Integrated Probabilistic Modeling of Sea Ice, Metocean Conditions, and Vessel Operability for Estimating Weather Windows in Arctic Offshore Drilling

Abstract

Abstract. This article presents a probabilistic Monte Carlo simulation workflow that integrates sea ice dynamics, seastate conditions, and vessel operability to estimate weather windows for Arctic offshore drilling. The analysis also demonstrates how estimates of the weather window can be used to develop probabilistic cost and schedule estimates for drilling activities. Using 12 years of sea ice observations and 29 years of wave data for a Chukchi Sea drilling site, a first-order, time-inhomogeneous Markov chain is specified to estimate week-to-week site availability under open-water/sea-ice-free conditions (<10% ice concentration). Drilling rig operability is estimated based on joint wave direction–height distributions, drilling vessel flex-joint angle limits, and operator response (rig rotation) when operating limits are exceeded. A Monte Carlo simulation yields a probability distribution of the duration of the July–November operating season. When integrated with drilling activity cost and schedule information, the framework provides a quantitative foundation to develop risk-based cost and schedule estimates to support project planning and decision-making at various levels, from portfolio management and asset evaluation to detailed execution planning.