Reservoir Simulation Mini – Project – II

Roll No: 58,60,62,64,66,68,70,72,74,76

OBJECTIVETo determine effect of grid-block sizing on the performance of a horizontal well.

What and why are Grid Blocks ?

• Grid Blocks: They are reservoir volume elements .

If we wont dicretise reservoir model , then heterogeneity of the reservoir (permeability anisotropy , faults etc )would not be taken into account leading to less accurate predictions.

Selection of grid sizes

• Criteria : The gridblock sizes must be small enough to satisfy 5 requirements. They must

1. Identify saturations and pressures at specific locations.2. Describe the geometry, geology, and initial physical

properties of the reservoir .3. Describe dynamic properties.4. Model reservoir fluid mechanics properly.5. Should be compatible with the mathematics in the

solution segments of the simulator .

METHODOLOGY• Construct a Reservoir Model by selecting one

grid block size .• Vary the grid blocks size and determine their

respective results .• Compare results of all the grid blocks size

taken .• Conclusion .

Model Construction • Data Used :

Reservoir Temperature 113 F

Areal Extent 240 acres

Average Depth 4442 ft ( TVD)

Net Pay Zone Thickness 7 ft

OWC 4578 ft ( TVD)

Oil Density 37 API

Model • Reservoir Model with Grid Block size of

9*9*24.

Model• Reservoir Model with Grid Block size of

63*63*24.

ModelReservoir Model with Grid Block size of 109*109*24.

Comparison of fineness

Results: For Grid Size 9*9*247 .00 e+7

Results: For Grid Size 63*63*24

6.00 e+7

Results: For Grid Size 109*109*245.932 .00 e+7

Conclusion

• After comparing the results , we can see that there was a significant change cumulative oil SC between 9*9*24 and 63*63*24

• But not much difference between 63*63*24 and 109*109*109.

• Fineness of grid block size 63*63*24 is feasible to simulate considering the time constraint and accuracy of prediction.

umerical models offer a more detailed method of modeling pressure/rate data by dividing the reservoir into smaller blocks. Rigorous material balance calculations are performed on each block to account for diffusion based onpermeability, saturation, porosity, and fluid properties. Variations in these parameters can be rigorously accounted for which gives the numerical models a huge advantage over conventional analytical models which assume a homogenous reservoir with constant reservoir and fluid properties. Numerical models are ideal for modeling multiphase situations where you may have solution gas in addition to changing saturations. The underlying assumption of the analytical models for production data analysis is single phase flow in the reservoir. In order to accommodate multiple flowing phases, the model must be able to handle changing fluid saturations and relative permeabilities. Since these phenomena are highly non-linear, analytical solutions are very difficult to obtain and use. Thus, numerical models are generally used to provide solutions for the multi-phase flow problem. The numerical engine used in the software is based on a general purpose black-oil simulator. Numerical models can be created with less simplifying assumptions for reservoir properties than analytical models. The reservoir heterogeneity, mass transfer between phases, and the flow mechanisms can be incorporated rigorously. Numerical models solve the nonlinear partial-differential equations (PDE’s) describing fluid flow through porous media with numerical methods. Numerical methods are the process of discretizing the PDE’s into algebraic equations and solving those algebraic equations to obtain the solutions. These solutions that represent the reservoir behavior are the values of pressure and phase saturation at discrete points in the reservoir and at discrete times. The advantages of the numerical method approach are that the reservoir heterogeneity, mass transfer between phases, and forces/mechanisms responsible for flow can be taken into consideration adequately, for instance, multiphase flow, capillary and gravity forces, spatial variations of rock properties, fluid properties, and relative permeability characteristics can be represented accurately in a numerical model. In general, analytical methods provide exact solutions to simplified problems, while numerical methods yield approximate solutions to the exact problems. One consequence of this is that the level of detail and time required to define a numerical model is more than its equivalent analytical model.