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Nonequilibrium Exsolution Kinetics of Hydrocarbon Solvents in Heavy Oil

2024· article· en· W4400498683 on OpenAlexafffund
Hongyang Wang, Fanhua Zeng, Farshid Torabi, D. He, Xiang Zhou, You Zhou, Changfeng Xi, Bojun Wang

Bibliographic record

VenueEnergy & Fuels · 2024
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Regina
FundersPetroleum Technology Research CentreChina Postdoctoral Science Foundation
KeywordsHydrocarbonKineticsNon-equilibrium thermodynamicsChemistryThermodynamicsPetroleum engineeringChemical engineeringGeologyOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Nonequilibrium exsolution kinetics of methane and propane in heavy oil were studied through visual experimentations and continuum simulations. Experimentally, novel Constant Composition Expansion (CCE) tests, combined with a micromodel to visualize the bubbly oil flow, were fulfilled in pressure–volume–temperature (PVT) cells. Two schemes were applied, namely, constant volume extraction (CVE) and stepwise pressure depletion (SPD). From the pressure measurement of CVE, methane first went through a pressure-declining period due to hysteresis of exsolution and later a pressure-maintaining period under a balance between exsolution and volume expansion rate. Meanwhile, the pressure of the propane system dropped rapidly and rebounded back to a constant pressure for a long period of time due to a higher solubility than methane. Compared with equilibrium state, the solvent exsolution of both live oils were always under nonequilibrium. Bubbly oil flow was visually observed to determine the range of pseudobubble point pressure. From the volume expansion behavior from the SPD tests, both methane- and propane-based live oil systems present a close-to-linear relationship between volume and time at each pressure drawdown level before reaching equilibrium. This facilitates the quantification of exsolution rate under given pressure. Numerically, a simulation platform to calculate nonequilibrium exsolution kinetics has been built. The feasibility of the simulator is verified through simulating literature data with various pressure data ranges. The exsolution rates have been achieved by history matching the CVE and SPD tests. For CVE tests, methane shows a higher exsolution rate (1 × 10 –4 to 1 × 10 –2 min –1 ) than propane (1 × 10 –6 to 1 × 10 –3 min –1 ) under the same volume expansion rate, indicating a higher tendency to exsolve and form foamy oil. Propane tends to stay in heavy oil due to high solubility. The exsolution rates of the stable-pressure period present a power relationship with volume expansion rate for both live oils. For SPD tests, methane presents a similar range of exsolution rates (1 × 10 –5 to 1 × 10 –4 min –1 ) as propane under similar P / P sat ratios with pre-existing free gas phase. Compared to tests conducted by a sudden pressure drawdown scheme, pre-existing gas cap yields lower exsolution rates due to smaller chemical potential between phases. SPD tests also verify faster exsolution kinetics for methane than propane.

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)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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
Published2024
Admission routes2
Has abstractyes

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