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Record W4388095019 · doi:10.46690/ager.2023.11.05

Impact of key parameters on far-field temporary plugging and diverting fracturing in fractured reservoirs: A 2D finite element study

2023· article· en· W4388095019 on OpenAlexaff
Pingli Liu, Fengcheng Lou, Juan Du, Xiang Chen, Jinming Liu, Muming Wang

Bibliographic record

VenueADVANCES IN GEO-ENERGY RESEARCH · 2023
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersSouthwest Petroleum University
KeywordsHydraulic fracturingFracturing fluidGeologyPetroleum engineeringFracture (geology)Displacement (psychology)Finite element methodGeotechnical engineeringViscosityMaterials scienceEngineeringStructural engineeringComposite material

Abstract

fetched live from OpenAlex

Temporary plugging and diverting fracturing technology is of utmost importance in stimulating fractured reservoirs. However, studies investigating the mechanisms of new fracture initiation and propagation during far-field temporary plugging and diverting fracturing have been scarce, and the optimal technique parameters are still unknown. To address this issue, a two-dimensional fracturing model is developed via the finite element method in this work, which simulates the temporary plugging effect using the equivalent viscosity temporary blockage method and the unrestrained growth of hydraulic fractures by globally embedding the cohesive element of zero-thickness. Then, some key parameters for far-field temporary plugging and diverting fracturing in fractured reservoirs are discussed and some interesting insights are given. Firstly, a lower-permeability plugging zone expedites the pressure increase within the fracture, thereby boosting the probability of achieving temporary plugging and diverting fracturing. The size of the plugging zone significantly impacts the pressure increase within the fracture. Secondly, the plugging position should be determined considering the density and arrangement of natural fractures in the layer, and the temporary plugging construction should be performed after maximizing the elongation of initial hydraulic fracture. Thirdly, an increase in fluid viscosity and injection displacement promotes the pressure rise inside the fracture. Nonetheless, the impact of injection displacement on temporary plugging and diverting fracturing surpasses that of fluid viscosity. Overall, the established model can inform the design of temporary plugging and diverting fracturing in fractured reservoirs. Document Type: Original article Cited as: Liu, P., Lou, F., Du, J., Chen, X., Liu, J., Wang, M. Impact of key parameters on far-field temporary plugging and diverting fracturing in fractured reservoirs: A 2D finite element study. Advances in Geo-Energy Research, 2023, 10(2): 104-116. https://doi.org/10.46690/ager.2023.11.05

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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.349
Teacher spread0.320 · 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

Citations17
Published2023
Admission routes1
Has abstractyes

Explore more

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