When developing and operating oil and gas fields, a large number of engineering decisions need to be taken. These decisions range from the very high-level such as recovery mechanism, facility sizing or well count to more detailed decisions such as individual well placements, well design and completion strategies. Typically, subsurface models play a role in informing these decisions by testing their effect on forecasted production and it is generally held best practice to test them against a wide range of subsurface conditions, a range that expresses the envelope of subsurface uncertainty. Whilst these commonly held objectives are more or less universal, selecting an appropriate subsurface modelling strategy (i.e. what to model & how to model it) to achieve these objectives usually generates more divergent views. Whilst there are always various valid modelling approaches available which are both geologically and numerically valid, a good modelling strategy pays close attention to the type of the specific decisions being taken for the project and the accuracy required to take those decisions.

To align these views, in decision-based modelling, business decisions and their timing were mapped to the models needed to make the estimates that inform them. Dialogue between the disciplines established the accuracy required for these estimates, and these discussions often revealed surprising opportunities to simplify processes and accelerate delivery. The outcome is a common view on a decision-driven modeling strategy that enables business decisions to be taken efficiently. This strategy, and the subsequent delivery plan that is developed from it is seen as a key to success.

This paper describes the decision-based approach taken in the subsurface modelling required to support quality development decisions for the development of two of KOC's Heavy oil fields through the Enhanced Technical Service Agreement (ETSA) between Shell and KOC. In this particular application of the process, the suite of models to be built has been mutually agreed at the start by the integrated development team through a structured collaborative workshop, or Model Framing Event. A fullfield and a sector model for 2 different fields are discussed to exemplify the link between required decision and supporting modelling approach.

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