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Record W2032785045 · doi:10.2118/07-03-02

Methods for Modelling Full Tensor Permeability in Reservoir Simulators

2007· article· en· W2032785045 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTensor (intrinsic definition)Orientation (vector space)Viscous stress tensorPermeability (electromagnetism)AnisotropyMathematicsTensor fieldGridGeometryCauchy stress tensorTensor contractionMathematical analysisExact solutions in general relativityPhysicsChemistry

Abstract

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Abstract This work examines methods for modeling reservoir flow in the presence of a permeability tensor. Usually, control-volume multipoint discretizations are used to simultaneously handle the tensor permeability and complex geometry. Instead, the method used in this work is based on a simple extension of the conventional finite difference method. It is shown that this method (which results in 9-point approximations with a full tensor) cannot accurately predict the behaviour of reservoirs which contain permeability anisotropy. It suffers from what we call a "tensor orientation " effect, in addition to the well known grid orientation effect. The tensor orientation effect introduces an error in the magnitude and shape of the pressure field, which depends on the relative orientation of the grid in relation to the principal axes of the permeability tensor. This problem has been solved by developing a 13-point extension of the conventional 9-point finite difference method for the tensor permeability, which essentially eliminates the tensor orientation errors. Since this difference scheme is not easily implemented in conventional simulators, an approximate semi-implicit method, in which only nine points are in the implicit mode, was also developed. The semi-implicit method provides a good match with the 13-point method for the test problem. However, further reduction to a 5-point implicit operator results in a loss of accuracy. Comparative evaluation against the Flux Continuous Scheme technique shows that while both methods are free of the tensor orientation effect, the 13-point method has a lower value for well block pressure. Lack of an analytical solution makes it difficult to determine which method is closer to reality. Introduction In complex reservoirs, orientation and magnitude of principal permeabilities may vary spatially, and also evolve in time due to geomechanical effects. In such cases, a formulation with a full permeability tensor should be used to model fluid flow. In this paper, we examine methods for modeling fluid flow with a permeability tensor, and in particular, the effect of the permeability tensor orientation on the results with various numerical methods. Dependency of simulation results of fluid flow in porous media to the type of the grid mesh is well known and called the "grid orientation" effect. This problem was first demonstrated for 5-point reservoir simulators by Todd et al.(1) in 1972. They suggested using 2-point upstream mobility method to alleviate this effect. This problem is associated mainly with unfavourable mobility ratios which occur in most EOR isothermal processes and steam and combustion, and can very seriously alter the results and conclusions of simulation studies. The grid orientation effect is also severe for simulating miscible displacement. Settari et al.(2) have shown that a standard 5-point approximation gives unacceptable results even for moderately adverse mobility ratios (M = 10). Until now, a completely satisfactory solution has not been found for finite difference simulators and the grid orientation remains one of the more difficult numerical research problems. Nine-point discretizations are the usual method for solving the problem. However, the 9-point method still has some orientation errors, which depend on the problem solved(1).

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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)0.002
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.212
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.349
Teacher spread0.314 · 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