Horizontal directional drilling (HDD) alignment optimization using ant colony optimization

• Published in: Tunnelling and underground space technology 2020-09, Vol.103, p.103450, Article 103450
• Main Authors: Patino-Ramirez, Fernando, Layhee, Carrie, Arson, Chloé
• Format: Article
• Language: English
• Subjects: Algorithms; Alignment; Angles (geometry); Ant colony optimization; Ant colony optimization (ACO); Design optimization; Design parameters; Drilling; Geometric constraints; Geometry; Horizontal directional drilling (HDD); Mechanical integrity; Mechanical properties; Optimization; Stability; Trenchless
• ISSN: 0886-7798; 1878-4364
• DOI: 10.1016/j.tust.2020.103450

•Ant colony optimization algorithms automate horizontal directional drilling design.•Optimized drill paths have shorter length than conventional designs.•Multi objective optimization allows finding complex drill paths automatically.•ACO significantly reduces the design time in horizontal directional drilling. Horizontal Directional Drilling (HDD) is a trenchless method that consists in drilling an inclined and curved bore from an entry point to an exit point. In practice, HDD is designed iteratively by trial and error, to minimize the cost under geometric and mechanical constraints. In this paper, we optimize the drill path with continuous implementations of an Ant Colony Optimization (ACO) algorithm that sets the depth of the alignment and its entry and exit angles as the design parameters to optimize, to ensure minimal drill path length (cost), avoid collapse or instability (mechanical constraints) and remain in the construction domain (geometric constraint). We compare the ACO results to the drill paths designed in practice in two different scenarios: one in which the entry and exit points are fixed, and one in which the geometry of the central segment is constrained. Results show that ACO can be used to automate the otherwise time-consuming design process while minimizing the drill path length and the costs associated to it.