A comparative study of several metaheuristic algorithms for optimizing complex 3-D well-path designs

Abstract

Considering the importance of cost reduction in the petroleum industry, especially in drilling operations, this study focused on the minimization of the well-path length, for complex well designs, compares the performance of several metaheuristic evolutionary algorithms. Genetic, ant colony, artificial bee colony and harmony search algorithms are evaluated to seek the best performance among them with respect to minimizing well-path length and also minimizing computation time taken to converge toward global optima for two horizontal wellbore cases: (1) a real well offshore Iran; (2) a well-studied complex trajectory with several build and hold sections. A primary aim of the study is to derive less time-consuming algorithms that can be deployed to solve a range of complex well-path design challenges. This has been achieved by identifying flexible control parameters that can be successfully adjusted to tune each algorithm, leading to the most efficient performance (i.e., rapidly locating global optima while consuming minimum computational time), when applied to each well-path case evaluated. The comparative analysis of the results obtained for the two case studies suggests that genetic, artificial bee colony and harmony search algorithms can each be successively tuned with control parameters to achieve those objectives, whereas the ant colony algorithm cannot. Keywords Metaheuristic algorithms • Well-path designing • Well-path optimization • Genetic algorithm • Harmony search • Artificial bee colony List of symbols Definitions of wellbore trajectory variables (modified after Shokir et al. 2004) 1 , 2 , 3 First, second and third hold angles, °

Optimizing the separation factor along a directional well trajectory to minimize collision risk

“…Minimizing wellbore length for complex directional well trajectories taking into account a range of constraints including, inclinations, build rates, azimuths, dog-leg severity (DLS) and frictional torque on the drill string has been the focus of several studies (Atashnezhad et al 2014;Mansouri et al 2015;Wood 2016a), some using a range of evolutionary optimizers and metaheuristic algorithms (Wood 2016b;Khosravanian et al 2018). Well-design optimization also involves a number of other considerations, such as casing placement scenarios (Khosravanian and Aadnoy 2016) and well-collision issues (Wang et al 2016).…”

“…The main objective function of this study is the maximization of the minimum wellbore separation factor, while recent wellbore optimization studies have focused on the optimization of wellbore length, torque and drag, etc. (Atashnezhad et al 2014;Mansouri et al 2015;Wood 2016a;Khosravanian et al 2018). To demonstrate and validate the effectiveness of this novel and easy-to-apply approach, we apply the model to an example well cluster from an offshore platform in the Persian Gulf.…”

Old well sidetracking selection standards: Sulige low-permeability gas field, China

“…Many theories, methods and models have been used to optimize well trajectory (Sawaryn and Thorogood 2005;Qi et al 2014;Wang et al 2016). Khosravanian et al (2018) used metaheuristic algorithms including genetic, ant colony, artificial bee colony and harmony search algorithms to optimize complex three-dimensional well-path length and minimize drilling cost. Manshad et al (2019) considered the parameters in fishbone configuration well including length of main hole and side track, space between side tracks, number of side tracks, and angle between side track and main hole to maximize the reservoir contact and well productivity.…”

“…For the fields especially in the Middle East fields with good reservoir properties, the geological risks of oil/gas wells are small. The influences of reservoir geological conditions on sidetracking well trajectory are rarely considered in these studies (Khosravanian et al 2018;Manshad et al 2019). However, reservoir distribution and resource condition are the bases of sidetracking well location design and optimization, especially in low-permeability oil/gas field where the reservoir is discontinuous.…”

A novel hybrid AGWO-PSO algorithm in mitigation of power network oscillations with STATCOM

“…Introduction. The application of metaheuristic algorithm is growing in finding the optimal solutions to the complex engineering problems [33], [19]. There are numerous benefits of these algorithms in terms of their creation and applicability.…”