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Record W4407768287 · doi:10.1063/5.0253410

Damage characteristics of shale with different bedding inclinations under high-pressure water jet impact after thermal treatment

2025· article· en· W4407768287 on OpenAlexfundno aff
Zhaolong Ge, Yuhuai Cui, Qinglin Deng, Jianming Shangguan, Zhi Yao, Zhongtan Li, Lei Liu, Binbin Ge

Bibliographic record

VenuePhysics of Fluids · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaNatural Science Foundation of ChongqingUniversity of Guelph
KeywordsPhysicsBeddingOil shaleJet (fluid)Water jetThermalPetroleum engineeringMechanicsMeteorologyWaste managementThermodynamics

Abstract

fetched live from OpenAlex

Water jet-assisted rock breaking is a conventional method for shale gas extraction. However, the complex conditions of deep shale reservoirs, including elevated temperatures and intricate stratification, obscure the rock-breaking mechanisms of jets. Therefore, this study conducted high-pressure water jet impact experiments on shale with five bedding angles (0°, 30°, 45°, 60°, and 90°) and four temperatures (room temperature, 100, 150, and 200 °C). Computed tomography (CT) and three-dimensional reconstruction techniques were used to analyze the damage characteristics. Results indicate that increased temperature significantly enhances rock-breaking efficiency. The crack volume fraction at 200 °C increased by 146.44 times compared to 25 °C. The new crack area exhibited a sharp increase from 100 to 150 °C compared to the slow increase rate before and after this temperature range, indicating the presence of a threshold temperature for effective fragmentation by jet impact. Damage showed significant anisotropy, with crack depth increasing with bedding angle and a through crack emerged at 90°, while the new crack area peaked at 45°. The jet rock-breaking efficiency index (JREI) was introduced which integrates crack volume, area, and depth to characterize the fragmentation efficiency at different temperatures and bedding conditions. These findings could provide a theoretical basis for enhancing the fragmentation of deep shale.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.008
GPT teacher head0.257
Teacher spread0.249 · 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 designObservational
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

Citations4
Published2025
Admission routes1
Has abstractyes

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