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Record W4388960958 · doi:10.22158/se.v8n4p92

Semi-Analytical Modeling of Fractured Horizontal Wells in Heterogeneous Formations Considering the Interference between Hydraulic Fractures

2023· article· en· W4388960958 on OpenAlexaff
Fangdong Zhou, Yanwen Yu, Pinlu Cao, Liangliang Jiang, Shanshan Yao

Bibliographic record

VenueSustainability in Environment · 2023
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeologyFlow (mathematics)Fluid dynamicsInterference (communication)Hydraulic fracturingTransient (computer programming)Petroleum engineeringGeotechnical engineeringMechanicsComputer scienceChannel (broadcasting)

Abstract

fetched live from OpenAlex

In this study, a semi-analytical model is developed for the pressure and rate transient analysis of multi-stage fractured horizontal wells. This model simulates the fluid flow towards a fractured horizontal well centered in an unconventional formation with considering the interferences between hydraulic fractures under various heterogeneity conditions. In this proposed model, the formation is divided into sub-systems, and each sub-system is further composed of linear flow regions. Boundaries of the linear flow regions are being updated in real-time response to the interferences between hydraulic fractures. Applicability of the proposed model in heterogeneous reservoirs is demonstrated by the comparison with the five-region model published in literature. The proposed model is applicable to the heterogeneity conditions including a fractured horizontal well having heterogeneous completions and/or the formation being heterogeneous in reservoir properties. Furthermore, the proposed model is utilized to analyze field data from fractured horizontal wells in heterogeneous conditions.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.013
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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