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Record W2024060319 · doi:10.2118/100400-ms

Experimental Investigation and Network Modeling Simulation of Free Fall Gravity Drainage in Single-Matrix and Fractured-Blocks Models

2006· article· en· W2024060319 on OpenAlexaff
Alireza Mollaei, Manouchehr Haghighi, Brij Maini

Bibliographic record

VenueAbu Dhabi International Petroleum Exhibition and Conference · 2006
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMicromodelDrainageImbibitionGeotechnical engineeringMatrix (chemical analysis)Free surfaceDisplacement (psychology)Porous mediumGeologyWettingMechanicsPetroleum engineeringSimulationMaterials sciencePorosityEngineeringComposite materialPhysics

Abstract

fetched live from OpenAlex

Abstract Free Fall Gravity Drainage as an important recovery mechanism was investigated and analyzed experimentally and by numerical (network model) simulation for both single matrix and fractured blocks models. The results of free fall gravity drainage of these two models were compared to each other to determine whether or not the network of fractures intensify the free fall gravity drainage recovery of matrix blocks. For the experimental study, a set of glass micromodels with real pattern of porous media was constructed in two main forms of single matrix model (as a 2D simulator of conventional reservoirs) and fractured blocks model (as a 2D simulator of fractured reservoirs) in laboratory. Also, two numerical network model simulators were programmed based on pore scale displacement mechanisms (drainage, imbibition and flow through films) to study and compare the behavior of free fall gravity drainage process in two models. The simulator takes into account the dominant displacement mechanisms observed in free fall gravity drainage glass micromodel experiments of both single matrix and fractured blocks models. Free fall gravity drainage experimental results of glass micromodel were used to validate the network model simulator. The mixed-wet wettability of glass micromodels was applied in network model simulator which allows oil to flow through wetting films in oil-wet regions and through spreading films on water in water-wet regions. Method of Image-Analysis was used to generate pore and throat size distribution functions of glass micromodels. The simulators were used to study and interpret the effects of different parameters on free fall gravity drainage results. For this purpose, numerous sensitivity analysis scenarios were tested (run) by numerical simulators to evaluate the effect of different parameters (pore and throat size, fracture aperture, oil density, oil viscosity, gas -oil interfacial tension (sgo) and coordination number (Z)) on results of free fall gravity drainage process. Also, relative permeability and capillary pressure curves of both single matrix and fractured blocks models were generated by numerical network model simulator and are compared to each other.

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: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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

Citations2
Published2006
Admission routes1
Has abstractyes

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