Following the partnership formed by GE and Noble Corporation Plc, the two companies have launched the world’s first digital drilling vessel, targeted to achieve 20 per cent operational expenditure reduction across the targeted equipment and improve drilling efficiency. This is a concrete step forward to unlock the immense potential of digital solutions for offshore drilling operations.
In the offshore drilling industry, operators have long relied on individuals, leading to significant performance inconsistencies and variance. The downturn of the industry has challenged drillers to look for innovative ways to achieve operational excellence.
Senior Vice President, Operations, Noble Corp, Bernie Wolford, said: “We are very excited to showcase the launch of the Digital Rig solution and the world’s first digital drilling vessel as we continue to expand data-driven operations support while gaining significant efficiencies in drilling operations. The potential of digitalization will go beyond a single vessel, opening the door to transforming our entire fleet. The data backbone paves the way towards autonomous drilling, and digital technology is facilitating a new era of drilling and asset performance improvements that are unprecedented.”
“Partnering with Noble, we are in a unique position to unlock synergies together—from drilling operations to equipment expertise and software analytics skills—to drive holistic transformation of the offshore industry. We are excited to be able to move an important step closer to achieving our vision of a more autonomous future for marine operations,” said Andy McKeran, general manager of GE’s marine solutions. “Noble Drilling has been a vanguard of industry digitalization, and today’s milestone is testament to how industry leaders can collaboratively transform the industry.”
The Digital Rig solution, powered by GE’s Predix platform, deployed on the Noble Globetrotter I drilling vessel has been successfully connected to all targeted control systems, including the drilling control network, the power management system and the dynamic positioning system. Data is collected through individual sensors and control systems, harmonized and centralized on the vessel before transmitting in near real time to GE’s Industrial Performance & Reliability Center for predictive analytics. The delivered implementation and analytics on major marine and drilling equipment have already shown promising results, as the Digital Rig solution captured multiple anomalies and has produced alerts to inform potential failures up to two months before they would occur.
The Digital Rig solution combines data models from a digital replica of physical assets, known as a digital twin, along with advanced analytics to detect off-standard behavior, providing an early warning to operators to mitigate a problem before it strikes. Thanks to vessel-wide intelligence, personnel both on the vessel or onshore can gain a holistic view of an entire vessel’s health state and the real-time performance of each piece of equipment onboard.
Through the learning curve, the digital twin will continue to enhance its predictive capability of machine behaviors and ultimately enable predictive maintenance. This means the personnel offshore can now focus their resources on maintenance activities that are truly needed and effective. The result is reduced unplanned downtime, improved revenue and significant maintenance cost savings. The Digital Rig solution is targeting to deliver up to a 20% reduction in operational expenditures across the targeted equipment.
“As the digital twin continues to acquire information, we will be able to learn from analytics results, which will shed new light on maintenance effectiveness as well as help us explore other possibilities to further improve drilling efficiency in marine settings,” remarked McKeran.
The companies will soon start running analytics on equipment’s real-time data on the edge to localize performance improvements and asset intelligence. The remaining three targeted vessels are on schedule to be digitalized for operational optimization early this year.
