Edy Soewono
Department of Mathematics, Institut Teknologi Bandung, Jalan Ganesa No. 10 Bandung, Jawa Barat 40132, Indonesia

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Optimization of Vertical Well Placement for Oil Field Development Based on Basic Reservoir Rock Properties using a Genetic Algorithm Ariadji, Tutuka; Sukarno, Pudjo; Sidarto, Kuntjoro Adji; Soewono, Edy; Riza, Lala Septem; David, Kenny
Journal of Engineering and Technological Sciences Vol 44, No 2 (2012)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (552.057 KB) | DOI: 10.5614/itbj.eng.sci.2012.44.2.2


Comparing the quality of basic reservoir rock properties is a common practice  to  locate  new  infill  or  development  wells  for  optimizing  oil  field development using reservoir simulation. The conventional technique employs a manual  trial-and-error  process  to  find  new  well  locations,  which  proves  to  be time-consuming, especially for large fields. Concerning this practical matter, an alternative in the form of a robust technique is introduced in order to reduce time and  effort  in  finding  new  well  locations  capable  of  producing  the  highest  oil recovery. The objective of this research was to apply a genetic algorithm (GA) for determining well locations using reservoir simulation, in order to avoid the conventional  manual  trial-and-error  method.  This  GA  involved  the  basic  rock properties,  i.e.  porosity,  permeability,  and  oil  saturation,  of  each  grid  block obtained from a reservoir simulation model, to which a newly generated fitness function was applied, formulated by translating common engineering  practice in reservoir  simulation  into  a  mathematical  equation  and  then  into  a  computer program. The maximum fitness value indicates the best grid location for a new well. In order to validate the proposed GA method and evaluate the performance of the program, two fields with different production profile characteristics were used, fields X and Y. The proposed method proved to be a robust and accurate method to find the best new well locations for oil field development. The key to the success of the proposed  GA method lies in the formulation of the objective functions.