ESTIMATION OF RESERVOIR PARAMETERS USING MATERIAL BALANCE METHOD

Material Balance Equation (MBE) is introduced to understand the inventory of materials entering, leaving and accumulating in a reservoir which results in a better understanding of reservoir development planning as well as for the prediction of water influx. The linearized MBE introduced by Havlen...

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主要作者: Chin, Pui Yee
格式: Final Year Project
語言:English
出版: Universiti Teknologi PETRONAS 2011
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在線閱讀:http://utpedia.utp.edu.my/10455/1/2011%20-%20Estimation%20of%20reservior%20parameters%20using%20material%20balance%20method.pdf
http://utpedia.utp.edu.my/10455/
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總結:Material Balance Equation (MBE) is introduced to understand the inventory of materials entering, leaving and accumulating in a reservoir which results in a better understanding of reservoir development planning as well as for the prediction of water influx. The linearized MBE introduced by Havlena & Odeh is designed in a manner whereby from plotting one variable group against another group, initial hydrocarbon in place can be subsequently obtained. Without detailed knowledge, trial and error approach is necessary and the calculation could be tedious and time consuming. Uncertainties in aquifer properties add up more complications. A simplified approach suggested by El-Khatib to estimate aquifer parameters is reviewed and applied to actual fields, focusing on the saturated oil reservoirs under simultaneous drives. By providing a reservoir's PVT and production history, estimation of initial hydrocarbon in place, ratio of initial hydrocarbon pore volume of gas to oil and water influx parameters could be solved simultaneously. By assuming the time adjustment factor, c in dimensionless time, t0 and dimensionless aquifer size, Reo in sensitivity analysis, numerical inversion of Laplace transform is used to obtain the Van-Everdingen-Hurst (VEH) solution with respect to aquifer parameters. With that, the original oil in place N, gas cap ratio m, and water influx constant B, can be obtained simultaneously with their linear relations in MBE via multiple-regression. Sum of squares of residuals are then computed and mapped for different sets of c and Reo to determine the regions of minima. The non-uniqueness of the map can be countered by understanding of the reservoir and aquifer characteristics. Finally, the approach is outlined to quantifY the possibility in N, m and B. Results have shown convergence to the correct solutions suggested in literature. This project presents an innovative approach as a more robust approach for reservoir preliminary understanding.