Drilling Parameter Optimization of Shale Gas Wells Based on Saw-Tooth Genetic Algorithm to Reduce Drilling Costs

Abstract

It is difficult to optimize the drilling parameters, which makes it difficult to reduce drilling costs in the process of drilling shale gas wells in the Fuling region of Chongqing, China. This paper takes the optimization combination of drilling parameters in drilling engineering as the research object and uses a saw-tooth genetic algorithm to perform the objective function. To solve the problem, the algorithm proposes a variable population size with periodic reinitialization, which follows a saw-tooth scheme with unequal amplitude and change period (saw-tooth GA), which can optimize the drilling parameters under constraints. According to the actual situation of the wells in the Fuling region, the three algorithms are compared for the vertical section’s drilling parameters. Example calculations show that the algorithm can achieve the best economic benefits at different revolutions per minute and WOB to reduce drilling costs. Compared with other methods, this algorithm has the characteristics of fast convergence, is easy to understand, and is simple to implement. The proposed algorithm is tested for the drilling parameter optimization of shale gas wells and from which it becomes evident that the saw-tooth scheme enhances the overall performance of GAs.