Calculation Method Research On Polymer Flooding Development Index

According to the different reservoir and geological conditions, the thorough study of thecalculating and forecasting method of the polymer flooding development index, and accurateprediction of the amount of oil have been the important guarantee of the implementation ofoptimal control, which also have important significance on the oil recovery enhancement.This paper analyzed and researched the polymer flooding index by reviewing relevantliterature at home and abroad, and using the mathematical methods and the correspondingmathematical treatment, the analysis and research has considered the actual geologicaldevelopment of Daqing Oil Field.The first two chapters of the paper analyzed fundamentals of polymer oil displacement inporous media flow. Use model of the generalized Darcy to deduce the basic differentialequation that seepage of power-law fluid in the formation，and have solved the definitesalutation problem by using numerical method. Analyzed the influencing factor of InflowPerformance Relationship Curve under the condition of calculating various parameters. Thethird part researched polymer drive performance analysis of mathematical model and beingapplied in numerical simulation. The following two chapters further investigated the regularpredictive model and function simulation model, the former one established the differentialprediction model and calculated solution of the model by fitting the coefficient of polymerflooding development dynamic characteristics. Choosing the historical data of the same block,separately use two different types of regular predictive method, which are differentialsimulation prediction and multiple regression analysis and forecasting compare the twomethods and analysis the corresponding result. The last part of the paper utilizes the theory ofNeural Network, considers the effect of parameters on the development of indicators andacquires are the performance function of neural network between the development ofindicators and control parameters, in order to achieve the development index prediction.