Decision support system to evaluate a vandalized and deteriorated oil pipeline transportation system using artificial intelligence techniques. Part 2: analysis of the operational and economic risk

The changing supply and demand of hydrocarbons in recent years, generated by inflation, pandemics, and wars, have impacted its price considerably, developing limitations in maintenance processes in the oil industry worldwide; however, the mechanical deterioration of facilities due to corrosion does not stop. This article contributes original to the knowledge and management of a pipeline transportation system (PTS) without an immediate high impact that would help reduce property loss due to corrosion through the development of intelligent evaluation models that combine field data, laboratory, and cognitive knowledge in a case study in Mexico. The research is divided into Part 1 (Modeling; https://doi.org/10.1515/corrrev-2021-0080) and Part 2 (Operational and economic risk analysis of PTS under corrosive effects, using Monte Carlo simulation, MCS), supported by information and knowledge of 564 km of soils, from cathodic protection studies, essential to determine corrosive profiles of the PTS, considering supply and demand effects, with 1095 data on the price of the Mexican mixture from 2016 to 2019, as well as data monthly inflation rates for the same period, to generate financial estimates representative of the system, in search of replicable exchange actions and practices in international fields.