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Record W3212771024 · doi:10.1115/1.4052912

Semi-Analytical Model for the Transient Analysis of the Pressure in Vertically Fractured Wells in Reservoirs Considering the Influence of Natural Fractures

2021· article· en· W3212771024 on OpenAlexaff
Yiming Chen, Qiushi Zhang, Zhiming Zhao, Cunlei Li, Bo Wang

Bibliographic record

VenueJournal of Energy Resources Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsGeologyFracture (geology)Fluid dynamicsHydraulic fracturingFluid pressureMechanicsFlow (mathematics)Petroleum engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract In addition to artificial fractures generated by hydraulic fracturing technology, natural fractures distributed in reservoirs will also affect the fluid flow process. To study the transient behavior of the pressure in fluid flows in reservoirs containing natural fractures, a semi-analytical model for vertically fractured wells with complex natural fracture networks was established. This model was based on the linear source function theory and the fracture discretization and coupling methods. It was solved by the Stehfest numerical inversion and the matrix transformation. The results of the study on the fluid flow stages in a reservoir with natural fractures indicated that the presence of natural fractures increased natural fracture flows. These flows were dominated by natural fractures and fracture interference stages and were different from the fluid flows observed in vertically fractured wells with a single main fracture. The sensitivity analysis on the influences of the fluid flow factors in the reservoirs with three types of natural fractures could provide a more detailed reference for the identification of the reservoir parameters and the transient characteristics of the flow stage. The different characteristic curves of the fluid flow in the reservoirs with different scale natural fractures could also provide a theoretical basis for determining the distribution of natural fractures in reservoirs.

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)0.001
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 score0.035
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.227
Teacher spread0.221 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Energy Resources TechnologySame topicHydraulic Fracturing and Reservoir AnalysisFrench-language works237,207