Experimental acoustic emission (AE) signals collected at a 3MHz sampling frequency during CO2 leakage from a storage cylinder. Data was gathered under different pressures, such as 5MPa with a 20 kg/h leakage rate, by the British Geological Survey as part of a 2020 UKCCSRC project.
Use Cases
- Train a classifier to detect CO2 leakage events using 3MHz acoustic emission signal patterns.
- Analyze the relationship between AE signal characteristics and specific pressure conditions like 5MPa.
- Build a regression model to predict leakage rates (e.g., 20 kg/h) from acoustic emission sensor data.
- Develop anomaly detection algorithms for CO2 storage monitoring using high-frequency AE signals.
Strengths
- High-resolution data captured at a 3MHz sampling frequency.
- Experimental conditions are clearly defined (e.g., pressure at 5MPa, leakage rate at 20 kg/h).
- Data originates from a authoritative organization, the British Geological Survey.
Limitations
- Unknown sample size and dataset scale.
- Limited to controlled experimental conditions, not field data from operational sites.
- Data format and structure are unspecified, requiring investigation before use.
Provenance
- Source
- British Geological Survey (BGS)
- Collection Method
- Experimental collection of acoustic emission signals from three sensors during controlled CO2 leakage.
- Time Range
- Project funded in 2020.
- Freshness
- Last updated in March 2026.
- Geography
- null