Numerical simulation of two-phase flow in fractured porous media using streamline simulation and IMPES methods and comparing results with a commercial software

Streamline simulation is developed to simulate waterflooding in fractured reservoirs. Conventional reservoir simulation methods for fluid flow simulation in large and complex reservoirs are very costly and time consuming. In streamline method, transport equations are solved on one-dimensional streamlines to reduce the computation time with less memory for simulation. First, pressure equation is solved on an Eulerian grid and streamlines are traced. Defining the "time of flight", saturation equations are mapped and solved on streamlines. Finally, the results are mapped back on Eulerian grid and the process is repeated until the simulation end time. The waterflooding process is considered in a fractured reservoir using the dual porosity model. Afterwards, a computational code is developed to solve the same problem by the IMPES method and the results of streamline simulation are compared to those of the IMPES and a commercial software. Finally, the accuracy and efficiency of streamline simulator for simulation of two-phase flow in fractured reservoirs has been proved.

Well production optimization using streamline features-based objective function and Bayesian adaptive direct search algorithm

Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.This method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization efficiency.To improve optimization efficiency,a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization(BADS)algorithm is established.This new objective function,which represents the water flooding potential,is extracted from streamline features.It only needs to call the streamline simulator to run one time step,instead of calling the simulator to calculate the target value at the end of development,which greatly reduces the running time of the simulator.Then the well production optimization model is established and solved by the BADS algorithm.The feasibility of the new objective function and the efficiency of this optimization method are verified by three examples.Results demonstrate that the new objective function is positively correlated with the cumulative oil production.And the BADS algorithm is superior to other common algorithms in convergence speed,solution stability and optimization accuracy.Besides,this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional methods.It can provide a more effective basis for determining the optimal well production for actual oilfield development.

Prediction of immiscible gas flooding performance:a modified capacitance-resistance model and sensitivity analysis

Reservoir performance prediction is one of the main steps during a field development plan.Due to the complexity and time-consuming aspects of numerical simulators,it is helpful to develop analytical tools for a rapid primary analysis.The capacitance-resistance model(CRM)is a simple technique for reservoir management and optimization.This method is an advanced time-dependent material balance equation which is combined with a productivity equation.CRM uses production/injection data and bottom-hole pressure as inputs to build a reliable model,which is then combined with the oil-cut model and converted to a predictive tool.CRM has been studied thoroughly for water flooding projects.In this study,a modified model for gas flooding systems based on gas density and average reservoir pressure is developed.A detailed procedure is described in a synthetic reservoir model using a genetic algorithm.Then,a streamline simulation is implemented for validation of the results.The results show that the proposed model is able to calculate interwell connectivity parameters and oil production rates.Moreover,a sensitivity analysis is carried out to investigate effects of drawdown pressure and gas PVT properties on the new model.Finally,acceptable ranges of input data and limitations of the model are comprehensively discussed.

A streamline approach for identification of the flowing and stagnant zones for five-spot well patterns in low permeability reservoirs

The mechanism of the fluid flow in low permeability reservoirs is different from that in middle-high permeability reservoirs because of the existence of the Threshold Pressure Gradient （TPG）. When the pressure gradient at some location is greater than the TPG, the fluid in porous media begins to flow. By applying the mirror image method and the principle of potential superposition, the steady-state pressure distribution and the stream function for infinite five-spot well patterns can be obtained for a low permeability reservoir with the TPG effect. Based on the streamlines distribution, the flowing and stagnant zones in five-spot well patterns can be clearly seen. By the definition of the effective startup coefficient （SUC）, the ratio of the flowing and stagnant zones can be calculated accurately. It is shown that the SUC for five-spot well patterns is not constant, but decreases with the increase of the di- mensionless TPG. By increasing the effective permeability of the formation （such as by the acid treatment and the hydraulic fracture）, in increasing the injection-production differential pressure or shortening the well space （such as by infilling well）, the SUC can be improved. The results of the sensitivity analysis show that a better choice for the SUC enhancement is to shorten the well spacing for small permeability reservoirs and to increase the pressure difference for large permeability reservoirs. This streamline approach can be used to determine the distribution of remaining oil and provide guidance for infilling well.