Application of Integrated Production and Asset Modeling for Sour Field Development Planning (SPE 154073)

A challenging issue in the EP industry is Integrated Asset Management, which encompasses efforts from various disciplines to build a single integrated model that describes the whole system. This paper presents an integrated production model (IPM), forecasting workflow and decision making philosophy to develop two complex sour fields comprising three reservoirs in South of Oman. The study involves two sour oil reservoirs of different PVT properties, H2S concentrations and drive mechanisms and one sour gas condensate reservoir used to complement associated gas to give a constant gas rate for export. Water injection and water handling are parts of the model. The modeling couples subsurface dynamic 3D models (built using Shell's MoReS reservoir simulator), well models and surface network (built in GAP) and the interactions occuring in the production system. The configuration involves three reservoirs, 19 oil and 3 gas producers, 12 water injectors, one production station, two separators (low and high pressure) and several flow lines of different sizes. The main objective of the study is to optimize the developments of these reservoirs by assessing the best design of surface network (plant capacity). The integration allows to assess the impact of various station capacities; either liquid or/and gas, on the project profitability under different operational scenarios such as injection rate, off-take, artificial lift and well phasing and their impact on CAPEX and OPEX. The model also helps in identifying system bottle-necks, back pressure effects, mixing of fluids and flow assurance. The use of jet pumps as artificial lift mechanism was successfully imbedded and optimized. The paper describes the structure of modeling, surface components, optimization strategy, benefits and challenges of IPM deployment to choose the optimum field design. The results demonstrate the importance and merit of field management in addition to accuracy and rapidness of production forecast.