M. Doshi
Schlumberger-Doll Research Center,
United States
Keywords: methane sensors, greenhouse gas, emissions reduction, sustainability
Summary:
Methane emissions from oil and gas facilities show extreme spatial and temporal variability. Continuous methane monitoring systems are essential to accurately quantify such variable emissions in a cost-effective manner. We have developed an IoT-enabled continuous methane monitoring system, named methane point instrument, which can be deployed along the perimeter of a facility to detect emissions in real time. We have also developed complementary planning algorithms that optimize the sensor placement and inversion algorithms that detect, quantify, and localize emissions. Our sensors collect real time meteorological data with their in-built anemometers and implement an adapted Gaussian Plume Model for methane dispersion to relate the methane concentrations measured by the sensors with the emission location, duration, and rate. We then combine the discrete sensor measurements using physics-based emissions lifecycle logic to create actionable emission events that show the spatial and temporal variations in emissions. Last year, we tested our methane point instrument system’s performance at a three month long blind test conducted by Colorado State University at METEC (methane emissions technology evaluation center), the premier testing facility for methane monitoring technologies. The test results show that our point instrument outperformed all point sensors ever tested at METEC and met US EPA’s requirement for the smallest limit of detection for continuous methane monitors. Measurements from sensing systems typically have two types of measurement errors: random and systematic. Random errors are fluctuations in measurements (a combination of underestimation and overestimation) that depend on the precision of the technology. As more measurements are collected, these random errors go away. Systematic errors, on the other hand, are directionally constant (i.e. always underestimation or always overestimation) and do not go away as more measurements are collected. For continuous monitoring systems that take thousands of measurements each year, systematic errors can have major implications on the accuracy of the total emissions estimated from a facility, while random errors mostly cancel out and are less significant. During our METEC tests, for the 400+ releases performed by METEC, our methane point instrument showed the smallest systematic error of 4% among all tested technologies proving the robustness and accuracy of our sensors at quantifying emissions from realistic oil and gas facilities