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Record W2005289150 · doi:10.2118/149200-ms

Advancements in Understanding and Enhancing Biogenic Methane Production from Coals

2011· article· en· W2005289150 on OpenAlexafffundabout
Karen Budwill, Susan Koziel, John Vidmar

Bibliographic record

VenueCanadian Unconventional Resources Conference · 2011
Typearticle
Languageen
FieldEngineering
TopicCoal Properties and Utilization
Canadian institutionsAlberta Innovates
FundersGenome AlbertaGenome Canada
KeywordsCoalMethaneNutrientEnvironmental sciencePopulationEnvironmental chemistryCarbon fibersChemistryGeologyMaterials science

Abstract

fetched live from OpenAlex

Abstract It is estimated that only 5% of Alberta’s CBM reserves are recoverable (Rieb, 2006). A variety of techniques such as horizontal drilling and new fracturing methods have allowed greater recoveries of the methane gas. Alberta Innovates – Technology Futures (formerly the Alberta Research Council) is developing a biotechnology that stimulates and enhances biogenic methane production coal seams. Biogenic methane production is believed to have occurred in the geological past, and is believed to be still occurring in deep, subsurface coal seams albeit at extremely slow rates. It is postulated that the native microorganisms are nutrient limited and, based on laboratory evidence, by adding an organic, nitrogen-rich nutrient, the methane production rate can be increased up to 30-fold over non-amended cutlures. The microbial diversity of Alberta coal seams has begun to be mapped out using state-of-the-art genomic sequencing techniques. It appears the geophysical environment has a strong influence on the types of microbes present as the microbial populations from deeper, more saline Mannville coals are significantly different than the microbes detected in Horseshoe Canyon coals. The microbial population changes upon addition of a nutrient, with shifts occurring in the types of fermenting organisms and methanogenic species. Low molecular weight monocarboxylic acids were observed to be produced and then consumed over the incubation period. These methanogenic precursor substrates accumulated in cultures with only nutrient and no coal. Much lower methane production occurred in these cultures suggesting an unbalanced nutritional state, whereas those cultures with un-limiting carbon from coal and nitrogen source from the nutrient generated large amounts of methane. The effects of surface area, bioavailability of coal moieties and coal porosity and permeability on biogenic methane production are under investigation. Results will aid in the design and deployment of an effective enhanced biogenic methane coal bed field trial.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.081
GPT teacher head0.208
Teacher spread0.128 · 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 designBench or experimental
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

Citations2
Published2011
Admission routes3
Has abstractyes

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