Abstract The paper presents a new methodology for building integrated risk models for reservoir and operational costs. Although the resulting models are fairly simple, they have proved to be adequate in several real-life applications in large field development projects as a part of a total value chain risk analysis. By using these models it becomes possible to optimize intervention strategies with respect to the total net present value of the project or other success criteria such as break-even price. When analyzing operational costs related to an oil or gas field, one usually develops a static cost profile based on the assumed expected yearly production throughout the lifetime of the field. However, when reservoir uncertainty is introduced, this approach breaks down, as different production scenarios must be matched with corresponding operational cost profiles. A typical risk analysis involves carrying out some sort of Monte Carlo simulation. To be able to do this, it is necessary to establish a more dynamic link between reservoir and operational costs. While some of these costs are more or less constant independent of the production, others depend heavily on how much the reservoir produces. In this paper we focus on the last category. It is natural to divide such costs into two subcategories: rare events with high costs, e.g., well interventions such as side-track operations, and frequent events with low costs, typically scale squeeze operations. Two different models will be presented dealing with these issues. For the rare events with high costs case, we present a lifetime model where the time is measured in cumulative production. For the frequent events with low costs, the relation between production and operational costs is developed based on curve fitting.