Offshore pipelines play an important role in oil and gas industry where they transports crude oil in large quantity. However, the increasing age of the pipelines has raised concerns among pipeline operators throughout the world due to offshore pipelines are typically operated in deteriorative environment, hence affecting the pipeline integrity. The pipeline wall thickness loss due to internal corrosion is a major potential problem and it becomes worse as the pipeline aging. In order to overcome this problem, pipeline operators have practiced reliability-based corrosion management programs, consisting three components in managing their pipeline which are in-line inspection, pipeline reliability evaluation and pipeline repair. Two common approaches have been used to determine the pipeline reliability; deterministic and probabilistic methods. In this study, both methods are being explored using intelligent pigging data. The models were ASME B31G, degradation analysis and PF interval. Degradation analysis has been widely used in reliability analysis of piping systems; however, the application to offshore pipelines by using intelligent pigging data is rather limited. The results were compared to result generated from ASME B31.G which is normally being used by most pipeline operators. The result showed that the degradation analysis more conservative than ASME B31.G and P-F interval.