Incorporating Geomechanics into Petroleum Reservoir Numerical Simulation
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Résumé
Incorporating Geomechanics into Petroleum Reservoir Numerical Simulation 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 Paper presented at the Rocky Mountain Oil & Gas Technology Symposium, Denver, Colorado, U.S.A., April 2007. Paper Number: SPE-107952-MS https://doi.org/10.2118/107952-MS Published: April 16 2007 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Rodrigues, Luis Glauber, Cunha, Luciane Bonet, and Richard J. Chalaturnyk. "Incorporating Geomechanics into Petroleum Reservoir Numerical Simulation." Paper presented at the Rocky Mountain Oil & Gas Technology Symposium, Denver, Colorado, U.S.A., April 2007. doi: https://doi.org/10.2118/107952-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 Rocky Mountain Petroleum Technology Conference / Low Permeability Reservoirs Symposium Search Advanced Search AbstractThere is currently a need in rock engineering for a coherent approach, which allows the identification and incorporation of the important parameters and mechanisms for any rock engineering activity. This is the case of reservoir numerical simulation studies of oil/gas recovery strategies in which geomechanical effects play an important role on the underlying physics of the recovery process. For example, during the depletion phase or the cold-water injection of high-pressure/high-temperature reservoirs, the stress state in and around a reservoir can change dramatically. This process might result in rock movements such as compaction, improvement of natural fractures, induced fracturing, and fault activation, which continuously modify the reservoir properties such as the porosities, the permeabilities and the fault transmissibilities. Modifications of such parameters strongly influence the flow pattern in the reservoir and ultimately the final recovery factor. In this work, a methodology is developed which enables the incorporation of key mechanisms and parameters to solve a numerical reservoir simulation problem that considers geomechanical aspects. The proposed technique utilizes an iterative-coupled reservoir-geomechanical modeling approach to capture the link between flow and in-situ stresses. In a validation stage, results from the coupled model are compared to ones obtained from a classical simulation approach (constant rock compressibility model). The usefulness of technique developed here is illustrated for reservoir performance forecasting of a giant Brazilian deepwater oilfield producing by water injection. The solution achieved to the real case problem revealed important geomechanical features that must be considered in complex oil exploitation project scenarios in which limited information and production uncertainties are present.IntroductionThere are five critical areas in the process of modeling deepwater reservoirs. These are geological and geophysical modeling, reservoir characterization, reservoir flow modeling, facilities/flow assurance, and uncertainties/risk analyses. This paper will focus more on reservoir flow modeling of deepwater reservoir with uncertainties.Deepwater reservoirs cause significant challenges worldwide to companies exploring and producing such reservoirs because of the high exploration, development, and production costs. Proper modeling of deepwater reservoirs provides companies with tools to evaluate these reservoirs and quantify risks associated with their development.This paper describes a general modeling process that improves reservoir understanding and performance forecasting. These factors are extremely important in the high cost, high-risk deepwater environment, where wrong decisions lead to expensive mistakes and can materially affect a company's financial standing.Petrobras (Brazil) in 2004 shut part of a giant field in offshore Campos's basin in Rio de Janeiro coast. This famous basin is responsible for almost 80% of the total production of the company. Due to the high viscosity of the reservoir fluids for offshore conditions, a water injection project was conceived and water was planned to be injected from the beginning of production. Some onshore studies indicated that a high injection pressure would be of practical use in offshore conditions due to the need of manipulation of wastewater to satisfy environmental needs [1].The main reason for this managerial decision was an abrupt oil surge or leak to sea floor. This environmental problem was immediately solved with the shut of one water injection well and three oil production wells. Although the field was under reservoir control of history match and continuous monitoring of the reservoir pressure, a steep and identified increase in reservoir pressure probably caused reactivation of a fracture that was linked with the sea floor.Petrobras has a wide portfolio and another field, which is the focal point of this work, is being considered as a candidate for a water injection project. Field "A" is located in Brazil and some of its properties have been described in Ref. [2]. Additional aspects to be considered are:The fault throw is 60m and this information is important to define the size of the grid during refinement of the model.The conclusion obtained in reference [2] was the main motivation for this work. It is stated there that the field should be considered for further investigation considering geomechanics aspects aiming to reducing uncertainties in reservoir behavior forecast. Keywords: Modeling & Simulation, Reservoir Characterization, compressibility, reservoir geomechanics, volumetric strain, injection pressure, depletion case, variation, porosity, injection Subjects: Reservoir Characterization, Reservoir geomechanics This content is only available via PDF. 2007. Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».