Thermodynamic and hydrochemical controls on CH4 in a coal seam gas and overlying alluvial aquifer: new insights into CH4 origins
Bibliographic record
Abstract
Using a comprehensive data set (dissolved CH4, δ(13)C-CH4, δ(2)H-CH4, δ(13)C-DIC, δ(37)Cl, δ(2)H-H2O, δ(18)O-H2O, Na, K, Ca, Mg, HCO3, Cl, Br, SO4, NO3 and DO), in combination with a novel application of isometric log ratios, this study describes hydrochemical and thermodynamic controls on dissolved CH4 from a coal seam gas reservoir and an alluvial aquifer in the Condamine catchment, eastern Surat/north-western Clarence-Moreton basins, Australia. δ(13)C-CH4 data in the gas reservoir (-58‰ to -49‰) and shallow coal measures underlying the alluvium (-80‰ to -65‰) are distinct. CO2 reduction is the dominant methanogenic pathway in all aquifers, and it is controlled by SO4 concentrations and competition for reactants such as H2. At isolated, brackish sites in the shallow coal measures and alluvium, highly depleted δ(2)H-CH4 (<310‰) indicate acetoclastic methanogenesis where SO4 concentrations inhibit CO2 reduction. Evidence of CH4 migration from the deep gas reservoir (200-500 m) to the shallow coal measures (<200 m) or the alluvium was not observed. The study demonstrates the importance of understanding CH4 at different depth profiles within and between aquifers. Further research, including culturing studies of microbial consortia, will improve our understanding of the occurrence of CH4 within and between aquifers in these basins.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".