Reservoir Modeling for Horizontal Exploitation of a Giant Heavy Oil Field - Challenges and Lessons Learned
Notice bibliographique
Résumé
Reservoir Modeling for Horizontal Exploitation of a Giant Heavy Oil Field - Challenges and Lessons Learned T. H. Tankersley; T. H. Tankersley Petrolera Ameriven Search for other works by this author on: This Site Google Scholar M.W. Waite M.W. Waite Petrolera Ameriven Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference, Calgary, Alberta, Canada, November 2002. Paper Number: SPE-78957-MS https://doi.org/10.2118/78957-MS Published: November 04 2002 Connected Content Related to: Reservoir Modeling for Horizontal Exploitation of a Giant Heavy-Oil Field Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Tankersley, T. H., and M.W. Waite. "Reservoir Modeling for Horizontal Exploitation of a Giant Heavy Oil Field - Challenges and Lessons Learned." Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference, Calgary, Alberta, Canada, November 2002. doi: https://doi.org/10.2118/78957-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 International Thermal Operations and Heavy Oil Symposium Search Advanced Search AbstractThe Hamaca Field, located in Venezuela's Orinoco Heavy Oil Belt, is a giant extra-heavy oil accumulation operated by Ameriven, an operating agent company for PDVSA, Phillips and ChevronTexaco. Over the 35-year life of the field, more than one thousand horizontal laterals are planned in order to deliver 190,000 BOPD to a heavy-oil upgrader facility. Reservoir models are built to support a broad continuum of activities in order to meet this objective. This paper will review the Hamaca reservoir modeling process, the challenge of integrating many sources of geologic and geophysical constraints including horizontal well information, the focus on continuous model improvement, and issues unique to Hamaca rock and fluid properties.BackgroundThe Hamaca Field is located in Venezuela's Orinoco Heavy Oil Belt, which is reported to contain more than 1.2 trillion barrels of heavy and extra heavy oil in a huge stratigraphic trap on the southern flank of the Oriente Basin (Fig. 1). The Hamaca concession area, which covers 160,000 acres, contains 8–10 API gravity oil trapped in shallow fluvial-deltaic reservoirs of the Oficina Formation (Miocene age). Sandstone reservoirs of the Oficina Formation at Hamaca were generally deposited in a bed-load dominated, fluvial-deltaic environment. Reservoir properties are excellent with porosity values of up to 36% and permeability values of up to 30 darcies. Hamaca crude is considered "foamy" and is generally saturated with gas at reservoir conditions1.Over the 35-year life of the field, over 1000 horizontal laterals are planned in order to deliver 190,000 BOPD to a heavy-oil upgrader facility, which is currently under construction1. To date, more than 110 horizontal wells have been drilled to produce from the Hamaca reservoirs. Oil is being produced under "cold production" methods, (no added heat) using progressive cavity pumps to bring oil to the surface. Cold production is possible due to the extended length of the horizontal wells (5000'), excellent reservoir properties and the "foamy oil" nature of Hamaca crude2. The heavy oil will be mixed with diluent just downstream of the wellheads to facilitate transport to the upgrader facility. The Hamaca crude will be converted to a sweeter crude product of approximately 26° API at the upgrader.The combined use of both well and seismic data is critically important for characterizing the stratigraphic complexity of the Hamaca fluvial-deltaic systems. To assist in targeting sweet spots for horizontal well placement, a 250 km2 3-D seismic survey was acquired along with the drilling of 91 stratigraphic information wells with an average separation distance of about 1.5 km. Keywords: variability, property pdf, variogram, upstream oil & gas, modeling & simulation, heterogeneity, gradient, reservoir characterization, artificial intelligence, permeability Subjects: Reservoir Characterization, Geologic modeling This content is only available via PDF. 2002. SPE/PS-CIM/CHOA International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference 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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».