An optimization method of shale gas drilling parameters based on improved sawtooth genetic algorithm

Abstract

The present invention relates to the technical field of oil drilling and production engineering drilling, in particular to a method for optimizing shale gas drilling parameters based on an improved sawtooth genetic algorithm; including collecting actual drilling problem parameters and encoding them into bit strings; generating initial populations according to the sawtooth cycle Sexual change; define the target fitness function with unit drilling cost; sawtooth optimization population selection, crossover, and mutation operators; select individuals with high fitness according to the target fitness function; screen individuals with high fitness to generate offspring populations, and The child population is the reinitialized population as the beginning of the next iteration cycle, and the cycle is repeated; the number of repetitions reaches the set iteration number termination judgment, and the optimal coordination of drilling parameters and the corresponding unit drilling cost are output. The population size changes periodically according to the sawtooth of the population algebra, which simplifies the algorithm while ensuring a strong global search ability and improving the local optimization accuracy.

Description

technical field [0001] The invention relates to the technical field of oil drilling and production engineering drilling, in particular to a method for optimizing shale gas drilling parameters based on an improved sawtooth genetic algorithm. Background technique [0002] One of the most important links in the design of drilling engineering is the optimization of drilling parameters, which has a great impact on the improvement of drilling economic benefits; the optimization of drilling parameters refers to the process of optimizing the drilling and production operations on site. Optimum combination of parameters to maximize the economic benefits of the entire project. [0003] According to the descriptions in the published literature, the correction of the Younger model with empirical formulas is relatively complex in mathematical derivation and calculation, resulting in low prediction efficiency, and the drilling rate model based on drillability representation and the real-ti...

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Problems solved by technology

[0003] According to the descriptions in the published literature, the empirical formula to correct the Younger model due to the relatively complex mathematical derivation and calculation results in low prediction efficiency, and the drilling rate model based on the drillability representation and the real-time optimization objective function of drilling parameters are not practical enough; multivariate Function extremum method and pattern search method are commonly used methods to solve parameter optimization problems in the industry

[0004] The problem with this commonly used method for solving parameter optimization problems is that the modeling process of the multivariate function extreme value method is relatively complicated, and the global search ability of the pattern search method is weak

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