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Record W3012444852 · doi:10.2118/199948-ms

Development of a Rigorous Erosion Prediction Physical Model for Thermal Standalone Sand Control Screens

2020· article· en· W3012444852 on OpenAlexaff
Seyed Abolhassan Hosseini, Morteza Roostaei, Arian Velayati, Mohammad Soroush, Mohammad Mohammadtabar, Mahdi Mahmoudi, Vahidoddin Fattahpour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsErosionComputational fluid dynamicsFlow (mathematics)Environmental scienceThermalFlashingWork (physics)Geotechnical engineeringMaterials scienceMechanicsGeologyMechanical engineeringEngineeringMeteorology

Abstract

fetched live from OpenAlex

Abstract Erosion of standalone screens in thermal wells can lead to significant damage and reduction in production. The dominant failure mechanism is the development of localized high-velocity hot spots in the screen due to steam breakthrough or flashing of the steam across the screen. This study provides methods to assess the erosion potential of screen material devices to determine the allowable production conditions which avoid erosion. In this study the effects of impact angle, flow rate, sand concentration, particle size, and fluid viscosity on erosion are systematically investigated through a multivariable study. Experimental impingement testing is performed on screens in different orientations. Erosion is accessed by collecting weight loss data of the screen. Empirical erosion models are calibrated to provide predictions of functional relationships between erosion rate and varied parameters. Computational Fluid Dynamic (CFD) simulations are performed prior to the experimental work to visualize particle flow paths through the screen and determine local flow and impact velocities and wear patterns. The performance of five existing erosion models is assessed through experimental testing of sand control screens. In order to translate short-term, high-velocity laboratory test results into field erosion predictions, an empirical erosion model is then developed and employed to provide well flow guidelines and minimize erosion potential. This suggests that the use of erosion prediction models in situations in which due to lack of time/data tuning is not possible, may still provide a reasonable estimate for the rate of material loss of the screen. The model is used to obtain threshold superficial velocity curves for several conditions. The main concern associated with existing erosion models is that they do not consider sand production, nor do they account for many other factors that affect erosion process. An erosion model, coupled with CFD simulation, has been developed, that account for factors such as geometry, size, material, fluid properties and rate, sand size, shape, and density in downhole flow conditions.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.244

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 head0.027
GPT teacher head0.244
Teacher spread0.217 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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