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Enregistrement W1986386835 · doi:10.2118/2001-057

Rehabilitating Heavy Oil Wells Using Pulsing Workovers to Place Treatment Chemicals

2001· article· en· W1986386835 sur OpenAlexaboutno aff
Maurice B. Dusseault, C. M. Gall, D. Shand, Brett Davidson, Kirby Hayes

Notice bibliographique

RevueCanadian International Petroleum Conference · 2001
Typearticle
Langueen
DomaineEngineering
ThématiqueDrilling and Well Engineering
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPetroleum engineeringEnvironmental sciencePetroleumWaste managementComputer scienceGeologyEngineering

Résumé

récupéré en direct d'OpenAlex

Abstract Workover chemicals were placed in a group of seven CHOPS wells in the Sparky and GP zones of the Canadian Heavy Oil Belt. Rather than direct injection, the chemicals were placed using aggressive pressure pulsing over a period of 7–10 hours. A three-month postworkover assessment shows that each well is producing far more total liquids than before the workover, and that the oil-to-water ratio has improved greatly. For the seven wells, oil production rates three months after the workover were approximately 5 times the rates before the workover. Chemical placement in these wells that co-produce sand appears to be much more successful if pulsing is used, and this is attributed to a much more efficient dispersion mechanism associated the dynamic excitation. Instead of channeling out into the formation and being recovered largely undiluted after production is reinitiated, it appears that the pulsing mixed the chemicals much more thoroughly in the formation and that channeling and chemical isolation were suppressed. Importantly, the new method provided payback within 60 days of the workover termination. Introduction Aggressive pressure pulsing as a workover method for oilwells was introduced in the Canadian oil industry less than three years ago (Sept 1998) 1,2. The method was proposed based on a two-year long series of laboratory experiments that demonstrated flow rate increases during active pulsing.3 Assessment of the probable reservoir reasons for oil production decline in CHOPS (Cold Heavy Oil Production with Sand) wells led to the conclusion that pulsing workovers could help revitalize poor wells, and even turn non-producing wells into economic producers. The first 100 or so workovers in Canada were carried out without chemical placement, and an increasing success ratio was achieved, based on gradually better screening criteria and better understanding of the process effects in the reservoir. Chemicals are added to wells to affect the conditions in the reservoir and achieve better production. In limestones, acidizing is widely used, and acids may also be used to dissolve clay minerals blocking sandstone pores in the near-wellbore region. In siliceous sandstones containing heavy oil, issues such as surface tension, permeability channeling, asphaltene and wax precipitation and wettability changes can often be addressed by chemical placement. However, in high viscosity oils in high porosity sandstones that have been exploited by CHOPS, chemical placement has in general not achieved a high success ratio. This can be attributed to a number of factors, discussed in more detail below. Several years ago, it became apparent that placing chemicals with aggressive pulsing would likely achieve better results than simple injection. This judgment was based on the initial workovers carried out in 1999–2000. An opportunity to test this idea on a group of CHOPS wells in the Heavy Oil Belt presented itself in late 2000. CHOPS WELL BEHAVIOR Using CHOPS implies maintaining continuous sand influx in order to sustain economical oil production.4

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 candidatesMéta-épidémiologie (sens strict)
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 enseignants0,133
Score d'incertitude au seuil1,000

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 Opus0,016
Tête enseignante GPT0,229
Écart entre enseignants0,213 · 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.

Devis d'étudeSimulation ou modélisation
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

Citations8
Publié2001
Routes d'admission1
Résumé présentoui

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