Risk Analysis for Water Injection in a Petroleum Reservoir ConsideringGeomechanical Aspects
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Résumé
Risk Analysis for Water Injection in a Petroleum Reservoir Considering Geomechanical Aspects Luis Glauber Rodrigues; Luis Glauber Rodrigues Alberta University Search for other works by this author on: This Site Google Scholar Luciane Bonet Cunha; Luciane Bonet Cunha U. of Alberta Search for other works by this author on: This Site Google Scholar Richard J. Chalaturnyk; Richard J. Chalaturnyk U. of Alberta Search for other works by this author on: This Site Google Scholar Jose C.S. Cunha Jose C.S. Cunha U. of Alberta Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Eastern Regional Meeting, Canton, Ohio, USA, October 2006. Paper Number: SPE-104551-MS https://doi.org/10.2118/104551-MS Published: October 11 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Rodrigues, Luis Glauber, Cunha, Luciane Bonet, Chalaturnyk, Richard J., and Jose C.S. Cunha. "Risk Analysis for Water Injection in a Petroleum Reservoir Considering Geomechanical Aspects." Paper presented at the SPE Eastern Regional Meeting, Canton, Ohio, USA, October 2006. doi: https://doi.org/10.2118/104551-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 Eastern Regional Meeting Search Advanced Search AbstractEconomic and risk analysis are important tasks in a petroleum engineering study. This work considers the analysis of the results obtained from a real Brazilian offshore field simulation study in which the decision making process for field development is discussed considering geomechanical aspects. The focus is on the evaluation of uncertainties of geomechanical parameters that may influence the response of a petroleum reservoir submitted to seawater injection for secondary recovery. A decision tree has been built and solved using utility theory and the expected monetary value (EMV) concept. A sensibility analysis for different discount rates and oil prices has been also performed.First, this work identifies if the reservoir is a candidate for a deeper analysis using a matrix approach consisting of important geomechanical parameters. Second, lab stress information is used and the results obtained compared with the traditional reservoir simulation, which considers compressibility invariant with time. Third, a decision tree is constructed and solved. Based on the assumptions chosen for these analyses, it is concluded that coupled reservoirgeomechanics simulations should be applied in order to more precisely forecast reservoir performance.IntroductionThe application of geomechanics to reservoir engineering problems is relative new and is receiving more focus as the oil and gas industry begins to exploit unconventional hyrdrocarbon assets. The relative importance of geomechanics in this context, however, remains a question.In this work, a new methodology is developed which enables, through a comprehensive listing of some major geomechanical parameters, the establishment of the important mechanisms associated with these parameters and a method for assessing their relative importance. This methodology is demonstrated by the use of traditional simulation and geomechanical approach in an economics analysis using a decision tree approach to obtain the critical parameters.The focus for this study is an offshore unconsolidated sandstone reservoir field located in Campos Basin, Brazil. The field has undergone water injection since the beginning of production and was chosen for this study due to strong uncertainties related to project's development. As is typical, the amount of information is incomplete in the initial phase of a project and a sensitivity analysis must be done to justify the acquisition of additional information and to determine whether a simple black-oil model will be sufficient to assist with development decisions.As mentioned by Onaisi et al.1, flood breakthrough leads to local effective stress changes and compressibility or volume changes. The addition of these stress-dependent effects into traditional reservoir simulation parameters (e.g.: porosity, rock compressibility and permeability) show that they can impact reservoir productivity and fault transmissibility. For the Brazilian offshore field, an important issue is the possibility of fluid leaking from the reservoir to the seabed due to flow along existing fault structures. The determination of rock mechanics parameters in unconsolidated sandstones is also an important step to better characterize the rock, providing important inputs for better forecasts.Soares and Ferreira2 noted that in some reservoirs large deformations could occur during oil production. These deformations result from increasing effective stresses as the reservoir fluid pressure declines. As the rock structure changes, it may cause permanent damage to the reservoir lowering the permeability and the final oil recovery.In general, reservoir engineering studies do not take into account the effect of in situ stresses on production. In most cases, the permeability is assumed to remain constant along the oil production. However, for limestone and unconsolidated sandstone, as in the deepwater reservoirs of Campos Basin, Brazil, this assumption is likely not valid and a better understanding of reservoir-geomechanical processes will help optimize the ultimate recovery from these classes of reservoirs.The Field " A"The Field "A" is located southeast of Brazil in a water depth of 1,500m (Figure 1). The real oilfield name and exact position is not revealed due to confidentiality aspects. The reservoir model built to depict the field is shown in Figure 2. Keywords: Modeling & Simulation, Artificial Intelligence, volumetric strain, reservoir geomechanics, Upstream Oil & Gas, compressibility, Reservoir Characterization, reservoir simulation, discount rate, geomechanical parameter Subjects: Reservoir Characterization, Reservoir Simulation, Reservoir geomechanics This content is only available via PDF. 2006. 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 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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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 ».