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Record W4220841448 · doi:10.2118/208968-ms

Quantification of Phase Behaviour and Physical Properties of Alkane Solvents/CO2/ Water/Heavy Oil Systems under Equilibrium and Nonequilibrium Conditions

2022· article· en· W4220841448 on OpenAlexaff
Daoyong Yang, Yunlong Li, Desheng Huang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsThermodynamicsEquation of stateDissolutionSolventViscosityPhase (matter)Non-equilibrium thermodynamicsHydrocarbonChemistryAsphaltButaneEnhanced oil recoveryMaterials sciencePetroleum engineeringOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract The hybrid steam-solvent injection has been considered as a promising technique for enhancing heavy oil/bitumen recovery, while its main mechanisms including the heat transferred and dissolution of solvents (e.g., C3H8, C4H10, CO2, N2, and DME) into heavy oil/bitumen to reduce its viscosity and swell it are closely related to the phase behaviour of the solvents/water/heavy oil systems. To allow the seamless integration with the existing reservoir simulators, the traditional cubic equations of state (i.e., SRK EOS and PR EOS) have been modified and improved to accurately quantify the phase behaviour and physical properties of the aforementioned systems under equilibrium and nonequilibrium conditions. Firstly, a huge database has been built to develop the corresponding alpha functions by minimizing the deviation between the measured and calculated vapour pressures for water as well as nonhydrocarbon and hydrocarbon compounds available from the public domain. Such obtained alpha functions are further validated with enthalpy of vaporization for pure substances, and then the reduced temperature has been optimized and the eccentric factor has been redefined. Finally, a pressure-implicit strategy has been developed to optimize the binary interaction parameters (BIPs) by treating heavy oil as one pseudocomponent (PC) or multiple PCs. Also, the contributions of each solvent to the aforementioned systems have been compared and analyzed within a consistent and unified framework. In addition to new alpha functions for hydrocarbons and water, respectively, the reduced temperature is found to have its optimum value of 0.59 for the two equations of state (EOSs), while 0.60 is recommended for practical use. Such improved EOSs have been further employed to reproduce the experimentally measured multiphase boundaries (or pseudo-bubble-point pressures), density, viscosity, (mutual) solubility, and preferential mass transfer for the aforementioned mixtures under equilibrium and nonequilibrium conditions. The swelling effect for the heavy oil can be enhanced due to the addition of C3H8 and/or C4H10 or their mixtures into the CO2 stream. Due to the existence of water, isenthalpic flash leads to more accurate quantification of multiphase boundaries and physical properties for the hybrid solvent-thermal processes. Each component of a binary or ternary gas mixture is found to diffuse preferentially into heavy oil at high pressures and elevated temperatures in the absence and presence of porous media, while each of them is found to exsolve differently from gas-saturated heavy oil under nonequilibrium conditions.

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 score0.622
Threshold uncertainty score0.532

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 head0.023
GPT teacher head0.247
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 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

Citations9
Published2022
Admission routes1
Has abstractyes

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