GRTgaz owns and operates the longest high-pressure natural gas transmission network in Europe. The industrial assets of GRTgaz include more than 32,000 km of pipes, 26 compression stations, about 4,800 shut‐off stations and more than 5,000 pressure reduction stations (notably for delivering public distributions and industrial consumers). In particular, the pressure reductions stations can have one two lines, each line having one or two pressure regulators, plus safety devices (shutdown valves and‐or safety relief valves), and other items (filters, manual valves, gas meters…). In addition, each type of device exists in different models (technology, manufacturer, sizes, parameters…) so that there are probably no two stations that can be assumed alike. Since GRTgaz must transport natural gas on behalf of all its customers while ensuring optimum safety, cost and reliability, risk assessments need to be performed for thousands of these stations. To perform efficiently the safety and reliability assessment of all gas pressure reduction stations, a process has been developed for automatically generating and analyzing fault trees. Two undesired events are considered per station: pressure too low (including loss of gas furniture) and pressure too high. The fault trees aim at modelling these events considering the proper architecture of each station and the characteristics of its devices. The inputs data are: the list of all stations with their architecture and the references of their devices; the list of all devices with their characteristics, including ages; the list of all failures observed over the last 15 years; and the maintenance policy. These data allow to estimate reliability parameters, using Weibull distributions, for required failure modes of each device according to its characteristics (from 3 to 5, depending on the type of device). Previous developments were dedicated to making available all these inputs within a digital platform for data visualization. Inputs data are then exported to Excel files where further developments have been performed in Visual Basic for Applications. First, fault trees are generated for each station according to its architecture, by creating a “.dag” file (readable by several fault tree software tools) per undesired event and per station. The basic events are parametrized by the Weibull parameters defined for the corresponding devices, the ages of the devices, and the periods of preventive maintenance that allow detecting the failure modes. Then, a specific development has been done within a commercial fault tree analysis tool in order to launch at a time any number of fault trees (“.dag” files) – for which access paths are given in a single “.txt” file – with given calculation parameters (e.g. the average frequency of undesired events over the 5 next years). Then, results are compiled within a “.csv” file, with one line per analyzed fault tree and requested results in columns. The resulting risk assessments are now used for identifying the most critical stations in terms of safety and availability, optimizing periods of preventive maintenance, and prioritizing investments in terms of asset renovation.