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Record W2178433972 · doi:10.2118/137453-ms

Three-Phase Equilibrium Study for Heavy Oil-Solvent-Steam System at High Temperatures

2010· article· en· W2178433972 on OpenAlexafffund
Na Jia, Jie Gao, Hao Huang, Julian Y. Zuo, Afzal Memon, Hongying Zhao, Heng‐Joo Ng

Bibliographic record

VenueCanadian Unconventional Resources and International Petroleum Conference · 2010
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsAlberta Innovates
FundersAlberta Innovates - Technology Futures
KeywordsSolventThermodynamic equilibriumPhase (matter)Equation of stateThermodynamicsViscosityChemistryHydrocarbonPetroleum engineeringSteam injectionMaterials scienceOrganic chemistryGeology

Abstract

fetched live from OpenAlex

Abstract Reservoir simulation and research activities of heavy oil production processes such as SAGD, VAPEX or the steam-solvent combined hybrid process require accurate values of equilibrium constants (K-values) at elevated temperatures. However, such data is rarely available in open literature either because of the temperature limitation of PVT equipment or difficulties in performing high temperature three phase vapor liquid equilibrium experiments. In this paper, with the assistance of a state-of-the-art fully visual PVT cell specifically developed for heavy viscous oils and capable of performing fluid phase behavior studies at temperatures up to 250°C and effectively mix samples with viscosity up to 1,000 cP at test temperature, a heavy oil-solvent-steam equilibrium case study is presented. The heavy oil was mixed with solvent and water at specified weight ratio, temperature and pressure in the heavy oil PVT cell. After achieving equilibrium, the volumes of vapor, liquid and water phases were measured. The samples from each phase were drawn for compositional analysis using gas chromatography and K-values of the hydrocarbon components were examined. The component compositions from this experiment were utilized for equation of state (EoS) model turning. This case study shows that with proper care, the EoS can be characterized and used to match with experimental data for heavy oil.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score1.000

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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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.

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
Published2010
Admission routes2
Has abstractyes

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