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Record W1489942136 · doi:10.1190/tle29020138.1

Highlights of the 2009 SEG Summer Research Workshop on CO2 Sequestration

2010· article· en· W1489942136 on OpenAlexafffundabout
David Lumley, Don Sherlock, T. M. Daley, Lianjie Huang, Don C. Lawton, R. M. Masters, M. Verliac, Don White

Bibliographic record

VenueThe Leading Edge · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsGeological Survey of CanadaUniversity of Calgary
FundersPetroleum Technology Research CentreU.S. Department of Energy
KeywordsLibrary scienceGovernment (linguistics)Presentation (obstetrics)Political sciencePanel discussionEngineeringOperations researchManagementComputer scienceBusinessAdvertising

Abstract

fetched live from OpenAlex

The 2009 SEG Summer Research Workshop on “CO2 Sequestration Geophysics” was held 23–27 August 2009 in Banff, Canada. The event was attended by over 100 scientists from around the world, which proved to be a remarkably successful turnout in the midst of the current global financial crisis and severe corporate travel restrictions. Attendees included SEG President Larry Lines (University of Calgary) and CSEG President John Downton (CGG Veritas), who joined SRW Chairman David Lumley in giving the opening welcome remarks at the Sunday Icebreaker. The workshop was organized by a committee of technical experts representing a good mix of industry, academic, and government research organizations (see box). The format consisted of four days of technical sessions with over 60 talks and posters, plus an optional preworkshop field trip to the Columbia Ice Fields to view firsthand the effects of global warming on the Athabasca glacier (Figures 1–2). Group technical discussion was encouraged by requiring each presenter to limit themselves to 15 minutes of presentation followed by a 15–minute open discussion period. Technical contributions focused on the current and future role of geophysics in CO2 sequestration, highlighting new research and field-test results with regard to site selection and characterization, monitoring and surveillance, using a wide variety of geophysical techniques. While there are too many excellent contributions to mention all individually here, in this paper, we summarize some of the key workshop highlights in order to propagate new developments to the SEG community at large.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.999

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.082
GPT teacher head0.363
Teacher spread0.281 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations9
Published2010
Admission routes3
Has abstractyes

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