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Record W2013888714 · doi:10.1039/c3lc00013c

Equilibrium gas–oil ratio measurements using a microfluidic technique

2013· article· en· W2013888714 on OpenAlexaff
Robert Fisher, Mohammad K. Shah, Dmitry Eskin, Kurt A. G. Schmidt, Ajay Singh, Shahnawaz Molla, Farshid Mostowfi

Bibliographic record

VenueLab on a Chip · 2013
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsSchlumberger (Canada)
Fundersnot available
KeywordsThermodynamic equilibriumPetroleumEquation of statePetroleum engineeringGas oil ratioMicrochannelMicrofluidicsCrude oilEnhanced oil recoveryChemistryChannel (broadcasting)ThermodynamicsMaterials scienceGeologyNanotechnologyEngineering

Abstract

fetched live from OpenAlex

A method for measuring the equilibrium GOR (gas-oil ratio) of reservoir fluids using microfluidic technology is developed. Live crude oils (crude oil with dissolved gas) are injected into a long serpentine microchannel at reservoir pressure. The fluid forms a segmented flow as it travels through the channel. Gas and liquid phases are produced from the exit port of the channel that is maintained at atmospheric conditions. The process is analogous to the production of crude oil from a formation. By using compositional analysis and thermodynamic principles of hydrocarbon fluids, we show excellent equilibrium between the produced gas and liquid phases is achieved. The GOR of a reservoir fluid is a key parameter in determining the equation of state of a crude oil. Equations of state that are commonly used in petroleum engineering and reservoir simulations describe the phase behaviour of a fluid at equilibrium state. Therefore, to accurately determine the coefficients of an equation of state, the produced gas and liquid phases have to be as close to the thermodynamic equilibrium as possible. In the examples presented here, the GORs measured with the microfluidic technique agreed with GOR values obtained from conventional methods. Furthermore, when compared to conventional methods, the microfluidic technique was simpler to perform, required less equipment, and yielded better repeatability.

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)0.000
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 score0.116
Threshold uncertainty score0.812

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 head0.027
GPT teacher head0.234
Teacher spread0.207 · 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

Citations42
Published2013
Admission routes1
Has abstractyes

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