The number of wells to be abandoned on the Norwegian Continental Shelf will increase in
the forthcoming years. As a consequence, significant expenditures will be required paid by
the individual companies, the state and the society. Despite many technological advances
in the oil and gas industry the recent years, traditional P&A of platform wells is still
particularly performed by using expensive drilling rigs. In an industry characterized by
time-consuming, costly, and complex operations, it is especially interesting to investigate
the technological potential of P&A and possible cost-savings this may entail. This thesis
therefore considers rigless P&A of platform wells, where the use of well intervention
equipment is presented as an alternative approach to traditional rig-based P&A.
Three different case studies of P&A are explored and presented: a rig-based approach,
a rigless approach, as well as a combination of rig-based and rigless approach. Well
intervention equipment such as wireline and a hydraulic jacking unit are involved in the
emerging, rigless method. In order to suggest the most appropriate and cost-efficient
abandonment approach, three models are built and used in a Monte Carlo simulation to
forecast cost and duration of the different P&A operations. By using well intervention
equipment, risk and uncertainties related to unpredictability in the rig marked is removed,
which simplifies the time and cost forecasting. To achieve accurate estimation of cost and
duration, data is collected with awareness. Historical data, particularly from Aker BP,
as well as expert opinions and knowledge, are thus used as simulation input to produce
realistic forecasts. The simulation output of the different models is compared, discussed
and evaluated using the percentile output values. Findings from the case studies identifies
that rigless P&A is much more time-consuming than rig-based P&A. However, partly
reducing and completely removing the rig scope leads to significant cost-savings. Since
the chosen simulation models consider P&A of a single well, this opens an opportunity for
further research within time and cost simulation for multiple wells on platforms.