A major challenge faced by the asset management team of operator is the inventory management of its wells. The well count and number of wells in different states and in different assets is difficult to account for. The asset management team faces challenges in tracking the status of wells, due to the large well count and wide variety of states of wells. Therefore, operators need data analytics enabled analysis of oil and gas wells inventory which gives them insights into the well states and makes recommendations related to inventory management at a central facility. The wells data generated by asset teams is shared with central office. The operators want to run data analytics and machine learning tool to get a quick insight into the trends of states of the well. Machine learning enabled predictive models to make forecast and recommendation on wells expected to change their states with time.