Technology Of Real-Time Intelligent Diagnosis And Optimization-Decision For The Electrical Submersible Pumping System

Nowadays,the electrical submersible pump has been the main production method used in offshore oil exploitation.But there are some problems urgent to solve,such as the theory of data screening is blank,the theory of diagnosing working condition in real-time and accurately is not perfect,also the current method cannot optimize and decide production project in real-time and guarantee the operation efficiency.To solve these problems,firstly,this paper combines limiting range screening method,history matching screening method and logical relation screening method to screen production data and test data.Also analyzes characteristics of current curve to establish current curve screening model.Secondly,we consider the effect of radiative heat transfer of annulus gas,thermal dissipation of cable and thermal dissipation of pump unit on fluid temperature to divide the wellbore into four parts.Then we establish a fluid temperature calculation model according to the law of conservation of energy and heat transfer principle.Furthermore,we analyze the relationship among ground electrical parameters monitored in real-time,electrical machine input power,pumping head and suction inlet pressure,combine with performance characteristics of electrical submersible pump well to predict dynamic fluid level from ground electrical parameters.Thirdly,we analyze working condition types of electrical submersible pump well and feature of current curve to establish current curve diagnosing model and current curve feature library.Fourthly,according to principles of electrical submersible pumping system design and optimization aim of maximum system efficiency,combine with electrical submersible pump performance characteristics,inflow performance,wellbore fluid temperature and pressure calculation,establish electrical submersible pumping system optimization-design model with nodal system analysis method.Besides that,determining techno-economic indicators of electrical submersible pump well and establishing optimization-decision model.Finally,compile “Technology of Real-Time Intelligent Diagnosis and Optimization-Decision for Electrical Submersible Pumping System” software.Calculation results indicate that the theory and method in this paper are scientific and reasonable,which can provide guidance for field production and management.The data screening results of 4 oil wells,65 well-times indicate that the accuracy of screening model is 100%,which illustrates that screening model is scientific and can provide true basic data for later calculation and analysis.The calculation results of 20 oil wells indicate that the average relative error of wellbore fluid temperature is about 9.35%,the average relative error of dynamic fluid level is around 12.40%,which illustrates that the dynamic fluid level prediction model is reliable.The current curve diagnosing results of 13 oil wells,19 well-times indicate that the accuracy of diagnosing is 89.5%,which illustrates that the diagnosing accuracy is pretty high and the diagnosing model is practical and useful.The optimization-decision results of 9 well-times indicate that on the premise of guaranteeing production rate,the optimization-decision model can increase system efficiency about 14.40% and increase daily net profit around 264.94 yuan,which illustrates that the model can guide optimization-decision for electrical submersible pumping system effectively,and provide theoretical and technological guidance for field production and management.