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Record W3209722456 · doi:10.3390/en14217088

Differential Thermal Evolution between Oil and Source Rocks in the Carboniferous Shale Reservoir of the Qaidam Basin, NW China

2021· article· en· W3209722456 on OpenAlexaff
Qianru Wang, Haiping Huang, Chuan He, Zongxing Li

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Calgary
FundersNational Natural Science Foundation of China
KeywordsSource rockGeologyOil shaleMaturity (psychological)KerogenVitriniteGeochemistryCarboniferousShale oilHydrocarbonTotal organic carbonMineralogyPetrologyStructural basinPaleontologySedimentary rockChemistryEnvironmental chemistry

Abstract

fetched live from OpenAlex

Shale oil and source rock samples of the Carboniferous Keluke Formation from well Chaiye 2 in the Delingha Depression were analyzed by gas chromatography–mass spectrometry. Source rocks were highly mature at the gas generation stage with vitrinite reflectance (Ro) of 1.45–1.88%. However, the oil produced from the shale reservoir was characterized by abundant biomarkers but low abundance of diamondoid hydrocarbons with estimated Ro of ca. 0.78%, indicating hydrocarbons were still at a relatively low thermal maturity level. As the crude oil was generated and accumulated autochthonously, preliminary results indicate that crude oil and source rocks witnessed differential thermal evolution and significant disparity of the current thermal maturity in the shale reservoir due to rapid tectonic subsidence and clay mineral catalysts that accelerated the thermal maturation process. Although tectonic uplifts occurred afterwards, the vitrinite recorded the highest maturity that source rocks have ever reached, whereas the oil has not reached the same maturity level due to less impact from thermal alteration or mineral catalysis than source rocks in the shale reservoir. Such a discovery enlarges the hydrocarbon perseveration of maturity ranges in reservoirs, particularly for the unconventional tight formation, and benefits potential hydrocarbon exploration from highly mature sediments.

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 score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.196
Teacher spread0.189 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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