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Record W3197980548 · doi:10.3390/geosciences11090365

δ13C and δD Values of n-Alkanes from In-Reservoir Biodegraded Oils: Implications for Understanding the Mechanisms of Biodegradation and for Petroleum Exploration

2021· article· en· W3197980548 on OpenAlexaff
Nikolai Pedentchouk, Barry Bennett, Steve Larter

Bibliographic record

VenueGeosciences · 2021
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsSchlumberger (Canada)University of Calgary
Fundersnot available
KeywordsBiodegradationδ13CEnvironmental chemistryPetroleumAlkaneChemistryHydrocarbonIsotopes of carbonStable isotope ratioOil sandsGeologyOrganic chemistryTotal organic carbonMaterials science

Abstract

fetched live from OpenAlex

This study investigates the magnitude and direction of stable C and H isotope shifts of n-C15–30 alkanes from biodegraded oils sourced from Type II (Oil suite S) and Type II/III (Oil suite H) kerogens. Compound-specific isotope data show a 2.0‰ 13C-enrichment and no D-enrichment of n-alkanes in the most biodegraded oil from sample suite S. Similarly, there is a 1.5–2.5‰ 13C-enrichment and no D-enrichment in Oil suite H. Overall, there is a <2.5‰ δ13C and <20‰ δD variability among individual n-alkanes in the whole sequence of biodegradation. N-alkanes from the least biodegraded Oil H samples are 2–4‰ 13C-enriched in comparison with the least biodegraded Oil S. However, there are no differences in the δD values of n-alkanes in these samples. Our indirect isotopic evidence suggests (1) a site-specific biodegradation process, most likely at position C-2 and/or C-3 or another site-specific process, and (2) a significant D/H exchange between organic compounds in the source rock and isotopically similar marine formation waters. We conclude that, unlike δD methodology, investigation of δ13C composition of n-alkanes has strong potential as a supplementary tool for oil–oil and oil–source-rock correlation even in biodegraded oils when n-alkanes are present.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.695
Threshold uncertainty score0.206

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)0.0000.000

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 head0.071
GPT teacher head0.279
Teacher spread0.208 · 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.

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

Citations6
Published2021
Admission routes1
Has abstractyes

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