... Abstract Drilling related costs can contribute 30-70% of operators’ capital expenditures for well construction. To reduce costs, operators can reduce bit-on-bottom time and flat time. This work describes a drilling optimization advisory system utilizing machine learning (ML) with integrated...

... a Machine-Learning (ML) based rate of penetration (ROP) optimizer while reducing dysfunctions. This optimizer enables remote control of rig site auto driller setpoints through a seamless cloud-to-cloud connection, without the need for any additional rig devices. The ML ROP optimizer has been previously...

... optimizers using two-dimensional (2D) drill bit images provided by the SPE Drilling Uncertainty Prediction technical section (DUPTS) and labeled by the authors with training from industry subject matter experts. To achieve the modeling goal, the images were first annotated and labeled to create training...

... Abstract In the past half century, many techniques have evolved for the purposes of optimizing key parameters while drilling to achieve performance gains and economic improvements ( Lubinski 1958 ; Speer 1958). More recently, with the advent of computer systems and controls, different...