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Enregistrement W4240997993 · doi:10.2523/94024-ms

New Economic Indicator to Evaluate SAGD Performance

2005· article· en· W4240997993 sur OpenAlexaffabout
Hyundon Shin, M. Polikar

Notice bibliographique

RevueProceedings of SPE Western Regional Meeting · 2005
Typearticle
Langueen
DomaineEngineering
ThématiqueEnhanced Oil Recovery Techniques
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésCitationComputer scienceOperations researchInformation retrievalEnvironmental scienceLibrary scienceEngineering

Résumé

récupéré en direct d'OpenAlex

New Economic Indicator to Evaluate SAGD Performance Hyundon Shin; Hyundon Shin Search for other works by this author on: This Site Google Scholar Marcel Polikar Marcel Polikar U. of Alberta Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Western Regional Meeting, Irvine, California, March 2005. Paper Number: SPE-94024-MS https://doi.org/10.2118/94024-MS Published: March 30 2005 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Shin, Hyundon, and Marcel Polikar. "New Economic Indicator to Evaluate SAGD Performance." Paper presented at the SPE Western Regional Meeting, Irvine, California, March 2005. doi: https://doi.org/10.2118/94024-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Western Regional Meeting Search Advanced Search AbstractThe steam-assisted gravity drainage (SAGD) process simulations described in this study have been optimized to have the lowest cumulative steam-oil ratio (CSOR), highest RF and highest CDOR in order to obtain optimal operation conditions. In addition, net present value (NPV) calculations were performed for each simulation case to take the time factor into account.A simple thermal efficiency parameter (STEP), based on CSOR, CDOR and RF for the time corresponding to SOR = 4, was developed to evaluate the performance of a SAGD project under optimized conditions. A linear relationship was found to exist between STEP and NPV, with a correlation coefficient in excess of 0.96 for most of the cases studied. For each simulation case, highest values of NPV and STEP indicated optimum SAGD operating conditions.IntroductionThe steam-assisted gravity drainage (SAGD) process has been tested in the field and has proven to be an effective recovery method with more than 50% recovery efficiency in the Alberta oil sands (Athabasca, Cold Lake and Peace River deposits).Before a SAGD project is implemented in the field, a sensitivity analysis is usually required for optimizing the SAGD operating conditions: pre-heating period, steam injection pressure, steam injection rate and injector to producer spacing (I/P spacing). The economics of a SAGD project are related to several production performance parameters.The most significant of those are steam-oil ratio (SOR), ultimate recovery (recovery factor RF), calendar day oil rate (CDOR), and project life. Our main goal is to maximize oil production with the least amount of steam and in the shortest time.There is very little research regarding an economic indicator for thermal recovery. Kisman and Ruitenbeek1 introduced a performance indicator for thermal recovery. They developed a model for the economic and performance evaluation of thermal recovery projects including steam stimulation, steam drive and combustion processes.In this research, a new simple economic parameter, named STEP (simple thermal efficiency parameter), was introduced to optimize SAGD operating conditions for Athabasca, Cold Lake, and Peace River type reservoirs. Four operating conditions were optimized for the SAGD process. They are:preheating period, I/P spacing, steam injection pressure, and steam injection rate.The net present value (NPV) of each case is first calculated for optimized SAGD performance. Then, STEP is calculated from three performance parameters: CSOR, CDOR, and RF.Finally, STEP is correlated with NPV for each optimized case.Development of new economic indicatorThe SAGD simulations described in this study have been optimized to have the lowest cumulative steam-oil ratio (CSOR), highest RF and highest CDOR in order to obtain optimal operating conditions.If a case has the lowest CSOR and the highest CDOR and RF, this gives the optimal operating conditions. However, there are cases which have low CSOR and low RF or CDOR. In this case, it is difficult to optimize operating conditions without an economic parameter such as NPV or rate of return.STEP was introduced and developed for being used as a simple economic indicator during the SAGD optimizing procedure instead of NPV.In this study, the economic calculations assume that a project is cost-effective as long as the instantaneous SOR is below a value of 4.Capital costs have not been taken into account, assuming that these are similar for all the cases studied because the same well configurations and development plan are considered. NPV calculations only considered the cost of steam ($5/bbl) and price of bitumen ($20/bbl), at a 10% discount rate. Keywords: npv, injection rate, correlation coefficient, steam injection rate, river type reservoir, steam-assisted gravity drainage, csor, reservoir, thermal method, cdor Subjects: Improved and Enhanced Recovery, Thermal methods This content is only available via PDF. 2005. 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.

Comment cette classification a été obtenuedéplier

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)0,000
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 enseignants0,642
Score d'incertitude au seuil0,879

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 Opus0,014
Tête enseignante GPT0,243
Écart entre enseignants0,229 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2005
Routes d'admission2
Résumé présentoui

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