Aquifer Water Movement Into Oil And Gas Reservoirs: Prediction And Performance Analysis

Flow Models for Aquifer Water Movement into Oil and Gas Reservoirs

Question :

Discuss about the Modelling Techniques of Mechanical Engineering ?

The paper has been for the aquifer water movement into or out of the oil or the gas reservoirs. This is based on the aquifers which are mainly for the maintenance of the pressure, with the balance of the material and the well-flooded calculations. For this, the gas storage operations work on the movement of water and the prediction of the pressure with the pore volume behaviour. Through this, there have been volume which has been occupied by the reservoir fluid where the flow model has been used for the idealised and the mathematical representation of the water flow. It is based on the prediction setup of the movement of water where there is a need for selecting the flow model and to handle the reservoir aquifer system. The quantity is based on computing the reservoir pressure and then working on the water-influx rates which are able to predict and handle the amount of the gas reservoir pressure and the pore volume performance for the gas-in-place schedule. (Abdulkarim, 2015). With this, the model has been applied for the reservoir performances which is set by the thick sand model with the radial flow

The prediction of the water movement need to work on the flow model for the reservoir aquifer system where there has been a detailed flow model to date the radial flow. The horizontal approach includes the interface between the reservoir fluid and the water of the aquifer with the proper depth set for the underlying the reservoir. The bottom-water drive will be able to handle the 3D model which accounts mainly for the pressure gradients and the other flow of the water system in a vertical direction. This is working in a detailed description through the formulation of the governing behaviour to solution of the equation. The model mainly accounts for the cases of the vertical permeability which is set in equal to the fraction of the horizontal permeability pattern. (Naderi et al., 2016). The drop of pressure values can easily be used to predict the reservoir from the water-influx rates. It includes the prediction of the water-influx when a known reservoir pressure is there. The gravity includes the analysis of the patterns where there has no major effect on the flow of the homogenous fluid and the other boundary conditions. Hence, the gravity acceleration is zero when there is a final result is found to be unchanged. The pressure distribution can easily be altered by the inclusion of the analysis of the gravity with the time constant hydrostatic head. The equations are working on the development and prediction of the pressure with the pore-volume behaviour for gas storage. The prediction is also based on the bottom reservoir performance on the bottom water drive model which completely differs from the other horizontal flow model which are based on van Everdingen and Hurst. (Osman et al., 2015). The problem is based on the physical interpretation which is for the practical significance. It includes the gravity in the analysis with the trivial pattern that has no effect on the flow of the homogenous patterns with the compressing fluid with the fixed boundary system which is subjected to the boundary conditions. The gravity acceleration is zero where the final results is found to be unchanged. The pressure distribution is based on alteration by including of the gravity. The time-constant hydrostatic head is based on applying the prediction the pressure and the pore-volume behaviour of the gas storage reservoir.

Prediction of the Reservoir Performance

The edge water drive flow model can easily be treated by the Everdingen and Hurst which includes the thickness of the aquifer h which is small in relation to the reservoir or the radius r. The water is easily able to invade and recede from the field at the edge of the latter where there have been horizontal radial flow which are seen in the figure. The bottom water-drive reservoir aquifer system has been properly sketched. The thickness of the aquifer is h is based on the relation to r where the flow of the water is in and out of the reservoir for the rough horizontal reservoir fluid interface. (Spain et al., 2015). The aquifer is considered to be holding the right circular cylinder of the height h and the radius at the exterior which. There have been upper and the lower faces which are found to be impermeable except for the portions of the face which is at the upper side and intersected by the reservoir. The formation of the aquifer is considered to be constant but completely unequal to handle the permeability in the direction set in the horizontal and the vertical direction. The consideration is also about the average vertical permeability which is equal to the average of the horizontal permeability that is set in the aquifers with a thin and the shale streaks in discontinuous manner. The fraction taken is 1 and the applications for this thick model is considered to be homogenous.

The petroleum reservoirs are set in contact with the aquifers which provide the support through the influx of water. The prediction is based on the behaviour of accurate aquifer model. The flow geometry is with the reservoir aquifer system which has been the edge water and the bottom water drive. The edge water drive where the patterns are based on radial diffusivity equation. The assumptions are based on the better model with coats that has been model which takes into account for the vertical flow effects. The objective is based on the development of the depletion strategy for the active bottom water drive reservoir which improves the oil recovery with the reduction of the water production. It is mainly due to the coning, with the delay water breakthrough time and then pre-identifying the well to work on excessive water production. (Codrington et al., 2016).

