In order to determine the importance of influencing factors of energy consumption in oilfield water injection systems, the distribution of energy loss in the water injection system was analyzed, the factors affecting the energy consumption of the water injection system were determined, and an evaluation index system for the energy consumption of the water injection system was established. This indicator system covers all links and all energy loss nodes of the energy loss of the water injection system, thereby an evaluation model for influencing factors of energy consumption in water injection system based on entropy weight - grey correlation method was built. Use the entropy weight method to get the ranking of the importance of energy consumption indicators; use the gray correlation method to determine the correlation between each water injection system and energy consumption factors. The application results show that the entropy weight-grey correlation method proposed in this paper can effectively obtain the importance of the energy consumption factors of the oilfield water injection system, and provide scientific guidance for the daily management and targeted optimization of the water injection system.
Due to the complexity of the large-scale water injection pipe network system and the difficulty of manual analysis, it is impossible to guarantee the optimal operation mode scheme selected. At present, there are still gaps in the research on the judgment of its optimal operation mode. Through the calculation and evaluation of a large amount of water injection system data, the selection method of the optimal operation mode of the water injection system is determined, and it is found that the selection of the optimal operation mode is closely related to the pressure distribution characteristics of the individual wells of the entire water injection system, and five discriminant rules for the optimal operation mode of the water injection system are formed based on these characteristics; the mathematical model for determining the mode and the optimal method of operating parameters is given, and the pipeline network simulation system automatically generates the pipe network topology diagram; the optimal operation mode of the water injection system is developed; Intelligent judgment software can modify its operating parameters according to needs, change operating modes, easily simulate the energy consumption in various modes of operation, adjust and find the optimal operation plan of the water injection pipe network. Application examples show that the judgment rules of the optimal operation mode of the water injection system and the optimization method of operating parameters can be used as an effective means for selecting the optimal operation plan for a large-scale water injection pipeline network.
With the development of oilfield water injection systems becoming more and more complex, relying on artificial experience to judge the efficiency of energy consumption and the status of the system more difficult. Based on hydraulic theory and matrix theory, establish the characteristic equations of the node unit, pipeline unit and auxiliary unit of the water injection system, and use the flow balance to form the overall matrix equation of the water injection system. Established a theoretical model of water injection system simulation, based on this, build a digital intelligent evaluation platform for water injection system energy consumption. In this way, it simulates the production operation status of the water injection system under theoretical conditions and compares it with the actual production operation data, so as to accurately analyze and evaluate the current status of the water injection system’s pipe network energy consumption and the operating efficiency of the branch pipe network energy consumption of each water injection station. The intelligent analysis and evaluation of energy consumption of the water injection pipe network system has been realized, and the optimization and transformation goals have been defined. It has played a significant role in promoting the realization of digital and intelligent oilfield water injection systems.
As intelligence technology develops, there is a higher requirement for computing speed and accuracy of water injection system simulation. In this paper, aiming at the tree-shaped water injection pipe network system of large-scale oilfields, based on the energy equation for calculating the pressure drop [Formula: see text] of pipe section, a mathematical model of the pipeline unit and the node unit is established, and finally, a mathematical model of pipe network for the entire water injection system is established; then, the improved iterative algorithm is used to solve the simulation model of water injection system. In this way, we determine the boundary calculation conditions, take the water injection station as reference node, and use the maximum pressure of water injection well as the initial value of the reference node for calculation, which reduces the number of iterations in model calculation; by comparing the simulation results of different iteration steps, 0.01 is selected as the iteration step size due to its higher calculation accuracy; and the calculation process has also been optimized. The process of solving the characteristic matrix [Formula: see text] is combined with the process of calculating the pressure drop [Formula: see text] of pipe section, and placed outside the algorithm loop, thereby shortening the calculation time of a single cycle and reducing the calculation amount of the algorithm. The application cases show that the proposed optimization algorithm for water injection system pipe network simulation can be used as an effective method to improve the solution speed and calculation accuracy of the simulation algorithm of tree-shaped water injection system in large-scale oilfields.
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