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Record W2144656689 · doi:10.1306/01270605130

The controls on the composition of biodegraded oils in the deep subsurface: Part II—Geological controls on subsurface biodegradation fluxes and constraints on reservoir-fluid property prediction

2006· article· en· W2144656689 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAAPG Bulletin · 2006
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsGeological Survey of CanadaAlberta EnergyUniversity of Calgary
Fundersnot available
KeywordsGeologyBiodegradationPetroleum engineeringGeochemistryPetrologyMining engineering

Abstract

fetched live from OpenAlex

Abstract The principal controls on the fluid properties of biodegraded oil systems have been determined by a combination of petroleum geochemistry, numerical modeling of oil biodegradation in reservoirs, and analysis of oil property data sets from a variety of geological settings. Petroleum biodegradation proceeds under anaerobic conditions in any reservoir that has a water leg and has not been heated to temperatures more than 80°C. In most reservoirs with low concentrations of aqueous sulfate, methanogenic degradation is a primary mechanism of petroleum degradation, whereas in waters containing abundant sulfate, sulfate reduction and sulfide production may dominate. Net degradation of petroleum fractions in reservoirs is primarily controlled by the reservoir temperature, the chemical compounds being degraded, and relationships between the oil-water contact (OWC) area and oil volume. The relative volumes of water leg to oil leg, prior level of oil biodegradation, and reservoir water salinity act as second-order controls on the process. Typically, degradation fluxes (kilograms of petroleum destroyed per square meter of oil-water contact area per year or kg petroleum m−2 OWC yr−1) for fresh petroleum in clastic reservoirs are in the range of 10−3–10−4 kg petroleum m−2 OWC yr−1 and increase with decreasing reservoir temperature, from zero near 80°C, to a maximum flux at the OWC of less than 10−3 kg petroleum m−2 OWC yr−1 at a temperature less than 40°C. At very low reservoir temperatures and with severely degraded oils, such as are seen in the near-surface Canadian tar sands at the present day, the net degradation fluxes are much less than maximum values. Nutrient supply from the aquifer and adjacent shales, mostly buffered by mineral dissolution, probably provides the ultimate control on the range of degradation flux values. Oil compositional gradients and resulting oil viscosity variations are common on both reservoir thickness and field scales in biodegraded oil reservoirs and are a defining characteristic of heavy oil fields produced by crude-oil biodegradation. Continuous vertical gradients in the oil columns document episodic degradation for many millions of years, suggesting that the time scales of oil-field degradation and petroleum charging are similar. The flux-temperature relationship we have derived, coupled with typical reservoir charge histories, defines the range of variation of fluid properties seen in many biodegraded oil provinces and identifies oil charge, mixing of biodegraded and fresh oils, and reservoir-temperature history as the primary controls on fluid properties. These flux-temperature relationships are easily integrated into prospect charge modeling procedures; sensitivity analyses show that the limiting factor in fluid property predictions, using even this first-level approach, are ultimately constrained by the accuracy of current oil-charge modeling estimates. The absence today of any functional geochemical proxies for assessing oil-residence time in oil fields and the substantial uncertainty in petroleum-charging times estimated by forward basin modeling is a major obstacle to more accurate fluid-property predictions that needs to be addressed.

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.

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 categoriesnone
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 score0.052
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.203
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