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Record W2245096976 · doi:10.2118/174518-ms

Integration of PC-SAFT Equation of State into Heat Assisted Solvent Recovery Simulation

2015· article· en· W2245096976 on OpenAlexafffund
Mingxu Ma, Shengnan Chen, Jalal Abedi

Bibliographic record

VenueSPE Canada Heavy Oil Technical Conference · 2015
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Calgary
KeywordsEquation of stateSolubilityThermodynamicsMaterials scienceSolventTolueneAsphaltWork (physics)Phase (matter)ChemistryPhysical chemistryPhysicsOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract The accuracy of Equation of State (EoS) in phase behaviour modeling plays an important role in compositional and thermal reservoir simulations. PC-SAFT (Perturbed-Chain Statistical Associating Fluid Theory) EoS can predict solubility and density of bitumen/solvent systems more accurately than Peng-Robinson and Soave-Redlich-Kwong EoS. In this work, a simplified version of PC-SAFT EoS was integrated into a thermal reservoir simulation to model heat assisted solvent recovery process. Bitumen was characterized into two scenarios for the simplified PC-SAFT modeling: eight pseudo-components (8-PCs) and three pseudo-components (3-PCs) using a well-developed bitumen characterization method. The solubility and density modeling ability of 3-PCs was evaluated and verified with that of the 8-PCs system. The simplified PC-SAFT with 3-PCs bitumen characterization method was then applied to generate data of K-Value, density, compressibility, and thermal expansion coefficient of each pseudo-component. The generated fluid properties were integrated with reservoir simulation to model a warm C3H8 VAPEX experiments at 40, 50 and 60 °C. In the 8-PCs characterization, the overall Average Absolute Relative Deviations (AARDs) for the solubility and density of CH4, C2H6, C3H8 and CO2-saturated bitumen were within 6.6 % and 2.3 % respectively, and the predicted AARDs for the density of n-C5H12, n-C10H22, n-C14H30, toluene and xylene-diluted bitumen were as low as 0.9 %. Results of the 3-PCs characterization were found to be as accurate as those of 8-PCs in modeling bitumen/gas solvent systems. In addition, the results of the fluid properties were successfully integrated into commercial reservoir simulator. Relative permeability was history matched with the measured data at 40 °C, and then tested against the measured data at 50 and 60 °C. The reservoir simulation results indicated good agreement with the measured data. The numerical results showed that although bitumen viscosity decreased due to high temperature solvent, solubility was reduced at the same time, compensating the viscosity reduction effects by solvent diluting.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.261
Teacher spread0.217 · 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 designSimulation or modeling
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

Citations2
Published2015
Admission routes2
Has abstractyes

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