Borehole EM Monitoring at Aquistore: Final Report to the Carbon Capture Project (CCP)
Bibliographic record
Abstract
Geologic carbon sequestration (GCS) is a technology whose goal is to prevent atmospheric release of greenhouse gases via injection of carbon dioxide (CO2) into an underground reservoir for long term storage. GCS is typically part of a program of carbon capture and storage (CCS) that captures CO2 from point sources such as power plants, transports the CO2 to a storage site, and operates an injection facility. One recent CCS pilot project is the Aquistore CO2 sequestration project, near Estevan, Saskatchewan, Canada. The Aquistore project is managed by the Petroleum Technology Research Centre (PTRC) and will be one of the first integrated CCS projects storing CO2 in a deep saline aquifer from a coal fired power plant (PTRC, 2011). Aquistore is expected to store 500,000 tons of CO2 during its lifetime (Ministry of Environment, 2012). Assuring the long-term, safe storage of CO2 requires the development of effective monitoring strategies. As part of the geophysical monitoring effort at Aquistore, there were initial plans for deployment of borehole electrodes for electrical or electromagnetic measurements to monitor CO2 within the reservoir. The injected CO2 displaces saline brine in the reservoir, and because CO2 has a high resistivity compared to brine, the overall resistivity of the formation increases and can be monitored by measuring electric or magnetic fields. Previous work by Lawrence Berkeley National Laboratory (LBNL) had indicated that borehole-to-surface electromagnetic monitoring, using an electric dipole source near the bottom of a well penetrating the reservoir, could detect the resistivity change induced by GCS. To assess the potential application of electromagnetic monitoring at Aquistore, Lawrence Berkeley National Laboratory and Multi-Phase Technologies collaborated on a two-part study including (1) numerical forward modeling of a time-lapse, controlled-source electromagnetic (CSEM) monitoring survey, and (2) an initial engineering study of instrumentation and proposed design for a borehole electric dipole source and electrode sensors.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".