Drilling

Totally automated drilling today looks like a robot doing all the heavy lifting on a drilling floor. By 2025, there may no longer be anything surprising about it.

Well construction must always be executed safely at reduced operational costs, while ensuring appropriate wellbore quality and placement, per asset team requirements. Consequently, analysis of drilling efficiency, a critical performance indicator, has moved from maximizing rate of penetration to improving cycle time.

A supervised machine-learning algorithm is developed to classify drilling parameters that increase rate of penetration and bit endurance for use in unconventional fields in Australia.

The failure of the Raptor rig to drill its first-ever well offers a short history of the challenges that came with creating the first automated drilling rig.

Drilling automation is not “there” yet, but it no longer seems like a pipe dream.

This paper describes how severe rig limitations were overcome through an optimization plan in which an optimal bottomhole assembly was designed and drilling practices were customized.

This paper presents a methodology that aims to allows the anticipation of problems such as mechanically stuck pipe or lockup situations when running casing or completion strings in hole.

Schlumberger and Russia’s Gazprom Neft have agreed to jointly develop software and promote other upstream services to be commercialized across Russia and internationally.

The fresh investment will result in the manufacture of new drilling-related equipment to assist the national oil company in boosting production capacity.

Although offshore drilling demand is slowly getting better, headwinds remain.