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Enregistrement W4252803235 · doi:10.2523/90273-ms

Sand Production Prediction: A New Set of Criteria for Modeling Based on Large-Scale Transient Experiments and Numerical Investigation

2004· article· en· W4252803235 sur OpenAlex
Alireza Nouri, Vaziri Hans, Belhaj Hadi, Islam Rafiqul

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Notice bibliographique

RevueProceedings of SPE Annual Technical Conference and Exhibition · 2004
Typearticle
Langueen
DomaineEngineering
ThématiqueHydraulic Fracturing and Reservoir Analysis
Établissements canadiensDalhousie University
Organismes subventionnairesNatural Sciences and Engineering Research Council of CanadaKillam Trusts
Mots-clésCitationExhibitionComputer scienceScale (ratio)Set (abstract data type)Information retrievalOperations researchLibrary scienceEngineeringArchaeologyHistoryGeographyCartography

Résumé

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Sand Production Prediction: A New Set of Criteria for Modeling Based on Large-Scale Transient Experiments and Numerical Investigation Alireza Nouri; Alireza Nouri Dalhousie University Search for other works by this author on: This Site Google Scholar Hans Vaziri; Hans Vaziri BP-America Inc. Search for other works by this author on: This Site Google Scholar Hadi Belhaj; Hadi Belhaj Dalhousie University Search for other works by this author on: This Site Google Scholar Rafiqul Islam Rafiqul Islam Dalhousie University Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas, September 2004. Paper Number: SPE-90273-MS https://doi.org/10.2118/90273-MS Published: September 26 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Nouri, Alireza, Vaziri, Hans, Belhaj, Hadi, and Rafiqul Islam. "Sand Production Prediction: A New Set of Criteria for Modeling Based on Large-Scale Transient Experiments and Numerical Investigation." Paper presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas, September 2004. doi: https://doi.org/10.2118/90273-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Annual Technical Conference and Exhibition Search Advanced Search AbstractUsing novel physical model experiments and numerical analyses, a set of criteria are proposed that can be used to determine the onset of sanding and its severity in terms of rate and duration.Experiments on large-scale hollow cylinder specimens were conducted involving real time sand production measurement under various conditions. Synthetic sandstone was used in the experiments whose strength properties were comprehensively determined. A numerical approach was used for simulating the proposed experiments. The material behaviour was simulated using an elasto-plastic stress-strain relationship. The model simulates interaction between fluid flow and mechanical deformation of the medium in predicting sand production. The criteria considered for sanding are more comprehensive than conventionally used and included modeling strain softening of the material accompanied with shear bands formation as well as tensile failure. In the post disaggregation phase, additional features are considered including allowing for the removal of the disaggregated material and making the necessary adjustments to the size and properties of the domain under consideration. Hence, the model is considered to be suitable for time-dependent analysis of the rock as it undergoes disaggregation and production induced by depletion, drawdown, and water-cut. By relating the sand rate to production over the life of a field, the tool can be used in assisting with the completion and operation design of the wells.The model shows good agreement with experimental results in terms of rock deformation and sand rate. It predicted the onset of shear failure and the subsequent strain softening initiated from the cavity face and propagated inside the medium. Strain softening proved to be the main mechanism for material disaggregation. The good agreement between the numerical and experimental results under comprehensive and complex conditions bodes well for its field applications.IntroductionDespite the great effort to improve the prediction of sand production, field practices have been demonstrated that quantitatively accurate prediction of volumetric solid production yet needs to be developed, especially for poorly cemented sandstones. Existing models can predict the onset of sand production and analyze cavity stability and rock failure; however, they cannot predict the volumetric production of sand over time as a function of applied stresses, fluid flow rate and changes in water saturation.In the following, a brief description of the existing models is introduced.Modeling StrategiesSeveral analytical and numerical models are available for predicting sand production1,2,3,4,5,6. Some of these models assume sanding is due to seepage (tensile failure) while others base it on the strain level (compression). Most of the models predict sanding initiation4,7,8,9,10,11,12,13. Some other models view sand production as a mixed hydro-mechanical process14,15,16,17,18.Shear or Tensile FailureNumerous types of shear failure models have been published. An elastic brittle failure model is easy to implement19,20,21,22,23, but has disadvantage that it does not offer a very realistic description of friable and loose materials. An elastic-plastic material model involves more computational effort and, in return, enables a more realistic description of the material behaviour8,22.Stability criterion based on tensile failure has been expressed in terms of the drawdown pressure gradient at the cavity wall8,9. A critical value of the pressure gradient was first derived by Bratli et al.24. Their model has the weakness that the disintegration phase is overlooked in the stage of modeling. Keywords: strength, tensile strength, criteria, completion installation and operations, tensile stress, experiment, drillstem/well testing, reservoir characterization, kpa, effective stress Subjects: Reservoir Characterization, Formation Evaluation & Management, Perforating, Drillstem/well testing, Completion Installation and Operations, Completion Operations This content is only available via PDF. 2004. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,355
Score d'incertitude au seuil0,424

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,027
Tête enseignante GPT0,264
Écart entre enseignants0,237 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle