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Record W2262210297 · doi:10.1144/0060633

Biodegradation, gas destruction and methane generation in deep subsurface petroleum reservoirs: an overview

2005· article· en· W2262210297 on OpenAlexaff
Steve Larter, Ian M. Head, Haiping Huang, Barry Bennett, Martin Jones, Andrew C. Aplin, Andrew Murray, M. Erdmann, A. Wilhelms, Rolando di Primio

Bibliographic record

VenueGeological Society London Petroleum Geology Conference series · 2005
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiodegradationMethanePetroleumPetroleum engineeringEnvironmental scienceWaste managementEnvironmental chemistryGeologyChemistryEngineering

Abstract

fetched live from OpenAlex

Plate tectonics forms and destroys sedimentary basins, accumulating organic carbon and converting it into mobile petroleum which may be concentrated in reservoir traps in which, if temperatures are below 80°C, it may become biologically degraded (biodegraded). The biodegradation process produces altered, denser, heavy oils and methane as a primary product. Much of the world’s oil is biodegraded under anaerobic conditions, with methane being a major by-product of the action of the deep biosphere on petroleum when sulphate is not present as an oxidant. A review of the literature relating to destruction of wet gas and the systematics of methane generation during subsurface oil biodegradation concludes that large biodegrading oil fields may be major source systems of dry gas.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.252
Teacher spread0.218 · 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 designSimulation or modeling
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

Citations70
Published2005
Admission routes1
Has abstractyes

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