Flowing Feature And Optimization Of Multi-branch Horizontal Well In Offshore Low Permeability Reservoirs

Oil production from offshore low permeability reservoirs has become an important source which is favorable for production performance of offshore reservoirs. Multi-branch horizontal well has advantages in this type of reservoirs comparing with conventional horizontal well and vertical well. So knowing its flowing feature and optimization are of great significance. In this work, a multi-segment well model for multi-branch horizontal well was built. The simulation parameters’ effect on simulation result was analyzed. Flowing characteristics differences between multi-branch well and horizontal well were compared. Furthermore we studied the flowing feature and flowing rate distribution in wellbore of different patterns of multi-branch wells. Based on genetic algorithm(GA), a program was written which realized the automatic optimization process of initial group initialization, coding and encoding of chromosome, calling the simulator, target vector computing, GA operations, objective function computing. For the shortage of standard GA, two methods were used including using orthogonal design to initialize first group, adaptive crossover and mutation probability. Finally, we optimized the well location, well trajectory, and well type parameters in a real reservoir in Pearl River Mouth Basin, using GA assisted with hill-climbing algorithm. Results show that grid size and segment length have little effect on the simulation result. Pressure loss in the wellbore is very small when oil production is low. Acceleration loss of fluid is considerably larger than friction loss. Shapes of the isobars around multi-branch wells is similar with the shape of itself. Flow rate distribution in the main bore is characterized by step-shaped and flow rate distribution of the main bore is characterized by dissymmetric U-shaped. Flow rate in the laterals decreases along the direction from heel to toe. Due to different reciprocal interference among the branches, flow rate in different patterns of multi-branch wells is different. The automatic optimization program built based on GA in the paper, whose search step length is small, and searching space is great, can obtain desirable optimum result. Initializing first group using orthogonal design avoids the blindness of searching in early stages and improves the optimum result. Adaptive crossover and mutation probability can avoid blindness and precocity. The optimum multi-branch horizontal well parameters for the real reservoir in Pearl River Mouth Basin are main bore length 980 m, branches 230 m, 230 m, 240 m, branch angle 60 degree, 3 branches.