A reservoir simulator called "SimBest II" has been used in the present study. The oil field under study is a sector of South Rumaila oil field/ main pay. The simulator has been used to study the fluid flow in the reservoir and predict the future behavior of the reservoir. SimBest II consists of two parts: Initialization and Simulation. The validity of the model is achieved by comparing its results with historical performance of the reservoir.The validity of initialization results has been adjusted according to the actual initial oil in place and the initial pressure and water saturation distributions. Also good matching has been adopted in the simulation part according to average reservoir pressure, well pressure, the time of water breakthrough, and the depths of oil-water contact. Three types of contour maps were plotted at the end of simulation time for all layers of the sector under study which are Pressure contour map (isobaric map), Permeability times sand thickness (capacity) contour map, Oil saturation times porosity (hydrocarbon porosity) contour map. These contour maps are the best indicator for determining the trapped oil zone. The treatment method of water influx at the flow boundary that used in the current study is the Carter-Tracy method. This method yields an influx of water that moves across the flow boundaries.
Determining the optimal location of the wells is a crucial decision to be made during a field development plan. A reservoir simulator called "SimBest II" has been used in the present study. The oil field under study is a sector of South Rumaila oil field/main pay. Two methods of optimization have been adopted in the present study. The first one is manual optimization and the second method is automatic optimization. Genetic Algorithm (GA) was used as the automatic optimization method to find the best number and locations of the wells. Genetic algorithm depends on the principle of artificial intelligence similar to Darwin's theory of Natural Selection. The genetic program is coupled with the simulator in order to re-evaluate the optimized wells at each iteration. The genetic algorithm computer program gave results similar to the results that are obtained by the manual method with less computer time. Both methods have been adopted according to the aspects of net present value (economic evaluation) as objective function. According to the relationship between net present value and future production time, the abandonment time was estimated before end of December 2014 for all proposed future scenarios. The optimal future scenario was with water injection of 15000 surface bbls/day per well. The optimal number of additional wells for this case was nineteen wells, but it may be impossible to drill such a number of wells in the one year especially in Iraq. Moreover, that an alternative option of drilling three wells with reduction of 0.07399 % in NPV has been considered. This option is also suggested if the surface injection facilities cannot handle the injection of 15000 surface bbls/day. The optimal number of additional wells for this choice is also three wells.
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