MétaCan
Menu
Back to cohort
Record W3177169580 · doi:10.1007/s13202-021-01190-6

Evaluating geomechanical effects related to the production of a Brazilian reservoir

2021· article· en· W3177169580 on OpenAlexfundno aff
Raquel Oliveira Lima, Leonardo José do Nascimento Guimarães, Leonardo Pereira

Bibliographic record

VenueJournal of Petroleum Exploration and Production Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
FundersUniversidade Federal de PernambucoPetrobrasConselho Nacional de Desenvolvimento Científico e TecnológicoEnergi Simulation
KeywordsGeomechanicsOffshore geotechnical engineeringPermeability (electromagnetism)CompressibilityReservoir simulationReservoir engineeringPetroleum engineeringCoupling (piping)Oil fieldFinite element methodGeologyPorosityGeotechnical engineeringStress (linguistics)Petroleum reservoirFlow (mathematics)Pore water pressureMechanicsEngineeringPetroleumStructural engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract This paper presents a coupled finite element approach for modeling geomechanical effects induced by production/injection processes in petroleum reservoirs. The module developed employs coupled- reservoir analysis using CMG IMEX® as the flow simulator and a finite element program in MATLAB® as the stress–strain simulator, in a two-way explicit partial coupling scheme. The flow and mechanical problems are coupled by the change of effective stress due to the change in pore pressure and by varying stress-dependent reservoir properties, such as pore compressibility, absolute permeability, and porosity. The coupling procedure was applied to the Namorado Field (Campos Basin, Brazil) to quantify the impact of the rock deformation on fluid recovery. Based on the cases studied, the coupled analyses predicted higher oil recovery than the conventional reservoir simulations. The results showed that the reservoir deformation can affect its performance and must be taken into account in reservoir-engineering studies depending on production strategy and reservoir stiffness. Besides, the geomechanical calculations were performed only in the coupling timesteps, reducing the computational effort and making this coupling method feasible on a field scale.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.267
Teacher spread0.251 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Petroleum Exploration and Production TechnologySame topicDrilling and Well EngineeringFrench-language works237,207