio of water relative permeability to oil relative permeability, which can be calculated fairly accurate from the Welge method, confirm that water relative permeability exponent is generally independent of the volume of injected water. Since the irreducible water saturation can be determined nicely during the oil flooding due to the inverse mobility ratio, the water relative permeability is not a function of volume of injected water. In contrast, determination of the true residual oil saturation in five experiments out of six is predicted with an error less than 5%. For several systems at different temperatures, at least 40 PV of water needs to be injected to result in accurate residual oil saturation determination. The oil exponent determination reveals a deviation of 20%-60% from the entered value to the simulation. The ratio of water relative permeability to oil relative permeability should be inserted into the simulation for acceptable history matching of relative permeability determination. The estimation of true residual oil saturation for relative permeability determination from the experimental data cannot be achieved easily. In this study, a new technique described by in the literature has been examined and tested to determine the required pore volume of injected water in different heavy oil/water systems within a wide range of temperatures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes1
Has abstractyes

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