Cost-conscious developers of any new ASR project may be reluctant to invest time and cost to undertake investigations to determine whether the level of treatment intended for the source water will be adequate to prevent irreversible clogging in the injection well. So a Bayesian approach was developed to determine the benefit cost ratio of undertaking such investigations before undertaking them, using assumed reliability of investigations. This gives transparent outcomes based on the views held by decision makers.
At three Australian ASR sites, two stormwater and one treated sewage effluent, the projected confidence of a successful outcome for a given water type was qualitatively defined based on experiences at each phase of project investigations. A Bayesian analysis of laboratory column clogging studies was undertaken and embedded in an analysis of expected benefits and costs. Furthermore, the effect of clogging on operational costs including reduced volumes recharged and well rehabilitation for accute and chronic clogging were defined using analytical equations.
Benefit-cost ratios were determined for a set of assumed experimental reliabilities (10% false positives and 20% false negatives) for an applied example project. The results showed that if the results of the clogging investigations were used to make water treatment decisions, expected benefits significantly exceeded costs regardless of whether the clogging investigation predicted clogging or no clogging. .
Although this Bayesian approach is based on assumed experimental reliability, it does show how clogging investigations can be highly valued in establishing viable projects and in avoiding losses, and lead to more confident decisions. This work has been documented in Dillon et al (2016) but has not yet been presented at an Australian conference.