Software Development Of Energy Consumption Analysis Of Oil Gathering And Transportation System And Integrated Optimizing Design

On the one hand, measure of infilling well pattern has been adopted to guarantee stable production of crude oil in the oilfield during the increased production construction state. Therefore it's badly in need of reasonable layout and construction of gathering network. On the other hand, as the oilfield is in high water and extra-high water cut stage, the problems, such as widespreadly declining load rate of surface producing system, decreasing operation efficiency, rising energy consumption of gathering system and increasing cost of crude oil production, are getting more serious. Therefore, it's necessary to opitmize process links by research of energy consumption analysis and energy optimal utilization. Thus, research and development of"energy consumption analysis of oil gathering system and integrated optimizing design"application software will play an important role in controling energy consumption of oil production, reducing oil production cost and achieving efficient, low consumption, orderly adjustment and scientific management of oil fields surface engineering.In order to solve the problem of layout scheme optimization design of infill well, new construction pipeline and old pipeline network system, the strategy of making as many new nodes as possible flow into old pipeline system is adopted in optimization model to reduce investment and improve system load rate. The optimization results of a block of Daqing Oilfield is that load rate of the secend transfer station increases 23.28% and load rate of the dehydration station increases 5.12%. Firstly, multi objective parameter optimization model of single-pipe tree and water-mixing gathering pipeline network is built; Secondly, multi-objective optimization model is changed into single-objective by using linear weighting method; Then single- objective optimization is solved by multi-level optimization strategy; Lastly, network optimized design of a block of gathering pipeline network is conducted by the use of of software, and result is that pipeline construction investment reduces 5.64%, thermal energy consumption reduces 39.55%.Oil gathering and transportation system is divided into central gathering station, transfer station and dehydration station subsystem. Energy balance model and index system of energy consumption evaluation of each subsystem is separately built. Research on present situation of energy consumption and regularity of distribution of gathering system, the center of which is a dehydration station in Oil Recovery Plant No.3, Daqing Oilfield Corp.Ltd., is done by the use of the software. The results show that low heat energy utilization rate is the energy utilization weak links of the system in the region. After energy-saving reconstruction, average station efficiency of the system increases 3.91%, average pipeline energy dissipation rate reduces 1.81%, average heat energy utilization rate increases 3.76%, average electric energy utilization rate increases 4.32%, electricity-saving quantity per year is 6.58×10~5 kW·h and gas-saving quantity per year is 2.33×10~5 m3.Gray relative analysis method is used into analyzing energy consumption influential factors of oil gathering and transportation system. As a result of this, analysis of the main energy consumption influential factors of the system is done quantificationally. The result of case calculation shows percentage of effective thermal energy in total energy consumption is the main influential factor of average station efficiency of the methoded system.GM (1, 1) model of gray system theory is used into predicting energy consumption level of oil gathering and transportation system. Predicting process of the whole prediction is designed which is fit for computer operation and a corresponding software is developed. Thus, the whole prediction can be done by the computer. The result of case calculation shows the model calculation precision can reach the second level and the prediction result is credible. Key Words:production construction; parameters optimization; energy consumption...