Risk-based budgeting: quantifying Non-Productive Time (NPT) offshore drilling financial risk

Non-Productive Time (NPT) in offshore drilling operations represents a significant yet inadequately managed source of financial risk, responsible for persistent budget overruns that conventional contingency-based approaches fail to address systematically. The primary objective of this study is to develop and implement a Risk-Based Operational Budgeting Framework that transforms NPT from an uncontrolled contingency into a quantifiable, manageable financial variable enabling drilling contractors and operators to replace arbitrary contingency reserves with defensible, data-driven budget allocations. To achieve this objective, NPT events recorded across 279 offshore wells drilled by 69 jackup rigs over one calendar year were classified into 22 operational categories using a modified SPE NPT taxonomy. Category-specific occurrence probabilities were derived as annual time-loss ratios using a purpose-built Java microservice application. A uniform severity metric of US$9,760/hour was applied to monetize time losses into financial exposure. Risks were then evaluated through an ALARP-aligned four-tier probability matrix, inter-rig risk dependencies were captured via a cascaded compound probability model, and a Cost–Benefit Analysis (CBA) was applied to financially justify and optimize mitigation investment. The framework quantified total annual NPT financial exposure at US$369.6 million across the 69-rig fleet (8.7% of total operational time). Cascaded probability analysis identified 40 rigs (58%) as high-risk assets exceeding US$6 million per year. The CBA demonstrated that a mitigation investment of US$32.5 million could achieve up to 86% reduction in NPT costs under full implementation from US$369.6 million to US$50.2 million — yielding net savings of US$319.4 million (ROI ≈ 9.8 ×). A dynamic NPT Risk Budget of US$35.4 million was formulated for operational planning. The study's principal novelty lies in the integrated application of DDR-derived empirical probabilities, fleet-level cascaded risk aggregation, ALARP-justified CBA, and dynamic Risk Budget formulation to a large-scale offshore drilling dataset advancing NPT management from reactive contingency planning to proactive financial risk allocation.