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Record W4396872998 · doi:10.1021/acsomega.3c10205

Measurements and PR EoS Modeling of Thermophysical Properties at Vapor–Liquid Equilibrium Conditions for Natural Gas Condensate/Live Bitumen Mixtures

2024· article· en· W4396872998 on OpenAlexafffund
Sayyedvahid Bamzad, Mahmood Abdi, Shadi Kheirollahi, Mohammadjavad Mohammadi, Mabkhot Bin Dahbag, Hassan Hassanzadeh

Bibliographic record

VenueACS Omega · 2024
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Calgary
FundersKuwait Oil CompanySuncor Energy IncorporatedNatural Sciences and Engineering Research Council of CanadaImperial Oil LimitedCanadian Natural Resources LimitedCenovus EnergyUniversity of Calgary
KeywordsNatural gasThermodynamicsVapor–liquid equilibriumAsphaltMaterials scienceChemistryPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide In response to the need for less energy-intensive and greener bitumen recovery techniques, the use of multicomponent diluents through the expanding solvent steam-assisted gravity drainage (ES-SAGD) technique has garnered significant interest in recent years. In this work, we report new comprehensive measurements and Peng–Robinson equation of state (PR EoS) modeling of thermophysical properties (saturation pressure, density, viscosity, and K -values) of multicomponent mixtures of methane-bitumen-solvent. The multicomponent solvent is a natural gas condensate comprised of C 3, i -C 4, n -C 4, i -C 5, n -C 5, C 6, and C 7+ . Density, viscosity, solubility, and K -values of live bitumen (bitumen with dissolved methane) and various multicomponent mixtures are measured in the pressure range of 1–4 MPa and the temperature range of 313.41–459.10 K. A systematic approach is utilized to model the measured data. The experimental data show that the saturation pressure of the live bitumen can be controlled by selecting an appropriate solvent (condensate) composition. Condensate also has a significant effect on reducing the density and viscosity of the system. The results also show that the K -values of the components are almost independent of the composition of the solvent. The new comprehensive data set and the EoS model parameters reported in this work find applications in reservoir simulation as well as the design and optimization of the ES-SAGD process.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.669

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 head0.030
GPT teacher head0.247
Teacher spread0.216 · 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

Citations7
Published2024
Admission routes2
Has abstractyes

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