The objective of this paper is to highlight the necessary steps for the successful use of integrated asset modeling. It presents the full workflow for optimzing production and injection cycle times with the help of a simplified reservoir model (SRM) through the set up of an integrated asset model (IAM) to validate the SRM results and control the actual production performance. A discusson of the theory of the IAM as well as the steps to set up a SRM and IAM are presented in this paper. The steps are described in context of an actual field operation. A WAG cycle optimization workflow for the Snorre field has been created to demonstrate the advantages of using the SRM and IAM technology. The optimization process is performed using a SRM able to run a simulation run in a matter of minutes and hence being suitable for sensitivity analysis and optimization. The optimized WAG injection and production cycle is then carried forward to an IAM in order to accurately determine the well performance and the reservoir production. The IAM couples the modeling results from reservoir and well model with the surface facility network and process plant model. The coupling and integration allows investigating the impact of changes in one model to all the other models and hence also handles the proper propagation of constraints throughout the system. Introduction Coupling a full field reservoir simulation model with a surface facility network model allows for more accurate computation of hydrocarbon recovery since both system imposed constraints (fluid flow from the reservoir and surface constraints), can be considered simultaneously. The integrated asset model (IAM) comprises of a coupled system of reservoir simulation models with surface facility network models. The purpose of coupling is to balance a reservoir simulation model with the response of the surface facilities. The IAM consists of three distinct parts: The reservoir model, the well model and the surface facility model. These three models are coupled at coupling points, each passing the conditions at the coupling point on as a new boundary condition for the next model. The reservoir simulation model as a starting point computes the fluid movement and pressure distribution in the reservoir model, passing the information about the pressure and fluid saturation at the subsurface coupling point (well locations in the reservoir model) to the well models (conditions at sandface). In the well model the information about the conditions at the coupling point (sandface) is used as a boundary condition in order to compute the fluid rates or the pressure at the surface coupling point (e.g. well head), where the well model is linked to the surface facility model. The well model surface boundary condition acts as sink or source term in a surface network, which has to be balanced to account for varying fluid flow and pressure conditions in every well in the system. Their interaction will ultimativley lead to a newly calculated backpressure of the production system for every well. The system backpressure is then conveyed all the way back through the well model back into the reservoir in order to account for the changed boundary condition imposed by the surface model in the reservoir.