Based on the traditional numerical simulation and optimization algorithms,in combination with the layered injection and production"hard data"monitored at real time by automatic control technology,a systemati...Based on the traditional numerical simulation and optimization algorithms,in combination with the layered injection and production"hard data"monitored at real time by automatic control technology,a systematic approach for detailed water injection design using data-driven algorithms is proposed.First the data assimilation technology is used to match geological model parameters under the constraint of observed well dynamics;the flow relationships between injectors and producers in the block are calculated based on automatic identification method for layered injection-production flow relationship;multi-layer and multi-direction production splitting technique is used to calculate the liquid and oil production of producers in different layers and directions and obtain quantified indexes of water injection effect.Then,machine learning algorithms are applied to evaluate the effectiveness of water injection in different layers of wells and to perform the water injection direction adjustment.Finally,the particle swarm algorithm is used to optimize the detailed water injection plan and to make production predictions.This method and procedure make full use of the automation and intelligence of data-driven and machine learning algorithms.This method was used to match the data of a complex faulted reservoir in eastern China,achieving a fitting level of 85%.The cumulative oil production in the example block for 12 months after optimization is 8.2%higher than before.This method can help design detailed water injection program for mature oilfields.展开更多
To study the fluid dynamic response mechanism under the working condition of water injection well borehole,based on the microelement analysis of fluid mechanics and the classical theory of hydrodynamics,a fluid microe...To study the fluid dynamic response mechanism under the working condition of water injection well borehole,based on the microelement analysis of fluid mechanics and the classical theory of hydrodynamics,a fluid microelement pressure-flow rate relationship model is built to derive and solve the dynamic distribution of fluid pressure and flow rate in the space of well borehole.Combined with the production data of a typical deviated well in China,numerical simulations and analyses are carried out to analyze the dynamic distribution of wellbore pressure at different injection pressures and injection volumes,the delayed and attenuated characteristics of fluid transmission in tube,and the dynamic distribution of wellbore pressure amplitude under the fluctuation of wellhead pressure.The pressure loss along the wellbore has nothing to do with the absolute pressure,and the design of the coding and decoding scheme for wave code communication doesn’t need to consider the absolute pressure during injecting.When the injection pressure is constant,the higher the injection flow rate at the wellhead,the larger the pressure loss along the wellbore.The fluid wave signal delay amplitude mainly depends on the length of the wellbore.The smaller the tubing diameter,the larger the fluid wave signal attenuation amplitude.The higher the target wave code amplitude(differential pressure identification root mean square)generated at the same well depth,the greater the wellhead pressure wave amplitude required to overcome the wellbore pressure loss.展开更多
基金Supported by the Key Program of Petro China Exploration&Production Company(Grant No.kt2017-17-01-1 and kt2017-17-06-1)Consulting Project of Chinese Academy of Engineering(Grant No.2019-XZ-17)
文摘Based on the traditional numerical simulation and optimization algorithms,in combination with the layered injection and production"hard data"monitored at real time by automatic control technology,a systematic approach for detailed water injection design using data-driven algorithms is proposed.First the data assimilation technology is used to match geological model parameters under the constraint of observed well dynamics;the flow relationships between injectors and producers in the block are calculated based on automatic identification method for layered injection-production flow relationship;multi-layer and multi-direction production splitting technique is used to calculate the liquid and oil production of producers in different layers and directions and obtain quantified indexes of water injection effect.Then,machine learning algorithms are applied to evaluate the effectiveness of water injection in different layers of wells and to perform the water injection direction adjustment.Finally,the particle swarm algorithm is used to optimize the detailed water injection plan and to make production predictions.This method and procedure make full use of the automation and intelligence of data-driven and machine learning algorithms.This method was used to match the data of a complex faulted reservoir in eastern China,achieving a fitting level of 85%.The cumulative oil production in the example block for 12 months after optimization is 8.2%higher than before.This method can help design detailed water injection program for mature oilfields.
基金Supported by the National Natural Science Foundation of China(52074345)CNPC Research and Technology Development Project(2021ZG12).
文摘To study the fluid dynamic response mechanism under the working condition of water injection well borehole,based on the microelement analysis of fluid mechanics and the classical theory of hydrodynamics,a fluid microelement pressure-flow rate relationship model is built to derive and solve the dynamic distribution of fluid pressure and flow rate in the space of well borehole.Combined with the production data of a typical deviated well in China,numerical simulations and analyses are carried out to analyze the dynamic distribution of wellbore pressure at different injection pressures and injection volumes,the delayed and attenuated characteristics of fluid transmission in tube,and the dynamic distribution of wellbore pressure amplitude under the fluctuation of wellhead pressure.The pressure loss along the wellbore has nothing to do with the absolute pressure,and the design of the coding and decoding scheme for wave code communication doesn’t need to consider the absolute pressure during injecting.When the injection pressure is constant,the higher the injection flow rate at the wellhead,the larger the pressure loss along the wellbore.The fluid wave signal delay amplitude mainly depends on the length of the wellbore.The smaller the tubing diameter,the larger the fluid wave signal attenuation amplitude.The higher the target wave code amplitude(differential pressure identification root mean square)generated at the same well depth,the greater the wellhead pressure wave amplitude required to overcome the wellbore pressure loss.
