Artificial intelligence-based (AI) digital drilling technology was implemented in two mature fields of Ecuador, which represent 33% of the country's oil production and where it is essential to maximize the return on investment. The drilling campaign's main strategy included the deployment of a novel automation solution on two rigs, resulting in the optimization of the well construction process.

In this paper we present the results of implementing a rig automation solution that we applied to 20 wells in 2022. The study primarily focuses on analyzing the results achieved during this period, with the aim of evaluating the solution's effectiveness, performance, and its impact on drilling operations.

The rig automation system uses a goal-based approach to handle constantly changing drilling conditions like drilling dysfunctions and formation changes and repetitive tasks such as downlinking and pre- and post-connection procedures, without having constantly rely on human intervention. The system sends command packages to the rig control system to direct the surface equipment including the draw works, automated driller, top drive, and mud pumps to operate within the constraints of standard operating procedures that are incorporated into the system configuration in the form of procedures, mitigation strategies, and operational limits. It uses powerful data analysis and learning systems to assist and enhance every task from optimizing the rate of penetration (ROP) to drilling a stand autonomously.

Following the deployment of the rig automation solution on both rigs, the team entered into a hyper care phase, which consisted of monitoring the system and training the drillers at the rig-site over a period of at least 3 months, Once concluded, the team spent the next year leveraging the system and routinely reviewing and optimizing the procedures and configuration parameters to maximize value added. Overall, a total of20 wells were drilled with the digital solution throughout 2022 including 214,000 feet drilled in automated mode, an on-bottom ROP improvement of 8.4%, with total time savings adding to 23.86 days, and pre-and post-connection time reductions of 54% on average, with latest wells achieving as little as 6 minutes as compared to the initial benchmark of 25 minutes. Additional collaborative features were implemented, such as the remote monitoring and execution of the directional drilling process, where the engineer located in the remote operations center was able to send a downlink request, and once accepted by the driller, the system would dynamically re-plan a new sequence to incorporate the new goal and execute the downlink procedure autonomously while drilling, while the driller monitored other variables to optimize and drive safer operations. 

In the oil and gas industry, automation is mostly associated with the control of heavy machinery that is operated through predefined sequence automation. This goal-based technology provides a significant advantage by minimizing the human interaction needed to deal with the uncertainty of dynamically changing operations and, ultimately, lower drilling times. This indirectly results in a reduction in the carbon emissions footprint, operational risks, and cost, optimizing efficiency and field development.