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Record W4412902377 · doi:10.1063/5.0274824

Numerical simulation of fully coupled two-phase flow and geomechanics in complex fracture networks of tight oil reservoir

2025· article· en· W4412902377 on OpenAlexaff
Jinchong Zhou, Renyi Cao, Zhihao Jia, Linsong Cheng, Bo Zhang, Rick Chalaturnyk

Bibliographic record

VenuePhysics of Fluids · 2025
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
FundersNational Major Science and Technology Projects of ChinaChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsGeomechanicsPhysicsTwo-phase flowFracture (geology)MechanicsFlow (mathematics)Multiphase flowPhase (matter)Petroleum engineeringGeotechnical engineeringGeology

Abstract

fetched live from OpenAlex

In tight oil reservoirs, water huff and puff serves as an effective recovery technique by replenishing formation energy and stabilizing production of volumetric fractured horizontal wells. However, fully coupled flow–geomechanics models currently available are limited in accounting for nonlinear flow characteristics and impose strict mesh constraints under complex geometry conditions. To address these challenges, a numerical model integrating fully coupled flow and geomechanics is established. The model incorporates nonlinear flow behavior and is constructed on the three-dimensional projection-based embedded discrete fracture model (3DpEDFM) to characterize four-dimensional in situ stress evolution during long-term waterflooding and water huff and puff processes in tight reservoirs. Notably, this study presents the first integration of 3DpEDFM with the virtual element method for coupled flow and geomechanics, enabling accurate simulation of complex fracture–matrix interactions without relying on conforming grids. The governing flow and mechanical equations are, respectively, discretized by the finite volume and virtual element methods, leading to a fully coupled nonlinear system that is solved using Newton–Raphson iterations. The model's reliability is demonstrated by benchmarking against the classical Mandel problem and numerical outputs from the commercial simulator tNavigator under idealized scenarios. A case study is further designed according to the geological features of a representative tight reservoir in China, involving long-term waterflooding and water huff and puff implemented via a volumetric fractured horizontal well injection–production system. The simulation results are used to investigate changes in flow behavior and in situ stress evolution. A reduction in horizontal principal stress differences within the stimulated reservoir volume is achieved through the application of water huff and puff, which in turn promotes the development of a complex fracture network and boosts horizontal well productivity.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.270
Teacher spread0.259 · 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
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

Citations3
Published2025
Admission routes1
Has abstractyes

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