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Record W7106694076 · doi:10.1080/12269328.2025.2593531

Optimization study of production system based on the return rule of shale gas wells

2025· article· en· W7106694076 on OpenAlexaff

Bibliographic record

VenueGeosystem Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsShale gasPressure systemProduction (economics)Production system (computer science)System optimizationOil shale

Abstract

fetched live from OpenAlex

In view of the transformation of global energy structure and the importance of efficient shale gas extraction, a scientific and reasonable reentry strategy has a decisive impact on capacity release, reservoir protection and economic benefits. By establishing a fracturing fluid drainage model of shale gas fracture system and matrix system, the process of fracturing fluid drainage in the fracture system to the wellbore is clarified, and an empirical formula for the drainage pattern of gas wells is derived based on the relationship between the relative permeability of gas and water. Based on this, the optimal production system for various types of shale gas wells during the stable production period is calculated by using the field measurement data and wellhead throttling theoretical model in combination with the characteristics of different types of shale gas wells in terms of return and discharge to ensure that the production capacity is maximized and the reservoir energy is maintained, so as to realize the sustainable development of shale gas wells.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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