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Record W2808982224 · doi:10.2118/191153-ms

Modelling of Fluid Flow in a Petroleum Reservoir Using an Engineering Approach

2018· article· en· W2808982224 on OpenAlexaff
Mahamudul Hashan, Labiba Nusrat Jahan, Tareq Uz Zaman, Murtada A. Elhaj, Syed Imtiaz, M. Enamul Hossain

Bibliographic record

VenueSPE Trinidad and Tobago Section Energy Resources Conference · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPartial differential equationDiscretizationReservoir simulationComputer scienceFluid dynamicsAlgebraic equationFlow (mathematics)Applied mathematicsDifferential equationMathematical optimizationMathematicsNonlinear systemMathematical analysisEngineeringMechanicsPhysicsGeometry

Abstract

fetched live from OpenAlex

Abstract The mathematical approach is the most commonly used approach in reservoir simulation. The classical mathematical approach considers numerous impractical assumptions leading toward the development of unrealistic reservoir simulator. In contrast, recently developed engineering approach is much promising as it has numerous advantages, such as – scope of bypassing the formulation of partial differential equations and discretization of partial differential equations, the ability to avoid rigorous and complex mathematics, and capability of realistic representation of reservoir behaviour through eliminating spurious assumptions. The present study outlines the route map for developing a reservoir simulator using an engineering approach. Major challenges encountered in reservoir simulation and the fundamentals of various available modelling approaches are addressed in this paper. The outlook for both classical mathematical approach and engineering approach are reviewed along with their strengths and weaknesses. Fluid flow equations are derived based on the proposed engineering approach. To do that, a set of non-linear algebraic flow equations in the time integral form is developed using the mass balance equation, an equation of state, and a constitutive equation without going through the formulation of partial differential equations and discretization step. The time integral is then approximated to obtain the non-linear algebraic flow equations for all the gridblocks of the reservoir. The significance of the engineering approach for describing the accurate fluid flow through porous media is compared to the to conventional mathematical approach. The engineering approach provides the same fluid flow equations as the classical mathematical approach for both the radial cylindrical and cartesian coordinate system but, without going through the formulation of partial differential equations and discretization step. Much simpler ordinary differential equation solvers, e.g., Runge-Kutta method or Euler method can be used in the engineering approach to obtain the solution, whereas the classical mathematical approach does not have this advantage. Both the classical mathematical approach and the engineering approach treat the initial conditions in the same way. If classical mathematical approach uses second-order approximation then the same accuracy is obtained for both approaches in treating the boundary conditions. The engineering approach provides more precise dealing to the constant pressure boundary condition for block-centred gridding system in case of using the first-order approximation. The engineering approach gives the justification of using the central difference approximation for second order space derivative in classical mathematical approach. Results show that the proposed engineering approach based fluid flow model provides better flow prediction than the conventional mathematical approach based flow model. The outcome of this study will help engineers and researchers to develop more transparent simulator instead of creating a black box where the natural chaotic behaviour of the underground reservoir will be more understandable.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.266
Teacher spread0.204 · 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".

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Citations2
Published2018
Admission routes1
Has abstractyes

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