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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| Format: | Final Year Project |
| Language: | English |
| Published: |
Universiti Teknologi PETRONAS
2011
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| Online Access: | 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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| Summary: | 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. |
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