A risk-based containment monitoring framework for long term geological CO2 storage
Bibliographic record
Abstract
Shell Global Solutions, The Netherlands <br> <br> Carbon capture and storage (CCS) is a key climate mitigation technology available to meet the Paris Agreement goal for limiting global warning. The goal of CCS projects is to separate, capture and permanently store CO2, thereby reducing greenhouse gas emissions from existing industrial facilities. The main components of a CCS project are the capture infrastructure, the transport of the CO2 to the storage site and the injection of the CO2 deep underground. Site selection, characterization and engineering design are the prime means to ensure CO2 risks are as low as possible. In addition, Shell uses a risk-based measurement, monitoring and verification (MMV) framework to evaluate the storage performance by monitoring conformance and containment. Shell is currently involved in several CCS projects as a partner (Gorgon in Australia, Northern Lights in Norway) and as the operator for Quest, a commercial-scale facility in Alberta, Canada. At Quest, CO2 is captured from the Scotford oil sands upgrader and transported by pipeline to the storage site. Since 2015, more than 5 million tons of CO2 have been injected into a saline aquifer located at a depth of about 2 km below ground surface. A comprehensive MMV plan is in place and incorporates several monitoring techniques including microseismicity monitoring. Even though Quest is in a quiet tectonic area, induced seismicity is recognized as a potential risk in all large-scale fields undergoing injection. We will discuss how microseismic monitoring is an important element of the MMV plan to evaluate the induced seismicity risk and to possibly provide early notice of anomalies.
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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 | 0.001 |
| 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) | 0.005 | 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".