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Record W2548394865 · doi:10.1144/petgeo2016-070

Causes and mitigation strategies of surface hydrocarbon leaks at heavy-oil fields: examples from Alberta and California

2016· article· en· W2548394865 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.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePetroleum Geoscience · 2016
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
FundersCanadian Natural Resources LimitedUniversity of Texas at Austin
KeywordsTelmatologyEnvironmental geologyMetamorphic petrologyGeobiologyGeologyEconomic geologyIgneous petrologyRegional geologyEngineering geologyHydrocarbonHydrogeologyPalaeogeographyEarth sciencePetroleum engineeringSeismologyVolcanismGeotechnical engineeringTectonics

Abstract

fetched live from OpenAlex

Identification and mitigation of leaks of subsurface fluids such as hydrocarbons at many heavy-oil fields is a first-order concern to operating companies, their regulators and the public. A variety of leaks have been documented at heavy-oil fields in Alberta (Canada) and California (USA). Although the petroleum geology and tectonic framework of fields in these areas differ significantly, production-related uplift of overburden and dilation of pre-existing fractures due to cyclic steam injection are likely to have facilitated the leakage events. As a result, integration of overburden characterization and monitoring with management of steam pressures may provide an effective means of risk mitigation of major leakage events.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.999

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 head0.007
GPT teacher head0.197
Teacher spread0.190 · 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