MétaCan
Menu
Back to cohort

A review of physical, chemical, and hydrogeologic characteristics of stray gas migration: Implications for investigation and remediation

2021· review· en· W3133957995 on OpenAlexaff
Lisa J. Molofsky, John A. Connor, Cole J.C. Van De Ven, Mark P. Hemingway, Stephen D. Richardson, Brian A. Strasert, Travis M. McGuire, Shawn M. Paquette

Bibliographic record

VenueThe Science of The Total Environment · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of British Columbia
FundersGSI Environmental
KeywordsEnvironmental remediationEnvironmental scienceHydrogeologyNatural gasUnconventional oilGroundwaterPetroleumFossil fuelPetroleum engineeringContaminationEnvironmental engineeringWaste managementGeologyEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Releases of natural gas into groundwater from oil and gas exploration, production, or storage (i.e., "stray gas") can pose a risk to groundwater users and landowners in the form of a fire or explosive hazard. The acute nature of stray gas risk differs from the long-term health risks posed by the ingestion or inhalation of other petroleum hydrocarbons (e.g., benzene). Stray gas also exhibits different fate and transport behaviors in the environment from other hydrocarbon contaminants, including the potential for rapid and extensive transport of free-phase gas through preferential pathways, and the resulting variable and discontinuous spatial distribution of free and dissolved gas phases. While there is extensive guidance on response actions for releases of other hydrocarbons such as benzene, there are relatively few examples available in the technical literature that discuss appropriate response measures for the investigation and remediation of stray gas impacts. This paper describes key considerations in the physical, chemical, and hydrogeological characteristics of stray gas releases and implications for the improved investigation and mitigation of associated risks.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.925
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.019
GPT teacher head0.252
Teacher spread0.232 · 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 designOther design
Domainnot available
GenreReview

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

Citations48
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueThe Science of The Total EnvironmentSame topicAtmospheric and Environmental Gas DynamicsFrench-language works237,207