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Enregistrement W4233304239 · doi:10.2523/83978-ms

Promoting Real-Time Optimization of Hydrocarbon Producing Systems

2003· article· en· W4233304239 sur OpenAlex

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Notice bibliographique

RevueProceedings of Offshore Europe · 2003
Typearticle
Langueen
DomaineEngineering
ThématiqueReservoir Engineering and Simulation Methods
Établissements canadiensConocoPhillips (Canada)
Organismes subventionnairesConocoPhillips
Mots-clésWorld Wide WebComputer scienceInformation retrievalKeyword searchLibrary science

Résumé

récupéré en direct d'OpenAlex

Promoting Real-Time Optimization of Hydrocarbon Producing Systems L.A. Saputelli; L.A. Saputelli PDVSA Search for other works by this author on: This Site Google Scholar S. Mochizuki; S. Mochizuki ExxonMobil Search for other works by this author on: This Site Google Scholar L. Hutchins; L. Hutchins BP Search for other works by this author on: This Site Google Scholar R. Cramer; R. Cramer Shell Search for other works by this author on: This Site Google Scholar M.B. Anderson; M.B. Anderson Schlumberger Search for other works by this author on: This Site Google Scholar J.B. Mueller; J.B. Mueller Schlumberger Search for other works by this author on: This Site Google Scholar A. Escorcia; A. Escorcia Halliburton Search for other works by this author on: This Site Google Scholar A.L. Harms; A.L. Harms ConocoPhillips Search for other works by this author on: This Site Google Scholar C.D. Sisk; C.D. Sisk BP Search for other works by this author on: This Site Google Scholar S. Pennebaker; S. Pennebaker ITSVE Search for other works by this author on: This Site Google Scholar J.T. Han; J.T. Han ITSVE Search for other works by this author on: This Site Google Scholar A. Brown; A. Brown EPS Search for other works by this author on: This Site Google Scholar C.S. Kabir; C.S. Kabir ChevronTexaco Search for other works by this author on: This Site Google Scholar R.D. Reese; R.D. Reese Case Services Search for other works by this author on: This Site Google Scholar G.J. Nunez; G.J. Nunez ITSVE Search for other works by this author on: This Site Google Scholar K.M. Landgren; K.M. Landgren Schlumberger Search for other works by this author on: This Site Google Scholar C.J. McKie; C.J. McKie EPS Search for other works by this author on: This Site Google Scholar C. Airlie C. Airlie EPS Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Offshore Europe Oil and Gas Exhibition and Conference, Aberdeen, United Kingdom, September 2003. Paper Number: SPE-83978-MS https://doi.org/10.2118/83978-MS Published: September 02 2003 Connected Content Related to: Promoting Real-Time Optimization of Hydrocarbon-Producing Systems Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Saputelli, L.A., Mochizuki, S., Hutchins, L., Cramer, R., Anderson, M.B., Mueller, J.B., Escorcia, A., Harms, A.L., Sisk, C.D., Pennebaker, S., Han, J.T., Brown, A., Kabir, C.S., Reese, R.D., Nunez, G.J., Landgren, K.M., McKie, C.J., and C. Airlie. "Promoting Real-Time Optimization of Hydrocarbon Producing Systems." Paper presented at the SPE Offshore Europe Oil and Gas Exhibition and Conference, Aberdeen, United Kingdom, September 2003. doi: https://doi.org/10.2118/83978-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Offshore Europe Conference and Exhibition Search Advanced Search AbstractThe term "Real-Time Optimization" (RTO) has rapidly found its way into common usage in the oil and gas industry, as it already has in many others. However, RTO in the oil and gas industry is usually used more as a slogan rather than describing a system or process that truly optimizes anything at all, let alone does so in real-time.In this paper, we describe what RTO means in the exploitation of hydrocarbons and what technologies are available now and are likely to be available in the future. We discuss how it is misunderstood and what real financial benefits await those who adopt it. Furthermore, we are working toward developing a method of classification to allow us to establish where a field operation lies on the RTO ladder, and to help plan a strategy to generate the benefits that moving up the RTO ladder can offer on specific fields and assets. The paper also describes a new SPE Technical Interest Group (TIG), explaining why it has been formed, and outlining its objectives and some planned deliverables.Real-time Optimization - Concepts and DefinitionsWhat is optimization?Intuitively most people agree on what we mean by "optimize." This comes down to understanding the dictionary definition; that is, to make the most of; to plan or carry out an economic activity with maximum efficiency; to find the best compromise among several often conflicting requirements, as in engineering design. Therefore, examples of what is usually meant by optimization in the oil and gas industry include:Maximizing hydrocarbon production or recovery,Finding the best solution in the region of physical and financial constraints to produce a decision,Maximizing net present value (NPV) through changes in capital expenditure (CAPEX) and/or operational expenses (OPEX). These elements, in turn, improve financial efficiency in portfolio management and risk analysis, andAdvanced real-time optimization: behavioral prediction and inference, pattern recognition to identify states of a group of wells, continuous adaptation and self-tuning ability.Although we may readily agree on these (and other) descriptions of what would be the outcome of optimization, agreeing what it actually means appears to be more complex. The reason for this is that the term optimization is usually used very loosely, whereas it needs to be defined rigorously and mathematically, while honoring the real-life physical system constraints that exist in the overall production process. Keywords: constraint, artificial intelligence, modeling, society of petroleum engineers, classification, sensor, data acquisition, application, real-time optimization, production optimization Subjects: Information Management and Systems, Artificial intelligence This content is only available via PDF. 2003. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,047
Score d'incertitude au seuil0,678

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
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 Opus0,013
Tête enseignante GPT0,225
Écart entre enseignants0,212 · 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