Abstract
AbstractThe most crucial function in drilling wells is the rate of penetration, which is modeled by many researchers, and the best one is Young-Bourgyen model, which is used in this study. Eight factors affecting rate of penetration have been studied and approved in developing a mathematical equation that shows the combined effects of these variables on rate of penetration optimization. This paper presents an efficient way to find the optimum values for parameters of the Young-Bourgyen model using metaheuristic algorithms. An actual drilling data was used from Khangiran field to calculate the difference between the actual penetration rate and the predicted one by different optimization algorithms. Particle swarm optimization, dynamic differential annealing optimization, artificial bee colony, gray wolf optimization, Harris hawk's optimization, flower pollination algorithm, firefly algorithm, whale optimization algorithm, and sine cosine algorithm are used to find best possible solution.
Highlights
The demand for underground resources, like minerals, groundwater in aquifers, and groundsource energy, has increased dramatically in recent decades
This paper presents an efficient way to find the optimum values for parameters of the Young-Bourgyen model using metaheuristic algorithms
An actual drilling data was used from Khangiran field to calculate the difference between the actual penetration rate and the predicted one by different optimization algorithms
Summary
The demand for underground resources, like minerals, groundwater in aquifers, and groundsource energy, has increased dramatically in recent decades. An actual drilling data was used from Khangiran field to calculate the difference between the actual penetration rate and the predicted one by Particle Swarm Optimization (PSO) [9], Dynamic Differential Annealing Optimization, (DDAO) [10], Artificial Bee Colony (ABC) [11], Grey Wolf Optimization (GWO) [12], Harris Hawks Optimization (HHO) [13], Flower Pollination Algorithm (FPA), Firefly Algorithm (FF), Whale Optimization Algorithm (WOA), and Sine Cosine Algorithm (SCA) The results from these metaheuristics are compared and discussed, and no one of them could find acceptable solution. The predicted penetration rate from the proposed procedure was compared with a previous work had used genetic algorithm (GA) to find ROP
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