Production optimization has got growing interest in the context of closed loop reservoir management during the last few years. A comparative solution project was designed in connection with SPE Applied Technology Workshop in Brugge, June 2008 (Brugge field). The Brugge field data set is used to investigate a large-scale waterflooding optimization problem. The net present value (NPV) is maximized by updating the production and injection rates of the smart completions. We use a set of history matched models generated by Lorentzen et al. (SPE119101) for investigation of the adjoint based waterflooding optimization. Here a large number of decision variables should be updated to maximize the NPV.
An efficient procedure is employed to handle the high dimensional optimization problem. The procedure starts with two coarse groups of production/inj ection rates over the time, in the beginning of production and at the moment that the cumulative NPV is halved. After a convergence criterion is met, each coarse group is doubled so that the cumulative NPV values are equal over the refined time interval. The procedure continues until the finest update frequency is achieved. The algorithm is applied to the waterflooding optimization task of the Brugge field. The strategy improves the efficiency of initial optimization steps. Moreover, using the new procedure and 168 variables comparable results were obtained as with optimization using 3,360 variables.
Selection of the coarse optimization time intervals for the updating production and injection rates based on the equal cumulative NPV values obtained over the time provides several advantages. First, the strategy decreases the number of the variables tremendously where the large number of optimization variables makes the large-scale optimization algorithms impractical with the current computer resources. Second, larger and faster updates of the rates are made possible as well as achieving higher optimal NPV values for some methods.
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AbstractThe water coning caused by the imbalance between gravity and viscous forces is the most important reason for water production in different fractured reservoirs. There are various controllable and uncontrollable parameters affecting this phenomenon. In this study different dynamic models were constructed to search for the key parameters affecting the coning process in both single-well and Cartesian multi-well models. It has been determined that oil layer thickness, perforation thickness, fracture permeability and its orientation, especially horizontal not vertical fracture permeability, production rate, mobility ratio, and fracture storativity have the major role in water coning phenomenon. Also it has been determined that fracture spacing, aquifer strength and skin factor have insignificant effect on water coning in fractured reservoirs. The variation of water breakthrough time respect to each effective parameter has also been studied. We concluded that for any production program or adjusting the wells location, the parameter study is very important. Multi-well studies using an Iranian fractured reservoir data show that the trend of dependency of water coning on each parameter is similar to the single-well model. However, in field scale, it is necessary to have all reservoir data including well location, and production history for a successful water coning simulation because a small pressure drawdown exerted by a far well will affect the cone shape and its breakthrough time.
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