This study examined impacts of successive iteration of root-mean-square values on matching historical data with data obtained from simulator. Root-Mean-Square (RMS) is simply the magnitude of a set of numbers. The magnitude is a difference between two data sets, which was reduced. An RMS value of 24.389 was reduced to 20.788 and then to an acceptable value of 11.72. A match obtained was used to make 10 years forecast with a fluid rate of 500stb/day and 1500stb/day for two predictions. Results obtained from one of the simulator's predictions were compared with a third-order degree polynomial. It is required to identify regions whose faults have significant contribution to produced water volume. This is necessary because some faults do have zero transmissibility. Region with zero transmissibility sealing fault cannot be produced by flooding across the region. Inactive faults were identified through sensitivity analysis; it was discovered that bottom and flank water entered the region through the left flank and vertically upward from the bottom. Historical data of produced water were eventually matched with that simulated at an RMS value of 11.72 to generate future data for Sagbama. Sagbama is a name given to a hydrocarbon reservoir with the following characteristics: 16,404.2ft by 16,404.2ft by 197.85ft, gridded into 1,640.42ft in x-direction, 1,642.42ft in y-direction, and 49.212ft in z-direction. It consists of live oil and gas with unknown volume of bottom water drive. Densities of oil, water, and gas under consideration are 749.389 kg/m 3 , 1000 kg/m 3 and 1.11242 kg/m 3 respectively. Reference pressure was 400bar and rock compressibility took a value of 4.0E-5/bar. Datum depth of 3000m with 331.65bar as it the pressure at the datum, depth to gas-oil contact was 3000m without capillary pressure.
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