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Record W4414225650 · doi:10.1016/j.fuel.2025.136828

Impacts of geological and operational parameters on the performance of in-situ coal gasification using linked vertical wells

2025· article· en· W4414225650 on OpenAlexaff
Shuyu Tian, Zhao Feng Tian, Chaoshui Xu, Liangliang Jiang, John Centofanti

Bibliographic record

VenueFuel · 2025
Typearticle
Languageen
FieldEngineering
TopicMining and Gasification Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCoalUnderground coal gasificationCoal miningSyngasCoal gasificationPollution

Abstract

fetched live from OpenAlex

In-situ coal gasification (ISG) is a technology that converts underground coal into syngas, which can be used for power generation or as a chemical feedstock for urea production. ISG technology eliminates the need to construct surface gasification facilities or undertake mining activities, mitigating potential air pollution and reducing associated health and safety risks. And it can be effectively employed to repurpose abandoned coal mines. In this study, a numerical model for ISG using the linked vertical well (LVW) method has been developed based on some coal seam data from the Leigh Creek coal mine in South Australia. The aim is to investigate the impacts of operational parameters (such as the space between the injection well and production well, pressure difference between the injection well and the production well, and injection rates) and geological parameters (such as coal seam depth, coal seam thickness, and coal permeability) on the heating value of syngas produced. The model incorporates a series of complex chemical reactions, including drying, pyrolysis, gasification and combustion. The predicted results have been compared with the field experimental data from a Leigh Creek ISG test project. The simulations revealed that for the investigated LVW processes in Leigh Creek brown coal mines, the produced heating value of syngas in most cases is around 8MJ/m 3 . The injection pressure primarily influences the cavity pressure during ISG operations. The pressure difference between the injection and product wells is crucial for controlling the injection rate. Higher injection rates lead to a faster decline in the unit heating value of syngas produced, but a higher total energy output. The investigated coal seam’s depth and thickness have minimal impacts on the heating value. Decreased coal permeability impedes air injection and significantly reduces the reactions and syngas heating value.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.030
GPT teacher head0.250
Teacher spread0.220 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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