Intense precipitation events in Rio de Janeiro are linked to the occurrence of vast infrastructure and economic damages along oil pipelines. However, a comprehensive characterization of extreme precipitation events over the region is still lacking. Particularly, the main atmospheric mechanisms associated with those events are still poorly understood and so are the impacts on oil pipeline sectors. The work aims to fill this gap, identifying these extreme precipitation events. To this end, we use a remote sensing multi-satellite dataset from the Global Precipitation Measurement (GPM) mission for the last 20 yr along the ORBIG pipeline; the pipeline is primarily responsible for supplying oil to the Rio de Janeiro Petrochemical Complex, with an annual handling capacity of 32011200 m3 yr-1. First, we evaluated the usability of GPM precipitation estimates in the study region. Then, we applied a statistical ranking method aiming to classify extreme precipitation events over the study region. Here, we classified an extreme precipitation event by considering the total affected area and its intensity, based on the daily standardized precipitation anomaly computed for the 2000-2019 period and taking into account different time scales, from 1 to 5 d, allowing the classification of different periods of anomalous precipitation. Results show that most events were associated with the South Atlantic Convergence Zone, followed by cold fronts and low-pressure systems capable of generating transports of humidity and atmospheric instability. The majority of extreme cases took place during summer, and the most significant incidence occurred in the late afternoon. These results provide guidelines for designing crucial mitigation and prevention practices along the ORBIG pipeline.