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Record W4247227018 · doi:10.2523/107952-ms

Incorporating Geomechanics into Petroleum Reservoir Numerical Simulation

2007· article· en· W4247227018 on OpenAlexaffabout
Luís Vaz Rodrigues, Luciane Cunha, Richard J. Chalaturnyk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
FundersPetrobras
KeywordsGeomechanicsCitationGlauberPetroleumPetroleum engineeringGeologyExcavationArchaeologyComputer scienceLibrary scienceGeographyGeotechnical engineeringPaleontology

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.246
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2007
Admission routes2
Has abstractyes

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