GNGTS 2018 - 37° Convegno Nazionale

GNGTS 2018 S essione 2.3 525 MULTI-HAZARD RISK ASSESSMENT FOR GEO-RESOURCE DEVELOPMENT PROJECTS A. Garcia-Aristizabal 1,3 , J. Kocot 2 , R. Russo 3 , P. Gasparini 3* 1 Istituto Nazionale di Geofisica e Vulcanologia, sezione di Bologna, Bologna, Italy 2 Academic Computer Centre Cyfronet, AGH University of Science and Technology, Krakow 3 Center for the Analysis and Monitoring of Environmental Risks, Naples, Italy * deceased Introduction. The exploration and exploitation of geo-resources (a term generally referred to any kind of geological resource) may impact the surrounding environment, and for this reason such industrial activities need to be carefully planned, including the implementation of reliable environmental risk assessments (ERA). A multi-hazard risk (MHR) analysis aims at providing a theoretical framework for harmonising the methodologies employed and the results obtained from risk assessments (i.e. likelihood and consequences) considering different risk sources and taking into account possible interactions among events (e.g. Marzocchi et al. , 2012; Gasparini and Garcia-Aristizabal, 2014; Liu et al. , 2015; Garcia-Aristizabal et al. , 2018). The MHR problem in this kind of applications needs to be defined in the interface between a natural/built/social environment and an industrial activity perturbing it. The probabilistic model for MHR assessment, as implemented by Garcia-Aristizabal et al. (2018), relies on three fundamental concepts: (1) a logical structure that follows a bow-tie approach, (2) a Bayesian implementation for handling probabilistic information, (3) propagation of modelling uncertainties, and (4) the possibility of using data derived form integrated assessment modelling and expert judgement elicitation for analysing complex processes for which direct data is unavailable. The analyses therefore rely on the quantification of the likelihood and related consequences of identified risk pathway scenarios structured using a bow-tie (BT) approach (e.g. Bedford and Cooke, 2001; Rausand and Høyland, 2004). The BT is widely used in reliability analysis and has been proposed for assessing risks in a number of geo-resource development applications, as for example in offshore oil and gas development (e.g. Khakzad et al. , 2013, 2014; Yang et al. , 2013) and for the mineral industry in general (e.g. Iannacchione, 2008). The BT analysis, in particular, provides an adequate structure to performdetailed assessments of the probability of occurrence of events or chains of events in a given accident scenario. An example of a typical BT structure for this kind of application is presented in Fig. 1. It is targeted to assess the causes and effects of specific critical events; it is composed of a fault tree (FT, Fig. 1a), which is set by identifying the possible events causing the critical or top event (TE, Fig. 1b), and an event tree (ET, Fig. 1c), which is set by identifying possible consequences associated with the occurrence of the defined TE (e.g. Rausand and Høyland, 2004). Therefore, in the BT structure, the top event of the FT constitutes the initiating event for an ET analysis. Methods and results. The quantitative assessment of the scenarios implemented in a BT structure is based on the probabilities assigned to the basic events of the FT and to the nodes of the ET. In this work, the BT logic structure is coupled with a wide range of probabilistic tools that are flexible enough to make it possible to consider in the analyses different typologies of phenomena. Given the different categories of risk receptors of interest, Garcia-Aristizabal et al (2018) suggest the following general criteria for structuring the MHR scenarios in a BT: 1. Impacts to primary risk receptors can be chosen as critical TEs for constructing fault trees. 2. Identification of the boundary conditions with respect to external stresses. In this way, we define the type of hazards that need to be included in the analysis. 3. For each TE identified, a deductive technique is used to identify the possible causes of such a critical event, considering the boundary conditions defined and the level of resolution of the analysis. 4. The identified TEs are also the starting points of consequence analysis, which can be