MétaCan
Menu
Back to cohort
Record W4296848732 · doi:10.3390/min12101188

Unconventional Gas Geochemistry—An Emerging Concept after 20 Years of Shale Gas Development?

2022· article· en· W4296848732 on OpenAlexafffund
Jaime César

Bibliographic record

VenueMinerals · 2022
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
FundersNatural Resources Canada
KeywordsKerogenNatural gasOil shaleIsotopes of carbonShale gasSource rockGeochemistryCrackingStable isotope ratioGeologyChemistryEnvironmental chemistryPaleontologyTotal organic carbon

Abstract

fetched live from OpenAlex

Geochemical studies of gases from low-permeability reservoirs have raised new questions regarding the chemical and stable isotope systematics of gas hydrocarbons. For instance, the possibility of thermodynamic equilibrium is recurrently in discussion. However, it is not clear whether there is anything “unconventional” in the way these systems continue to be studied. Using molecular and stable carbon isotope data from North American unconventional and conventional reservoirs, this research has applied two parameters that well describe key transformation stages during gas generation. The δ13C of ethane and the C2/C3 ratio increase from baseline values (<1%Ro, prominent kerogen cracking) until a first inflexion at 1.5%Ro. The same inflexion leads to 13C depletion of ethane and a rapidly increasing C2/C3 ratio as hydrocarbon cracking becomes prominent. The transition between these two stages is proposed to be a crossover from equilibrium to non-equilibrium conditions. There is no evidence for these characteristics to be limited to low-permeability reservoirs. Unconventional gas geochemistry should represent an approach that acknowledges that chemical and isotope distributions are not ruled by only one mechanism but several and at specific intervals of the thermal history.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.995

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)0.0060.000

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 head0.013
GPT teacher head0.229
Teacher spread0.216 · 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 teacher head, not a consensus.

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

Citations4
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueMineralsSame topicHydrocarbon exploration and reservoir analysisFrench-language works237,207