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Record W4206617032 · doi:10.4095/329266

Hydrogen sulfide (H2S) distribution in the Triassic Montney Formation of the Western Canadian Sedimentary Basin

2021· report· en· W4206617032 on OpenAlexaffabout
Andrew Kingston, Andrew J. Mort, C Deblonde, Omid H. Ardakani

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGeologyStructural basinSedimentary basinSedimentary rockHydrology (agriculture)GeochemistryGeomorphology

Abstract

fetched live from OpenAlex

The Montney Formation is a highly productive hydrocarbon reservoir that is of great economic importance to Canada, however production is often dogged by the presence of hydrogen sulfide (H2S), a highly toxic and corrosive gas. Mapping H2S distribution across the Montney basin in the Western Canadian Sedimentary Basin (WCSB) is fundamental to understanding the processes responsible for its occurrence. We derive a Montney-specific dataset of well gas and water geochemistry from the publically available archives of the Alberta Energy Regulator (AER) and British Columbia Oil and Gas Commission (BCOGC) conducting quality assurance and control procedure before spatial interpolation. Empirical Bayesian Kriging is used to interpolate H2S across the whole Montney basin resulting in maps of H2S from hydrocarbon gas, condensates, and water; along with maps of sulfate and chloride ions in water. These interpolations illustrate the heterogeneous distribution of H2S across the basin with the highest concentrations in the Grande Prairie area along with several other isolated regions. Maps of H2S in gas, condensates, and water exhibit similar trends in H2S concentrations, which with future research may help elucidate the origin of H2S in the Montney.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

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