| dc.description.abstract | Permanent plug and abandonment (PP&A) is a necessary task that few oil and gas companies look forward to. All offshore operations are costly, and PP&A is no exception, it also does not provide any income after it is done therefore operators seek to do it as cost-effective as possible. To streamline the PP&A work, a reliable and probabilistic time-planning tool provides the best estimates. In this thesis a time-planning tool based on historical data and Monte Carlo simulations is presented.
The PP&A operation is divided in main operational steps to establish a data regime consisting of time used per step for 11 wells. The data was analyzed and found to match with a Weibull distribution, then additional statistics was added by simulating 200 more wells with Monte Carlo simulations based on Weibull parameters from the 11 historical wells. Based on the Monte Carlo simulation P10, P50, and P90 percentiles for estimated time necessary to perform each of the four main steps of the PP&A operation is presented.
The time-planning tool presented in the thesis was found to be more reliable and accurate than the existing time-planning method the cooperating operator company used for the data analyzed. By comparing these two with the actual time spent for each main step, the mean value from the Monte Carlo time-planning tool was found to be closest to the actual time spent for each step.
The time-planning tool presented in this thesis may easily be modified for time-planning other operations, such as running completion, drilling, running/retrieving marine riser etc. This thesis has shown that it is important to include a probabilistic approach in the time-planning phase. | |