02. Logistics and Supply Chain Management
The growing oil production in Brazilian waters makes the logistic management of offloadings from the platforms increasingly important. The platform offloading schedule must be carried out in advance, avoiding production stoppage due to lack of available storage space. An interruption in oil production, however small, causes a direct revenue loss for the producing company. Offloadings performed very close to the platform TOP represent an imminent risk of production loss and are called critical offloadings. This work aims to carry out a statistical study with historical data from 2016 to 2019 to create a multivariate model for forecasting critical offloadings in a large Brazilian oil company. The dynamic regression model was used to evaluate how the variables present in the offloading scheduling process are related to the monthly percentage of critical offloadings. From the developed model, it was identified that the variables of monthly production, average stock, weather forecast, average batch and monthly exports impact the percentage of critical offloadings. A sensitivity analysis was carried out, from which it was possible to conclude that the company's inventory management is the fundamental factor for the reduction of critical offloadings and, consequently, the reduction of the chances of production loss.
PALAVRAS-CHAVE: offloading; modeling; dynamic regression; oil logistics; offloading schedule.