Highlights of the 2009 SEG Summer Research Workshop on CO2 Sequestration
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 0.014 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".