Hyperspectral Sensor for Large-Area Monitoring of Carbon-Dioxide Reservoirs and Pipelines

Geologic carbon sequestration has the potential to store a century¿s worth of anthropogenic carbon dioxide production. However, this solution will require numerous large underground reservoirs that may extend over hundreds of square kilometers and an extensive network of pipelines, some of which will be on the order of hundreds of kilometers long. Consequently, very large areas will need to be monitored to identify any leakage that may occur in either the reservoirs or the pipelines. The purpose of this project is to develop a low-cost CO2 leak detection system suitable for large-area, high-resolution, full-coverage monitoring. Previous work has shown that plants exposed to low-level underground releases of CO2 exhibit measurable changes in reflectance. Thus, vegetation over potential leakage sites could be utilized as a massive sensor array if one could 1 effectively monitor underground CO2-induced changes in plant reflectance, and 2 differentiate CO2 plant response from other factors such as drought and soil type that also affect plant reflectance. This project will develop such a sensor based on a spectral imaging system. Measurements taken during planned controlled CO2 release experiments from an underground pipeline will be used to determine the important spatial resolution requirement of the sensor. Additional work will be devoted to identifying techniques to differentiate CO2 induced plant response from other factors. Results from these studies will be used to design an optimal sensor system. Commercial Applications and other Benefits as described by the awardee: In addition to the monitoring of CO2 reservoirs and pipelines, the technology should be useful for monitoring other types of pipeline gases, such as methane. Additionally, the technology may be useful for agricultural applications