Abstract

Oil spills and its attendant effects on the ecosystem is a common theme that is associated with crude oil exploration which in turn constitute a threat to public health and life. A model which provides a breakdown of oil spills occurrences based on the magnitude of spills; taking into consideration the varying length of times on each state before transition would provide a wealth of resource for better understanding of the scenario for effective management. This study presents a Homogeneous Semi-Markov process with a Weibull waiting time distribution for the analysis crude oil spills. The states of the Semi-Markov process were classified as minor (volume of spills 250 barrels) spills. Further, the consistency property of the Semi-Markov kernels was investigated. The approach was illustrated using data from the National Oil Spill Detection and Response Agency (NOSDRA), Nigeria and with particular consideration of the oil exploration by CHEVRON Nigeria Limited and Nigeria Agip Oil Company (NAOC) from January, 2006 to March, 2020. The stationary distribution of the Semi Markov process for NAOC was obtained to be Minor = 0.6954, Medium = 0.2461, Major = 0.0585 with mean waiting times before transition of 2.5438, 2.7429 and 3.6204 respectively. The stationary distribution of the Semi Markov process for CHEVRON was found to be Minor = 0.9373, Medium = 0.0393, Major = 0.0234 with mean waiting times of 6.4609, 6.0408 and 8.7861 respectively. Further result shows that oil spill due to NAOC occurred at least once every 3 days while that of CHEVRON Nig. Ltd occurred at least once every 6 days. Results obtained indicate that the homogeneous Semi Markov model is well suited for effective description and prediction of oil spill occurrences.