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Articles by Agus Yodi Gunawan
Total Records ( 2 ) for Agus Yodi Gunawan
  Deni Saepudin , Pudjo Sukarno , Edy Soewono , Kuntjoro Adji Sidarto and Agus Yodi Gunawan
  In this study, optimization problems for a cluster of gas lift wells system, which are coupled with a production and gas injection manifold, are discussed. The main goal is to determine the optimum gas injection rate for each well that maximizing the total oil production rate. The total gas for injection is constrained by the maximum availability and the total liquid production rate is constrained by separator capacity. The mathematical model for gas lift problem could be written as a boundary value problem, where the two parameter family non linear differential equation of the boundary value problem represents steady flow equation along the tubing, satisfying wellhead pressure and bottom hole pressure as boundary conditions. Oil production rate is a non-linear function of gas injection rate, which is given implicitly from the gas lift model. A computation scheme based on genetic algorithms is developed to solve the constrained optimization problem with and without considering separator capacity. Our results show quite good estimation for optimum solution. This approach is also flexible to accommodate separator capacity constraints.
  Fajril Ambia , Tutuka Ariadji , Zuher Syihab and Agus Yodi Gunawan
  Region based covariance localization ensemble Kalman filter is a method that incorporating the information of region to ensure that the updated parameters honor the region models such as facies, flow unit, rock type model, etc. Since, the model updated under specified regions, the adjacent parameters would not maintain its spatial correlation if it is under different regions. Therefore, the algorithm could freely update the parameters within the region without considering the values in another region. This approach would fit best in history matching that target reservoir-wide area. On the contrary, the significance of the fluid dynamics rarely follows such regions. The affected areas that influenced the production data is governed by the physics of fluid flow which incorporate the fluid types, relation of rock-fluid properties and so on. Since, history matching use production data as a measurement data, the parameters should only occur in the areas that affected by fluid flow in reservoir. These areas usually smaller than the area provided by regions model. Thus, it could be used to improve localization effect. In this study, we explore the formulation of localization based on the behavior of pressure and fluid flow combined with region based covariance localization ensemble kalman filter. The results show that, the combination of both methods could improve the localization effect while maintaining the defined regions. This method could be useful to improve the area within the wells that affects directly to the production forecast.
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