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Record W4281789090 · doi:10.1021/acsomega.2c00436

Pore Structure Characteristics and Adsorption and Desorption Capacity of Coal Rock after Exposure to Clean Fracturing Fluid

2022· article· en· W4281789090 on OpenAlex
Weiqin Zuo, Wenming Zhang, Yanwei Liu, Hongkai Han, Cheng Zhi Huang, Wenji Jiang, Hani S. Mitri

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS Omega · 2022
Typearticle
Languageen
FieldEngineering
TopicCoal Properties and Utilization
Canadian institutionsMcGill University
FundersHenan Polytechnic UniversityChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsCoalAdsorptionDesorptionVolume (thermodynamics)Microporous materialMethaneChemical engineeringPetroleum engineeringCoalbed methaneSpecific surface areaMaterials scienceMineralogyChemistryCoal miningGeologyComposite materialOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

adsorption method and scanning electron microscopy (SEM) were used to characterize coal samples. Using gas adsorption/desorption tests, high-, medium-, and low-rank coal samples before and after the clean fracturing fluid treatment were systematically studied. According to the relationship between coal pore structure parameters and gas adsorption/desorption characteristics, a correlation between the microscopic pore structure and the macroscopic gas adsorption/desorption characteristics of coal was obtained. The results show that the number of closed pores in high-, medium-, and low-rank coal samples increased after the clean fracturing fluid treatment. The micropore volume increased by 0.0009, 0.00143, and 0.0035 mL/g, respectively, and the specific surface area increased by 4.87, 9.06, and 57.60%. The fractal dimension also increased compared with that of raw coal. SEM analysis indicated that the influence degree of clean fracturing fluid treatment on the pore structure of different-rank coal samples was Gengcun low-rank coal > Pingba middle-rank coal > Jiulishan high-rank coal. The experimental results of methane adsorption and desorption showed that the adsorption capacity of the coal samples after clean fracturing fluid treatment was enhanced, which is related to increases in the micropore proportion, micropore volume, and specific surface area of the coal. The desorption capacity of the coal samples was also enhanced. The desorption rate of medium- and high-rank coal samples increased after the clean fracturing fluid treatment but that of low-rank coal samples decreased. The main reason is the increase in the number of micropores in low-rank coal, which enhances the gas adsorption ability and makes gas desorption difficult. Therefore, clean fracturing fluid is suitable for medium- and high-grade metamorphic coalbed methane mines. These research results provide a theoretical basis for the application of clean fracturing fluid in different coalbed methane 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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score0.370

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)0.0000.000

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 head0.009
GPT teacher head0.180
Teacher spread0.171 · 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