%0 Journal Article %1 navabi2015generalized %A Navabi, Shiva %A Khaninezhad, Reza %A Jafarpour, Behnam %D 2015 %J IFAC-PapersOnLine %K optimization pcg_optimization pcg_optimization_oilfieldapplications %N 6 %P 56 - 61 %R http://dx.doi.org/10.1016/j.ifacol.2015.08.010 %T A Generalized Formulation for Oilfield Development Optimization %U http://www.sciencedirect.com/science/article/pii/S2405896315008770 %V 48 %X Abstract Oilfield development involves several key decisions, including the number, type, location, drilling schedule, and operating controls of the wells. If optimized independently, i.e., without considering the coupling between the decision variables, only suboptimal solutions are obtained. A generalized oilfield development optimization approach is proposed to simultaneously optimize these decision variables. It is shown that the source/sink term in the governing multiphase flow equations includes all the decision variables for optimization. By incorporating the drilling cost in the net present value objective function, the proposed formulation transforms the problem into a sparsity-promoting optimization, which is efficiently solved using sparse reconstruction algorithms. Numerical experiments are presented to show the performance of the method for simultaneous optimization of the number, location, type (injection/production), control trajectories, and drilling schedule of the wells.

@article{navabi2015generalized, abstract = {Abstract Oilfield development involves several key decisions, including the number, type, location, drilling schedule, and operating controls of the wells. If optimized independently, i.e., without considering the coupling between the decision variables, only suboptimal solutions are obtained. A generalized oilfield development optimization approach is proposed to simultaneously optimize these decision variables. It is shown that the source/sink term in the governing multiphase flow equations includes all the decision variables for optimization. By incorporating the drilling cost in the net present value objective function, the proposed formulation transforms the problem into a sparsity-promoting optimization, which is efficiently solved using sparse reconstruction algorithms. Numerical experiments are presented to show the performance of the method for simultaneous optimization of the number, location, type (injection/production), control trajectories, and drilling schedule of the wells. }, added-at = {2015-11-04T13:37:10.000+0100}, author = {Navabi, Shiva and Khaninezhad, Reza and Jafarpour, Behnam}, biburl = {https://www.bibsonomy.org/bibtex/275dd1f246a0f065d4c35f735e2048f42/einar90}, doi = {http://dx.doi.org/10.1016/j.ifacol.2015.08.010}, interhash = {cf7c96aeed3ed9ab06ba0ddffa028988}, intrahash = {75dd1f246a0f065d4c35f735e2048f42}, issn = {2405-8963}, journal = {IFAC-PapersOnLine }, keywords = {optimization pcg_optimization pcg_optimization_oilfieldapplications}, note = {2nd \{IFAC\} Workshop on Automatic Control in Offshore Oil and Gas Production \{OOGP\} 2015Florianópolis, Brazil, 27–29 May 2015 }, number = 6, pages = {56 - 61}, timestamp = {2015-11-04T13:37:10.000+0100}, title = {A Generalized Formulation for Oilfield Development Optimization }, url = {http://www.sciencedirect.com/science/article/pii/S2405896315008770}, volume = 48, year = 2015 }