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.
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Translated from Khimiya i Tekhnologiya Topliv i Masel No. 2 pp. 61 — 64 March —April 2019.
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Sun, T., Zhang, H., Gao, D. et al. Application of the Artificial Fish Swarm Algorithm to Well Trajectory Optimization. Chem Technol Fuels Oils 55, 213–218 (2019). https://doi.org/10.1007/s10553-019-01023-7
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DOI: https://doi.org/10.1007/s10553-019-01023-7