Affiliation:
1. Auburn University, Department of Chemical Engineering, Auburn, Alabama, USA
Abstract
Sand produced along with well-production fluids accumulates in the surface facilities over time, taking valuable space, while the sand carried with the fluids damages downstream equipment. Thus, sand is separated from the fluid in the sand traps and separators and removed during periodic clean-ups. But at high sand productions, the probability of unscheduled facilities shutdowns increases. Such extreme production conditions can be handled by strategic planning and optimal design of the separator network to enable maximum sand separation at minimal equipment cost while ensuring the accumulation extent is within tolerable limits. This paper develops a mathematical model to optimize the separator network design to maximize sand separation while the sand accumulation extent and total equipment cost are minimal. The optimization model is formulated using multi-objective mixed-integer nonlinear programming (MINLP). The capabilities of the developed model to assist sand management in the separator network are demonstrated with a case study of optimizing the network for two wells producing sand particles of different sizes. A residence time distribution-based model is used to predict sand settling behavior. The developed Pareto Front shows the trade-off between the increase in total sand accumulation rate and total equipment cost for an increase in the fraction of sand settled.