AI for Carbon Capture, Utilization & Storage MRV |…

AI for Carbon Capture, Utilization & Storage MRV

Measure, report, and verify CO₂ capture, transport, utilization, and storage with AI-driven quantification, leak detection, and assurance.

CCUS projects require auditable MRV to prove climate impact. AI fuses process, geospatial, and sensing data to quantify captured/stored CO₂, detect leaks, and produce verification-ready evidence.

Satellite/EO detection for surface anomalies

Verification & Reporting: Automated MRV reports with uncertainty and evidence.

Utilizing satellite imagery and Earth observation (EO) data allows for the identification of surface anomalies associated with potential CO₂ leaks, providing crucial verification information.

live demo · related simulation● LIVE

SCADA/DCS from capture and pipelines; lab data for calibration

Geophysical and EO feeds; spatial indexing by wells/reservoir.

Integrating Supervisory Control and Data Acquisition (SCADA) systems from capture facilities and pipelines alongside laboratory data enables precise calibration and validation of AI models.

Frequently asked questions

What is the role of MRV in CCUS projects?

Measurement, Reporting, and Verification (MRV) is essential for CCUS projects to demonstrate their effectiveness in reducing carbon emissions and achieving climate goals. It provides verifiable evidence of captured or stored CO₂.

How does AI enhance MRV processes?

AI algorithms analyze vast datasets from various sources – including process data, geospatial information, and sensor readings – to provide more accurate and reliable quantification of carbon capture activities and detect potential leaks with greater speed and precision.

What types of data are used in AI-powered MRV systems?

AI-powered MRV systems utilize a combination of process data from capture facilities, geospatial information like satellite imagery and well locations, and sensor readings to create a comprehensive understanding of the CCUS project’s performance.

How does this approach improve verification accuracy?

By combining multiple data streams and applying sophisticated analytical techniques, AI significantly reduces uncertainty in MRV reporting, providing verifiers with greater confidence in the accuracy of carbon capture claims.

▶ Try it live

Everything above runs in your browser — open Hash Function Avalanche Visualizer and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Hash Function Avalanche Visualizer simulation