Oil and gas assets usually consist of several interconnected systems and processes. In order to build a reliable asset model, the interaction between the different components of the production system should be incorporated. Integrated Asset Modeling (IAM) presents an effective means of oil fields modeling. It combines reservoir, production and surface engineering modeling into a single software platform allowing simulation of the entire asset. Integrated Asset Modeling helps to identify the different limitations and bottlenecks in the production system and gives an asset-scale overview for future decision making. The aim of this thesis is to build an Integrated Asset Model of a mature oil field and to investigate possible production optimization using state of the art software. The last available data are used to build an updated model of the entire field and the different system bottlenecks are highlighted. Sensitivity analysis performed on the current system shows an important possible increase in oil rate by changing some operating conditions. This is applied mainly for gas-lifted wells where several gas lift allocation scenarios are investigated to determine the optimum gas distribution in the network. A review of the used artificial lift systems is also performed to define optimization opportunities by changing the applied lift methods. Multiple-criteria decision analysis is used to develop a tool that helps to select the best suited lift method for each well. This tool takes into account several well parameters and ranks the different artificial lift methods based on a number of predefined criteria. Updating the integrated model according to the selection results given by the tool shows a significant possible increase in production.