MétaCan
Menu
Back to cohort
Record W3003875375 · doi:10.1130/g46650.1

Direct evidence for fluid overpressure during hydrocarbon generation and expulsion from organic-rich shales

2020· article· en· W3003875375 on OpenAlexaff
Miao Wang, Yong Chen, Wyatt M. Bain, Guoqi Song, Keyu Liu, Zhenzhu Zhou, Matthew Steele‐MacInnis

Bibliographic record

VenueGeology · 2020
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOverpressureGeologyFluid inclusionsCalcitePetrologyHydrocarbonSedimentary rockVeinFluid dynamicsGeochemistryMineralogyQuartzPaleontology

Abstract

fetched live from OpenAlex

Abstract Fluid overpressures are widely expected during hydrocarbon generation and expulsion from source rocks, yet direct evidence for this phenomenon is lacking in the case of organic-rich shales. Here we show that formation of bed-parallel fibrous calcite veins in mature laminated organic-rich shales in the Eocene Dongying depression, Bohai Bay Basin, east China, occurred in direct response to fluid overpressure due to hydrocarbon generation. The evidence for overpressure is recorded by coexisting primary aqueous and petroleum inclusions in the calcite fibers. Our results show that all analyzed fluid-inclusion assemblages record variable degrees of overpressure during vein dilation, ranging from only modestly in excess of hydrostatic, to approaching and perhaps exceeding lithostatic. Thus, our results indicate that fluid pressures during dilation of horizontal veins are not necessarily equal to the opposing force of overburden throughout the history of opening. This suggests that at least some of the vein dilation is accommodated by concomitant narrowing of the adjacent wall-rock laminae, likely by scavenging (dissolution and reprecipitation) of CaCO3 from the adjacent wall rock.

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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.238
Teacher spread0.206 · 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

Citations73
Published2020
Admission routes1
Has abstractyes

Explore more

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