First Global Deepwater Autonomous Drilling Project - Artificial Intelligence Application to Derive Optimal Drilling Parameters Within Integration of Rig Orchestration System

Abstract The birth of autonomous system in a high stake deepwater operation has consistently set new benchmarks for operational excellence, enhancing consistency, improving operational safety and reduction in CO2 emission. The paper will present the first application globally for O&G of autonomous drilling in deepwater and the journey to reach the optimal drilling parameters in the entire campaign, integrating proprietary tools from Business Partners of the project. The autonomous solution facilitates seamless integration and interface with the Rig Control System (RCS) and downhole tools, achieving peak automation on a Drillship fostering a forward-looking intelligent execution of the Standard Operating Procedures (SOP), ensuring procedural compliance, minimizing operational and personal risks, and adapting dynamically to the ever-evolving drilling conditions. Multidisciplinary collaboration during the Well Engineering planning phase, combined with strategic change management and stakeholder engagement in the execution phase, allows the drilling crew to concentrate on engineering processes, thereby enhancing performance through data-driven insights, training and mentoring. This was the first deployment of the automation system on a 7th generation drillship and has significantly improved the rate of penetration (ROP), reduced the well construction days, by decreasing Invisible Lost Time (ILT) thereby bringing down the overall AFE days. The well-to-well learning curve has also ensured each well is better than the previous. The AI adaptive technologies have removed repetitiveness, ensure task consistency and operational efficiency. Its self-driven downhole dysfunctional mitigation capabilities continue to sustain the integrity of both surface equipment and Bottom Hole Assembly (BHA) thereby reducing overall operating cost. With the system automated validation protocol and the Automated Trajectory Design (ATD) engines, the well planning cycle has been reduced delivering a coherent Digital Drilling Program (DDP) allowing for a digitally orchestrated well construction processes while the AI completes the close loop for a seamless drilling execution. The high-performance Edge computing device aggregates data that is available through a secured cloud environment for on-site support team to aid Real-Time decision-making processes. Solutions have been applied on all the drilling campaign project, allowing operator to run entire drilling section in autonomous mode on Drilling ship already equipped with orchestration solution. Benefit extended also to the second drilling ship in use during the campaign, allowing application of AI in advisory mode. The paper will briefly describe real case application and the end-to-end requirement for running an AI enabled autonomous solutions either in an advisory or close loop mode especially on a floater and enumerate the challenges that might be encountered and how to overcome them in close collaboration with all the stakeholders involved.

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Publication Details

Journal
SPE Annual Technical Conference and Exhibition
Published
2025-10-13
DOI
https://doi.org/10.2118/227955-ms
Citations
3
Primary Topic
Drilling and Well Engineering
Type
article
Field-Weighted Citation Impact
6.38
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article

First Global Deepwater Autonomous Drilling Project - Artificial Intelligence Application to Derive Optimal Drilling Parameters Within Integration of Rig Orchestration System

L. Vallet, Mohamed Bouaziz, Nadjib Mouzali, S. Spagnolo et al.
3 citations
SPE Annual Technical Conference and Exhibition
Drilling and Well Engineering
6.38
article

First Global Deepwater Autonomous Drilling Project - Artificial Intelligence Application to Derive Optimal Drilling Parameters Within Integration of Rig Orchestration System

L. Vallet, Mohamed Bouaziz, Nadjib Mouzali, S. Spagnolo, Flavio Ferrari, Mohamed Khodja, L. Pinto Vieira, Valerio Bruni, Teddy Nkounkou, Eduard Ghiuzan, Yassine Chikh, Abeer Musbah, Mirella Caso-Salazar, Onyekachi Victoria Chigoziri, Richmond Kweku Duah, Vadim Akhmadeev, Sandro Toppi, Marco Tona, Carmelo Camillieri, Alessandro Artieri, Danilo Melis, Omorogieva Edohen, Teang Zhi Chew
article en
3 citations

Abstract

Abstract The birth of autonomous system in a high stake deepwater operation has consistently set new benchmarks for operational excellence, enhancing consistency, improving operational safety and reduction in CO2 emission. The paper will present the first application globally for O&G of autonomous drilling in deepwater and the journey to reach the optimal drilling parameters in the entire campaign, integrating proprietary tools from Business Partners of the project. The autonomous solution facilitates seamless integration and interface with the Rig Control System (RCS) and downhole tools, achieving peak automation on a Drillship fostering a forward-looking intelligent execution of the Standard Operating Procedures (SOP), ensuring procedural compliance, minimizing operational and personal risks, and adapting dynamically to the ever-evolving drilling conditions. Multidisciplinary collaboration during the Well Engineering planning phase, combined with strategic change management and stakeholder engagement in the execution phase, allows the drilling crew to concentrate on engineering processes, thereby enhancing performance through data-driven insights, training and mentoring. This was the first deployment of the automation system on a 7th generation drillship and has significantly improved the rate of penetration (ROP), reduced the well construction days, by decreasing Invisible Lost Time (ILT) thereby bringing down the overall AFE days. The well-to-well learning curve has also ensured each well is better than the previous. The AI adaptive technologies have removed repetitiveness, ensure task consistency and operational efficiency. Its self-driven downhole dysfunctional mitigation capabilities continue to sustain the integrity of both surface equipment and Bottom Hole Assembly (BHA) thereby reducing overall operating cost. With the system automated validation protocol and the Automated Trajectory Design (ATD) engines, the well planning cycle has been reduced delivering a coherent Digital Drilling Program (DDP) allowing for a digitally orchestrated well construction processes while the AI completes the close loop for a seamless drilling execution. The high-performance Edge computing device aggregates data that is available through a secured cloud environment for on-site support team to aid Real-Time decision-making processes. Solutions have been applied on all the drilling campaign project, allowing operator to run entire drilling section in autonomous mode on Drilling ship already equipped with orchestration solution. Benefit extended also to the second drilling ship in use during the campaign, allowing application of AI in advisory mode. The paper will briefly describe real case application and the end-to-end requirement for running an AI enabled autonomous solutions either in an advisory or close loop mode especially on a floater and enumerate the challenges that might be encountered and how to overcome them in close collaboration with all the stakeholders involved.

SPE Annual Technical Conference and Exhibition
Electroformed Nickel (United States) (US), Saipem (Italy) (IT)
Openalex Percentile: Top 2%
Drilling and Well Engineering
6.38
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