Automated High Power Permanent Borehole Seismic Source Systems for Long-Term Monitoring of Subsurface CO2 Containment and Storage
Bibliographic record
Abstract
The geologic storage of CO2 emitted from fixed sources, such as coal or gas power plants, is currently considered one of the prime technologies for short term (~50 year) mitigation of greenhouse gas emissions. The subsurface storage of CO2 for greenhouse gas mitigation will require monitoring to verify that CO2 remains effectively trapped underground, thus permanent seismic sources are needed to provide 24/7 monitoring. GPUSA Inc. has developed and successfully demonstrated numerous prototype vibratory seismic sources with power and performance far beyond any available on the market. The primary objective of this project was to validate in an operational field environment GPUSA’s powerful, low cost, automated borehole seismic source systems for the CO2 storage monitoring application. GPUSA originally proposed the building and testing of two types of permanent sources but ended up building and delivering three types of permanent seismic sources. These sources were delivered to the field test site (Carbon Management Canada’s Containment and Monitoring site near Calgary), however, only two of the systems were able to be tested before the contract ended (despite two contract extensions). The reasons for the delay were primarily weather related both at the US preliminary field test site and Carbon Management Canada site. But in the end, based upon the preliminary field testing in the US and the limited testing that was completed at the Carbon Management Canada site, the results were very impressive, and in some cases far exceeding expectations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".