A New Optimization Model for 3D Well Design

This paper introduces a software package that uses a genetic algorithm to find the optimum drilling depth of directional and horizontal wells in 3D. A special penalty function, mutation, crossover probabilities, and stopping criterion were used to obtain the global minimum of drilling depth. This minimum was achieved at the minimum values for kickoff point, inclination angle, build-up and drop-off rates. The minimum values of these parameters reduce the dogleg severity, which in turn reduce the drilling operation problems. The optimized design was compared to the conventional design (based on a trial and error method) and the WELLDES program (based on sequential unconstrained minimization technique) for two wells. The optimized design reduced the total drilling length of the two wells, while all other operational parameters were kept within the limiting constraints. The conventional design and WELLDES program have some variables out of their constraint limits

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