Application of the Artificial Fish Swarm Algorithm to Well Trajectory Optimization


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Resumo

Drilling applications involve a number of global optimization problems that require finding the best extremum value of a nonlinear function of many variables. One of such problems is the choice of the optimal well drilling trajectory. Various trajectory optimization algorithms have been previously proposed, but they all suffer from some shortcomings. In the present paper, the shortest well length is used as the objective function, and optimization is performed by the artificial fish swarm algorithm (AFSA). The calculations have been carried out in the Matlab environment. Comparison of our calculations with previously published data suggests that AFSA optimization produces the best numerical results and the shortest trajectory, while in addition ensuring high stability and reliability. The algorithm has a simple structure and fast convergence, quickly producing a global optimum. AFSA thus may be used to calculate the optimal drilling trajectory.

Sobre autores

Tengfei Sun

Beijing University of Chemical Technology; CNOOC Research Institute

Email: bortum@mail.ru
República Popular da China, Beijing, 100029; Beijing

Hui Zhang

Department of Petroleum Engineering, China University of Petroleum

Email: bortum@mail.ru
República Popular da China, Beijing

Deli Gao

Department of Petroleum Engineering, China University of Petroleum

Email: bortum@mail.ru
República Popular da China, Beijing

Shujie Liu

CNOOC Research Institute

Email: bortum@mail.ru
República Popular da China, Beijing

Yanfeng Cao

CNOOC Research Institute

Email: bortum@mail.ru
República Popular da China, Beijing

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