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Record W3205851034 · doi:10.1115/omae2021-62956

Experimental, Numerical, and Statistical Investigation of Two Phase Flow in a Cylindrical Perforation Tunnel

2021· article· en· W3205851034 on OpenAlexaff
Ekhwaiter Abobaker, Abadelhalim Elsanoose, Mohammad Azizur Rahman, Faisal Khan, Amer Aborig, Stephen Butt

Bibliographic record

VenueVolume 10: Petroleum Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPerforationPetroleum engineeringVolumetric flow rateFluentComputer simulationFlow (mathematics)Fluid dynamicsDrilling fluidPermeability (electromagnetism)MechanicsViscosityVolume of fluid methodNumerical analysisMaterials scienceEngineeringMechanical engineeringDrillingSimulationMathematicsChemistryComposite material

Abstract

fetched live from OpenAlex

Abstract Perforation is the final stage in well completion that helps to connect reservoir formations to wellbores during hydrocarbon production. The drilling perforation technique maximizes the reservoir productivity index by minimizing damage. This can be best accomplished by attaining a better understanding of fluid flows that occur in the near-wellbore region during oil and gas operations. The present work aims to enhance oil recovery by modelling a two-phase flow through the near-wellbore region, thereby expanding industry knowledge about well performance. An experimental procedure was conducted to investigate the behavior of two-phase flow through a cylindrical perforation tunnel. Statistical analysis was coupled with numerical simulation to expand the investigation of fluid flow in the near-wellbore region that cannot be obtained experimentally. The statistical analysis investigated the effect of several parameters, including the liquid and gas flow rate, liquid viscosity, permeability, and porosity, on the injection build-up pressure and the time needed to reach a steady-state flow condition. Design-Expert® Design of Experiments (DoE) software was used to determine the numerical simulation runs using the ANOVA analysis with a Box-Behnken Design (BBD) model and ANSYS-FLUENT was used to analyses the numerical simulation of the porous media tunnel by applying the volume of fluid method (VOF). The experimental data were validated to the numerical results, and the comparison of results was in good agreement. The numerical and statistical analysis demonstrated each investigated parameter’s effect. The permeability, flow rate, and viscosity of the liquid significantly affect the injection pressure build-up profile, and porosity and gas flow rate substantially affect the time required to attain steady-state conditions. In addition, two correlations obtained from the statistical analysis can be used to predict the injection build-up pressure and the required time to reach steady state for different scenarios. This work will contribute to the clarification and understanding of the behavior of multiphase flow in the near-wellbore region.

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 score0.368
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

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