Non-pipelined Wells Production And Transportation Scheduling Optimization Based On Intelligent Optimization Algorithm

Aiming at the problem of production and transportation scheduling of non-pipelined wells in oilfields,we have established a discrete-time-based optimization model for production and transportation scheduling of non-pipelined wells.Due to the complexity of the discrete-time-based non-pipelined wells production and transportation scheduling optimization model,when the model solves the long-period production scheduling problem of large-scale non-pipelined wells,there will be a large number of variables in the model,which is difficult to solve.Even a feasible solution cannot be obtained within an acceptable solution time,which severely restricts the application of the model in field practice.In order to solve the above problems,this thesis has carried out a research on the optimization model of production and transportation scheduling of non-pipelined wells based on intelligent optimization algorithm,and developed and designed the corresponding software.The research results of this thesis are of great significance to the practical application of this model in oilfields.The main results of the research in this thesis are as follows:(1)This study reviewed the discrete-time-based optimization model for production and transportation scheduling of non-pipelined wells,set up test examples of different scales and scheduling periods from small to large,and used accurate algorithms to solve and calculate them.The results found that in under the small-scale and short-period scheduling scale,the exact algorithm can give a feasible solution or even the optimal solution within an acceptable solution time.However,with the increase of the scheduling scale,it becomes extremely difficult to solve the model,and the exact algorithm cannot solve the problem within a reasonable time.Finding a feasible solution severely limits the application of the model in the field.(2)For the situation that the exact algorithm is difficult or impossible to solve,combined with the established optimization model of production and transportation scheduling of non-pipelined wells,a multi-layer coding genetic algorithm is designed in this thesis.The production and transportation scheduling problem of non-pipelined wells can be quickly solved to obtain a feasible scheduling scheme,and the algorithm design has achieved preliminary results.(3)According to the characteristics of the model,this thesis designs a tabu search algorithm.The designed tabu search algorithm is further optimized to improve the solution efficiency and reduce the driving path of the oil tanker.The algorithm can solve the optimization model of production and transportation scheduling of non-gathering and transportation well groups more quickly,and the solution stability is higher,and the algorithm is not easy to fall into the local maximum excellent.Compared with genetic algorithm,when solving large-scale long-period scheduling,a better solution can be obtained in a shorter time.(4)In the large-scale case analysis part,the advantages and disadvantages of the genetic algorithm and the tabu search algorithm are compared using a large-scale lowyield well case of 200 wells,and it is verified that the designed tabu search algorithm is superior to the genetic algorithm.On the basis of large-scale low-production wells,different scheduling conditions were changed,the adaptability and sensitivity of the tabu search algorithm were tested,and specific case analysis and recommended scheduling schemes were given in the case results section.(5)This thesis integrates the research results of the optimization problem of production and transportation scheduling of non-gathering and transportation well groups,develops and designs the corresponding software,and realizes the practical application of the model.