This paper presents a complete integrated asset model for gas planning and, in particular, the handling of stranded gas during exploration. Uniquely, it models a gas network from the reservoir, right through to product allocation based on contractual obligations. It back-allocates through the network from the market, to ensure accurate supply and product tracking. We show how this type of model provides unprecedented confidence in field evaluation and gas planning. The market-based approach to integrated asset modelling that we used includes an optimal amount of information to deliver a fast, accurate solution. Oil and gas exploration activities do not usually involve planning for stranded or associated gas. Many discovered gas reservoirs are left undeveloped due to a lack of scenario analysis during the exploration phase. A fully integrated gas planning approach is required for effective field development planning in a timely manner. This has been a subject of intense research and development in recent years. Stranded gas reserves can be effectively developed using proactive market planning and strategic gas exploration guided by an integrated gas planning approach. As such, our model includes reservoirs, platforms, facilities, pipelines and markets to effectively understand the network deliverability. In this paper we defined multiple scenarios for bringing up gas from reservoirs, through the facilities and delivery point, right up to allocation of resources to meet the market demand. The case study deals with a market-based approach for modeling 40 gas reservoirs and associated gas products from nearby platforms. The practical constraints such as condensate handling capacities, compressor systems, and contract gas quality are integrated into the model analysis. The unique, fully integrated reservoir to market approach to IAM we demonstrate in this study provides a real breakthrough in E&P companies’' ability to model and run scenarios against their complete gas network in a relatively very short time. In particular the back-allocation from the market provides confidence around their ability to meet their contractual sales obligations and enables product tracking through the whole network.

The case study presented in this paper will demonstrate the efficiency of an integrated subsurface and surface model running numerous what-if scenarios in a timely manner. It will also compare the results and the time taken to run the same scenarios with current conventional methods of having separate subsurface and surface modelling packages. Surface network configuration of a field depends on the field development strategies. As fields mature and reservoir conditions alter, these strategies change. This leads to changes in the configuration of the surface facilities, such as re-adjusting the facilities target rate, rerouting gas and products to different branches etc. Most of the current commercial Integrated Asset Modeling (IAM) tools, model reservoirs as a material balance tank. However, in cases of complex reservoirs, the material balance solution may not be able to model the full complexity in the behavior of the reservoirs. In such cases using a reservoir simulator to model the reservoir is a better option. Performance of the reservoirs depends on the pressure and capacity constraints of the facilities and also the configuration of the surface network. This demonstrates the importance of coupling a reservoir simulator and a network modeler to accommodate the changes to the surface network while accurately meeting the criteria of reservoir management. An integrated subsurface – surface model enables the user to evaluate the impact of changes in production policies while honoring all reservoir management constraints. In this paper we present the results of a fully integrated gas planning system coupled with a reservoir simulator, for guiding field development. We defined multiple scenarios for bringing up gas from reservoirs, through the facilities and delivery point to meet the market demand. The case study deals with a market-based approach for modelling 3 gas-condensate reservoirs. The unique, fully integrated reservoir to market approach we demonstrate in this study provides the ability to model and run scenarios against their complete gas network in a relatively very short time. In particular, the back-allocation from the market provides confidence in the ability to meet contractual sales obligations.