In a few years there will be a need for performing a considerable number of subsea plug and abandonment (P&A) on the Norwegian Continental Shelf (NCS). There are certain challenges associated with that such as more difficult access to subsea wells compared to ordinary platform wells, high daily rates of semi-submersible rigs and the fact that these rigs will be allocated for drilling new exploration and production wells to sustain the hydrocarbon production. For the moment there is large focus on looking for rigless technologies to decrease P&A cost and use of rig time. A probabilistic approach should be used to assess the cost and duration saving potential of such technologies relative to semi-submersible rigs.

In this paper, we will consider rigless technologies for performing parts of the P&A operation. For the first time, a risk based probabilistic approach including learning curves, correlations and possible risk events is used to evaluate subsea batch operated P&A.

A realistic example case which includes the use of a semi-submersible rig for batch operated P&A of subsea production wells is used to show how a probabilistic methodology can be implemented for obtaining probabilistic estimates of P&A cost and duration. Inclusion of learning curves and correlations makes the application of a probabilistic approach for multi-well campaigns challenging. It is demonstrated how to incorporate learning curves, correlations and possible risk events to capture a realistic range of cost and duration for multi-well P&A. In a second operational example, a light well intervention vessel is employed to accomplish preparatory work as well as wellhead cutting and removal for P&A of the subsea production wells in batch campaigns. These two case studies will be compared from a cost and duration point of view and it is shown that there are significant cost and duration savings related to transferring P&A activities from rigs to alternative intervention and vessel technologies.

You can access this article if you purchase or spend a download.