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A Comprehensive Model Coupling Embedded Discrete Fractures, Multiple Interacting Continua, and Geomechanics in Shale Gas Reservoirs with Multiscale Fractures

2017· article· en· W2734996469 on OpenAlexafffund
Kun Wang, Hui Liu, Jia Luo, Keliu Wu, Zhangxin Chen

Bibliographic record

VenueEnergy & Fuels · 2017
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology FuturesCMG Reservoir Simulation FoundationInternational Business Machines Corporation
KeywordsGeomechanicsHydraulic fracturingGeologyPetroleum engineeringOil shalePermeability (electromagnetism)Tight gasUnconventional oilReservoir simulationMatrix (chemical analysis)Fluid dynamicsFlow (mathematics)Fracture (geology)Geotechnical engineeringMechanicsMaterials scienceChemistry

Abstract

fetched live from OpenAlex

Shale gas has become one of the primary energy resources during the past few years, and its impact has been profound in many countries. Hydraulic fracturing treatments are required for the development of shale gas reservoirs, and the consequent hydraulic fractures usually connect with the original small-scale natural fractures forming complex fracture networks in these reservoirs. Therefore, a model for numerical simulation, which is capable of accurately modeling naturally and hydraulically fractured reservoirs, is essential in optimization and management of such reservoirs. In this paper, we develop a comprehensive model that couples embedded discrete fractures, multiple interacting continua, and geomechanics to accurately simulate the fluid flow in shale gas reservoirs with multiscale fractures. Large-scale hydraulic fractures are described by an embedded discrete fracture method, while middle-scale and small-scale natural fractures are modeled by a multiple interacting continua method. Usually, the connection of matrix–natural fractures–hydraulic fractures–wells is considered as the main pathway for the gas flow from a reservoir to a production well. However, geomechanics effects are significant in fractured reservoirs, which may lead to the closure of fractures and a dramatic decrease in gas conductivity in the fractures during the depletion of pressure. When the permeability of fractures is close to that of matrix, the gas production directly from the pathway of matrix–hydraulic fractures–wells as well as the fluid flow in shale matrix cannot be ignored. To accurately predict the fluid flow and well performance, the geomechanics effects and all the possible connections between different regimes must be taken into account. We implement this comprehensive model in our in-house reservoir simulator and study its behavior by numerical experiments. According to the numerical simulation results, accurate and comprehensive production prediction is performed, and reasonable physical phenomena is captured. Sensitivity studies are also performed to show the impacts of different parameters on the prediction of well performance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.248
Teacher spread0.237 · 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.

Study designSimulation or modeling
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

Citations61
Published2017
Admission routes2
Has abstractyes

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