MétaCan
Menu
Back to cohort
Record W2793597187 · doi:10.2118/189754-ms

General Analytical Model for Thermal-Solvent Assisted Gravity Drainage Recovery Processes

2018· article· en· W2793597187 on OpenAlexaff
H. Motahhari, Rahman Khaledi

Bibliographic record

VenueSPE Canada Heavy Oil Technical Conference · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsImperial Oil (Canada)
Fundersnot available
KeywordsMass transferDilutionMechanicsThermodynamicsHeat transferDiffusionPorous mediumDispersion (optics)Molecular diffusionDrainageWork (physics)ChemistryPetroleum engineeringMaterials sciencePorosityGeologyPhysicsEngineeringComposite material

Abstract

fetched live from OpenAlex

Abstract Thermal-Solvent Assisted Gravity Drainage are recovery processes in which the stimulation mechanism for bitumen viscosity reduction is by heating and/or dilution. Different gravity drainage recovery processes can be included in this category depending on the range of the injection temperature and the solvent concentration in the injection stream. Examples are SAGD, SA-SAGD, VAPEX and heated VAPEX. The performance behavior of these processes is significantly driven by the complex thermodynamic interaction of steam and solvent, heat transfer, multiphase fluid equilibrium and flow in the porous medium. In this study, we develop a general analytical model for gravity drainage processes by incorporating mass transfer mechanisms (including diffusion and dispersion) and heat transfer mechanism by conduction. In particular, we incorporate the dependency of diffusion and dispersion coefficients on concentration, temperature and drainage velocities, respectively. We utilize a novel approach to analytically solve the second order non-linear partial differential equation which governs mass transfer within the mass boundary layer. The resulted closed-form analytical model provides oil drainage rate due to gravity and heat and dilution effects as a function of reservoir and fluid properties. The developed model in this work provides a new perspective into the mass transfer mechanisms and their relative importance within the mass transfer boundary layer at different operating conditions. The consistent application of the new model to the gravity drainage processes ranging from SAGD to VAPEX demonstrated using laboratory data from literature. It is shown that the predicted concentration distribution profile by the model with the concentration-dependent diffusion coefficient is profoundly different than the predicted profiles with a constant diffusion coefficient. The modeling results demonstrate that the dispersion can be several orders of magnitude greater than diffusion for solvent assisted gravity drainage process at the elevated temperatures. In addition, the contribution of the mass transfer boundary layer to oil production rate can be significantly greater than the heat transfer boundary layer despite being considerably narrower than the heat transfer boundary layer at the elevated temperatures. These findings confirms that the performance of solvent assisted gravity drainage process can be more favorable at the elevated temperatures.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.259
Teacher spread0.226 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueSPE Canada Heavy Oil Technical ConferenceSame topicGroundwater flow and contamination studiesFrench-language works237,207