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Managing oil fields with multiple reservoirs and shared surface networks optimally is a challenging practical problem. The majority of studies on optimal well placement have focused on either the interactions within the surface network facilities or the dynamic states of the subsurface environment. This work holistically integrates both surface and subsurface sections and addresses well placement, surface network design and allocation, and production/injection planning in a field with multiple irregular-shaped reservoirs. We consider the dynamic, economic, and operational interdependencies of the reservoirs, shared surface network, and common oil market through a complex, nonconvex, and deterministic mixed integer nonlinear programming model. Our approach determines the optimal number and locations of wells, design or retrofit of surface network, connections/allocations of wells with surface facilities, and optimal injection/production planning in water-drive reservoirs. We illustrate the complex interplay of well operations and throughputs using a literature example.

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Integrated management can benefit oil-field development and exploitation tremendously. It involves holistic decisions on the order, placement, timing, capacities, and allocations of new well drillings and surface facilities such as manifolds, surface centers, and their interconnections, along with well production/injection profiles. These decisions have profound long-term impacts on field productivity; however, the dynamic nature of oil reservoirs makes them strongly intertwined and highly complex. Hence, a dynamic, holistic, and integrated approach is necessary. Most existing well placement studies ignore surface effects and drilling-rig availability and assume that all wells are opened simultaneously at the beginning of the production horizon. In this work, we extend our previous study [ Tavallali Tavallali Ind. Eng. Chem. Res.20145311033] and develop a mixed integer nonlinear programming (MINLP) approach for addressing such limiting assumptions. We develop a revised outer-approximation algorithm involving two multiperiod, nonconvex MINLPs and several local search strategies. Numerical results for a literature example show significant improvement in the net present value for oil-field development.