Intelligent Drilling of Oil and Gas Wells Using Response Surface Methodology and Artificial Bee Colony

The oil and gas industry plays a vital role in meeting the ever-growing energy demand of human race needed for its sustainable existence. Newer unconventional wells are drilled extraction hydrocarbons that requires advanced innovations to encounter challenges associated with drilling operations. type drill bits utilized any operation has an economical influence on overall operation. selection suitable is challenging task driller while planning new wells. Usually, when it comes deciding bit type, generally, data previously present similar geological formation analyzed manually, making subjective, erroneous, time consuming. Therefore, main objective this study was propose automatic data-driven method target based Optimum Penetration Rate (ROP). Response Surface Methodology (RSM) Artificial Bee Colony (ABC) have been develop modeling approach optimum type. Data from three nearby Norwegian testing proposed approach. RSM implemented generate function ROP due strong data-fitting characteristic, ABC locate global optimal value ROP. model generated 95% confidence level compared existing Neural Network Genetic Algorithm. can also be applied over other field automate selection, which minimize error cost. United Nations Development Programme promotes industrial sectors sustainability.