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Record W2095418204 · doi:10.2118/107692-ms

Physical Model Development To Study Sand Production

2007· article· en· W2095418204 on OpenAlexaboutno aff
Jothsimar González, J. E. Alvarellos, Héctor González, Víctor Lara

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPermeability (electromagnetism)Petroleum engineeringProduction (economics)Work (physics)Oil productionEnvironmental scienceFlow (mathematics)GeologyOil sandsProduction rateMining engineeringGeotechnical engineeringMechanicsMechanical engineeringEngineeringIndustrial engineeringMaterials science

Abstract

fetched live from OpenAlex

Abstract Most of heavy and extra heavy crude oil reservoirs in Venezuela are non-consolidated sand deposits. Venezuelan oil industry has a great interest to produce these reserves. Cold Heavy Oil Production with Sand (CHOPS) is an alternative for the primary production of some of these deposits; in particular those where other technologies are not applicable (i.e. sands with thicknesses are less than 10 m). In general, at field level, the application of the CHOPS has been successful around the world. In particular, it has experienced great development in Canada, China and United States. The physical and numerical studies show that change in the production rates, implies cavities formation and/or erosion zones near to the well that increase reservoir permeability. In Venezuela, experience in this technology does not exist. Furthermore, the bibliographical review demonstrates that many doubts still exist on the production mechanisms. It is the reason why this work considers the design, construction and evaluation of a sand production physical model. The main objective is to study the physical processes and to evaluate the influence of different variables like pressure, flow rate, among others, in the sand production mechanisms. The obtained data, will allow the development of models to predict reservoir behavior and its properties evolution in time. This physical model is set up with a cylindrical disc, 50 cm diameter and 20 cm thickness. Cylindrical geometry guarantees radial flow. The model is instrumented with sensors to measure pressures (injection, production and pores fluid) and fluid samples are taken to quantify total sand produced. The assembly system provides facilities to apply vertical stress. Ultrasonic wave velocity measurement is used to locate erosion zones. All data is collected by a Labview card and it is processed digitally in the computer in real time. This work shows results for a preliminary test with water and mineral oil used as fluids and calibrated glass bets as the porous media. The results prove that this system can be used to study sand production mechanism but it cannot be scale up to reservoir conditions. However the results will be used to validate numerical models.

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 score0.310
Threshold uncertainty score0.272

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 head0.031
GPT teacher head0.313
Teacher spread0.282 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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