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Record W4231145338 · doi:10.2118/2004-215

Incorporation of Strain-Induced Permeability Model in a Deformation-Flow-Heat Transfer Simulator

2004· article· en· W4231145338 on OpenAlexafffund
J. Du, R.C.K. Wong

Bibliographic record

VenueCanadian International Petroleum Conference · 2004
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHeat transferPermeability (electromagnetism)Deformation (meteorology)MechanicsMaterials scienceFlow (mathematics)Computer scienceSimulationComposite materialChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract This paper extends the fully coupled geomechanics and reservoir simulator previously developed by the authors to include temperature effects using finite element method (FEM). The strain-induced permeability model and the full permeability tensor are incorporated in the deformation-flow-heat transfer simulator. Numerical examples are given to evaluate the validity of the FEM model. Introduction The simulation of fluid flow and heat transfer through porous media has been a branch of research undergoing rapid growth in the chemical and petroleum field. Conventional reservoir simulators usually calculate the effects of deformation on pore volume change through the concept of reservoir compressibility and mainly focus on homogeneously or transversely isotropic porous structures, although in most practical problems the porous medium is anisotropic either due to geological processes or due to human being's industrial activities. Recently, much attention has been paid to the importance of geomechanics in reservoir simulation, particularly in thermal recovery of oil sand reservoir. Deformations in an oil sand reservoir are induced by the changes of pore pressure and temperature due to fluid injection and production in thermal recovery processes. In turn, the changes in deformation affect permeability. The permeability change of reservoir formation subjected to deformation changes is usually assumed as a function of porosity or volumetric strain, which is a scalar variable. Thus, the changes in permeability are equal in all directions even though the changes in strains are different in each direction. Wong (1)analyzed the grain fabric of intact and sheared oil sand specimens using the thin section imaging method. He observed that even in intact natural oil sand specimens, the hydraulic radius and tortuosity factors vary in vertical and horizontal directions resulting in an intrinsic anisotropy in permeability. Based on theoretical and laboratory works, he developed a new permeability model for deformable porous media (2). This model assumes the tensor permeability is governed by inducedprincipal strains. It can quantify the changes in permeability when the material experiences shear deformation and the changes in permeability can be anisotropic. In order to account for reservoir deformations due to pore pressure and temperature changes resulting from production and fluid injection, coupled geomechanics-reservoir-heat transfer simulation is necessary (3). Conventional reservoir simulators usually use finite difference method (FDM) and assume permeability either isotropic or diagonal tensor. It is impractical to develop coupled geomechanics-reservoir simulators based on FDM numerical schemes due to its complexity. A coupled deformation-flow-heat transfer simulator using finite element method (FEM) was developed by implementing temperature in early version of a geomechanics-reservoir simulator (4). The full tensor permeability and the strain-induced permeability model were incorporated in the simulator. It was then used to conduct a coupling analysis of two-dimensional non-isothermal singlephase fluid flow in elastic porous media. Coupled FEM Model Formulation Prior to the formulation of the governing equations, we need to make a few assumptions with respect to the FEM model (5, 6):Infinitesimal deformation theory holds.Domains of interest are fully saturated.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.997

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 head0.020
GPT teacher head0.223
Teacher spread0.202 · 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 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

Citations0
Published2004
Admission routes2
Has abstractyes

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