Geolabe develops AI algorithms for the automated detection of methane emissions from satellite imagery, achieving a false positive rate of less than 0.03% and pinpointing leaks as small as 50 kg/h. Their system provides near-real-time monitoring of methane emissions globally, addressing the need for accurate emissions tracking in oil and gas operations.
Funding
$100K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Current methods for monitoring methane emissions rely on manual inspections or infrequent aerial surveys, which are costly, time-consuming, and lack the spatial and temporal resolution needed for effective leak detection and mitigation. This makes it difficult for oil and gas operators to quickly identify and address methane leaks, contributing to greenhouse gas emissions and regulatory compliance challenges.
Solution
Geolabe offers an AI-powered methane monitoring system that automates the detection of methane emissions from satellite imagery. Their algorithms analyze data from NASA and ESA satellites to pinpoint methane leaks with a low false positive rate (less than 0.03%), enabling near-real-time monitoring of emissions globally. The system can detect leaks as small as 50 kg/h, providing accurate and timely information to oil and gas operators for leak detection and mitigation. Users can access near-real time methane detections over any number of areas of interest, anywhere on Earth, or get historical reports analyzing data from 2015 to today.
Target Audience
The primary customers are oil and gas companies, environmental agencies, and regulatory bodies that require accurate and timely monitoring of methane emissions for leak detection, regulatory compliance, and emissions reduction efforts.
Features
- Automated methane detection using AI algorithms applied to satellite imagery
- High accuracy with a false positive rate of less than 0.03%
- Ability to detect small leaks (down to 50 kg/h)
- Near-real-time monitoring of methane emissions globally
- Historical data analysis from 2015 to present
- 20m pixel resolution
- 4 days median revisit time