Using Bayes Theorem to Quantify and Reduce Uncertainties when Monitoring Varying Marine Environments for Indications of a Leak

Monitoring the marine environment for leaks from geological storage projects is a challenge due to the variability of the environment and the extent of the area that migrating CO2 might seep through the seafloor. Due to the environmental risk associated leaks should not be allowed to continue undetected. There is also a cost issue since marine operations are expensive, so false alarms should be avoided. The main question is then: how large a deviation in the monitoring data should cause mobilization of confirmation and localization procedures? Here Baye's theorem and Bayesian decision theory is suggested as a tool for quantifying certainties and to implement costs for false positives (false alarms) and false negatives (undetected leaks) in the decision procedure. The procedure is exemplified using modeled natural CO2 content variability and the predicted CO2 signal from a simulated leak.