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Record W2132348977

Relevance of underground natural gas storage to geologic sequestration of carbon dioxide

2002· article· en· W2132348977 on OpenAlexfundno aff
M.J. Lippmann, Sally M. Benson

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
FundersSuncor Energy IncorporatedU.S. Department of Energy
KeywordsNatural gasGreenhouse gasEnvironmental scienceCarbon sequestrationCarbon dioxideMethaneAquiferFossil fuelGroundwaterPetroleum engineeringWaste managementGeologyChemistryEngineeringGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

The practice of underground natural gas storage (UNGS), which started in the USA in 1916, provides useful insight into the geologic sequestration of carbon dioxide--the dominant anthropogenic greenhouse gas released into the atmosphere. In many ways, UNGS is directly relevant to geologic CO{sub 2} storage because, like CO{sub 2}, natural gas (essentially methane) is less dense than water. Consequently, it will tend to rise to the top of any subsurface storage structure located below the groundwater table. By the end of 2001 in the USA, about 142 million metric tons of natural gas were stored underground in depleted oil and gas reservoirs and brine aquifers. Based on their performance, UNGS projects have shown that there is a safe and effective way of storing large volumes of gases in the subsurface. In the small number of cases where failures did occur (i.e., leakage of the stored gas into neighboring permeable layers), they were mainly related to improper well design, construction, maintenance, and/or incorrect project operation. In spite of differences in the chemical and physical properties of the gases, the risk-assessment, risk-management, and risk-mitigation issues relevant to UNGS projects are also pertinent to geologic CO{sub 2} sequestration.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
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
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.011
GPT teacher head0.172
Teacher spread0.161 · 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 designObservational
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

Citations11
Published2002
Admission routes1
Has abstractyes

Explore more

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