Considering the knowledge of the solution, the diffusive equation has been mainly to govern the water movement aquifer which is set about the bottom water drive reservoir. With this, there have been validity for the radial infinite aquifers are set. The other pattern obtained is the use of the finite Hankel transformation which is for the aquifers to handle the fitness degrees. The significance is to show the difference which arise mainly in between the performance of the field that is set by the thick sand and the radial flow model in horizontal manner. The focus has been on the pressure gradients in the vertical direction which is set mainly due to the water flow. The calculations are for the aquifer water movement which is set for handling the material balance and the well flooding calculations. In gas storage operations work on the water movement where the prediction of the pressure and the pore-volume behaviour. The term includes the denoting the volume which has been occupied by the fluid of the reservoir. (Hosseini et al., 2016). The physical reasonable flow model has been set accordingly to the radial flow model by van Everdingen and Hurst. The cases are depending upon the situations on the aquifer with the horizontal interface between the fluid of the reservoir and the aquifer water. The significance is based on bottom water drive will occur as per the 3D model accounting for the pressure gradients and the flow of water. The vertical direction works on the formulation of the governing of the partial differential equation to solution. The model is based on the vertical permeability which equals to the horizontal permeability. The pressure drop works on the equations to predict the reservoir pressure which is from the known water influx rate with the water influx rate.

Effects of Gravity and Pressure Distribution on Aquifer Water Movement

The focus has been on the increased emphasis of the models with the resistance curve technique which oppose the flow model. The latter approach has been a major necessity that involves the idealisation that involves the different reservoirs mainly to handle the geometry of the aquifer and the homogeneity. The objection is about the arising the cases which violate based on the resistance curve methods. This also includes the objections of the no assumptions that concern about the aquifer geometry and the homogeneity that involves the determination of the resistance curve. (Codrington et al., 2016). The pattern is for the resistance curve method where the will is mainly to replace the model method in the long run with the increased ease and accuracy for calculating the water movement. The method has been set depending upon the edge-water drive gas field gas which has been carried out in effective manner. The different degree of success is set to match the field behaviour through the use of the horizontal flow of the radial model. With this, the reflection is on the different degrees to which the model has been working based on the idealization process. In present, there are certain flow models which are mainly to provide with the useful tool with the prediction set of the reservoir performance. The standards are based on comparison to the resistance curves which are obtained from the field data through a proper reliable method. The example is the pertinence to the resistance curves which might be for the comparison to the different models.

Reference

Abdulkarim, M., 2015. Development of Coning Correlations for Oil Rim Reservoirs using Experimental Design and Response Surface Methodology(Doctoral dissertation).

Osman, A.I.A., Alsayed, H.A. and Elshaikh, M., 2015. Evaluation of Cyclic Steam Stimulation (CSS) Implemented in Bamboo Field (Doctoral dissertation, Sudan University of Science and Technology).

Naderi, M. and Khamehchi, E., 2016. Nonlinear risk optimization approach to water drive gas reservoir production optimization using DOE and artificial intelligence. Journal of Natural Gas Science and Engineering, 31, pp.575-584.

Naderi, M., Rostami, B. and Khosravi, M., 2015. Effect of heterogeneity on the productivity of vertical, deviated and horizontal wells in water drive gas reservoirs. Journal of Natural Gas Science and Engineering, 23, pp.481-491.

Spain, D.R., Naidu, R., Dawson, W., Merletti, G.D., Kumar, R. and Guo, D.Y., 2015, November. Integrated Workflow for Selecting Hydraulic Fracture Initiation Points in the Khazzan Giant Tight Gas Field, Sultanate of Oman. In Abu Dhabi International Petroleum Exhibition and Conference. Society of Petroleum Engineers.

Al-Mudhafar, W.J., Rao, D.N. and Nasab, S.H., 2016, August. Optimization of Cyclic CO2 Flooding through the Gas Assisted Gravity Drainage Process under Geological Uncertainties. In ECMOR XIV-15th European Conference on the Mathematics of Oil Recovery.

Codrington, K., Nancoo-Ali, D., Leung, D., Calvert, P., Nouwens, N. and Harris, D., 2016, June. A Review of Water Reduction Techniques for Open Hole Gravel Pack Completions. In SPE Trinidad and Tobago Section Energy Resources Conference. Society of Petroleum Engineers.

Hosseini-Nasab, S.M., Padalkar, C., Battistutta, E. and Zitha, P.L., 2016. Mechanistic Modelling of the Alkaline/Surfactant/Polymer Flooding Process at Sub-Optimum Salinity Conditions for Enhanced Oil Recovery. Industrial & Engineering Chemistry Research.

Kashefi, K., Pereira, L.M., Chapoy, A., Burgass, R. and Tohidi, B., 2016. Measurement and modelling of interfacial tension in methane/water and methane/brine systems at reservoir conditions. Fluid Phase Equilibria, 409, pp.301-311.