Harnessing A.I. transforms rig power, engine management
Responsible drillers are always looking for ways to reduce the carbon footprint of operations. Being competitive, however, means not only producing each incremental barrel in a cleaner manner, but producing it more efficiently as well. In the past few years, innovative technologies have introduced many pathways to cut emissions and use less fuel, and one of the most effective tools for achieving emissions reductions while maximizing performance is automation.
That was then. This is now. A decade ago, the oil and gas industry considered drilling to be art rather than science, and it was an accepted fact that master drillers who practiced this art made a difference to the bottom line. Applying the knowledge gained over years spent honing their skills, veteran drillers could get good performance from a rig, but they could only deliver superior drilling results on one drilling program at a time. And while less skilled and less proficient drillers could hope to develop an intimate understanding of a rig’s capabilities and use that knowledge to improve drilling performance, there was no guarantee that they would realize the elite level of master driller.
Over time, it became increasingly difficult to hire master drillers who could deliver consistent, exceptional results at a time when the oil and gas sector was facing greater demands to improve its performance. Demographics have dramatically changed within the drilling section, with more than 50% of the workforce having less than two years’ experience. Relying on a handful of experts was clearly not a sustainable long-term plan. It became imperative that the industry produce a better solution. The answer lies in capitalizing on drilling data to execute faster and more efficient drilling programs.
Data analysis. Drilling contractors had been using sensors to track equipment performance on rigs for decades. In many cases, the information gathered was used to better manage equipment usage and schedule maintenance more cost-effectively by using definitive asset integrity data. Some drilling contractors took things a step further and began analyzing data from the engines and equipment after a section was drilled to determine whether the driller was getting the best performance from the rig.
Eventually, data was gathered and analyzed in real time to provide drillers with input to improve drilling speed, but there was no tool that collected performance data to solely improve how well engines are managed. For drilling contractors to achieve efficiencies across the board, there had to be a way to automate engine management and track fuel consumption and emissions.
Industrial automation gains ground. Other high-tech sectors have relied on robots and automation for decades. Not surprisingly, the aerospace industry is one of the leaders. NASA deployed its first autonomous robotics system, the Sojourner Rover, in 1997 to collect data on Mars. Honda introduced a humanoid robot, ASIMO in the early 2000s that could carry out basic daily tasks. The 2011 release of Apple’s Siri triggered a new age of automation and A.I.-driven assistants. And in the automobile industry, automation is now enabling the use of self-driving cars.
The incentive for these major advances in automation is that it streamlines operations, delivering time, cost and resource savings by basing activities on accurate data and drastically minimizing the effects of human variability. The many examples of successful applications to date demonstrate that automated processes can be applied to complex tasks.
Applying automation in the oil field. There was a longstanding belief in the oil and gas industry that drilling is different from other processes and could not be automated, but that belief has changed. Over the past few years, automation has been adopted in many facets of the industry. Process and drilling automation was introduced in waves, in upstream oil and gas operations, with advances in automation increasing downhole drilling efficiencies and reducing safety incidents and flat time on the drill floor. With the introduction of these capabilities, companies can now measure, monitor, control and report the drilling process.
The next step was to move beyond the drill floor to automate power and engine management. Getting a handle on power and engine utilization would not only allow drilling contractors to cut fuel costs by better managing consumption, but also to reduce their carbon emissions. Achieving this level of automation is particularly significant, because it demonstrates the value of ongoing technology innovation that will lead in time to additional robotics capabilities and enable even greater operational efficiencies.
In recent years, some drilling contractors have begun to address power management, using manual methods, and have developed and introduced processes to enable drillers to take generators offline when they are not needed. Though these processes have helped to reduce fuel consumption and emissions, they require continuous human intervention. For manual processes to be effective, the driller has to continuously monitor engine usage, recognize when power generation exceeds what is required, and manually take an engine offline.
When executed correctly and appropriately, manual power management can achieve the goal of reducing fuel use and cutting emissions, but it adds another task to the driller’s workload. And irrespective of the driller’s competence and expertise, it is difficult to stay on top of power management, in addition to the many other functions that are being executed throughout the drilling process.
Drilling A.I. evolves. Today, several companies have developed automated power management solutions that are based solely on engine conditions, irrespective of what is occurring throughout the drilling process. These basic systems analyze engine conditions and trigger the addition of another power source when engine load increases pass a set threshold. When engine load drops below a set threshold, excessive power sources are automatically turned off.
While this methodology offers improvements over traditional drilling, it cannot deliver optimal power management efficiencies. And although some of these solutions are system-agnostic and can be installed to work with equipment from a range of manufacturers on most rigs, a majority are designed to work only with the provider’s equipment.
These systems clearly have taken the first critical steps toward full automation, but for power and engine management to be truly automated, there must be a way to consistently capture efficiencies across the board. That means being able to gather and process real-time data, allow for predictive drilling execution, dynamically manage power usage, track and calculate fuel consumption and efficiencies, and integrate seamlessly with any drilling package on any rig.
The A.I.-driven SmartPOWER system is a standalone solution that takes automation to the next level. The system takes a proactive approach to drilling and power management by harnessing A.I. to make power need predictions, such that the available power sources are aligned for fuel-efficient consumption. It is agnostic by design, which makes it a viable option for practically any rig. Figure 1 shows a Nabors Pace-X rig that has the capabilities to be retrofitted with SmartPOWER system along with other third-party rigs.
Effectively improving efficiency. The technology behind the system’s effectiveness is its ability to connect processes being automated in isolation into an integrated system. The system improves drilling performance by looking at a variety of real-time drilling data and predicting what is going to happen in the near term. Using EDR data coming from sensors throughout the rig, the system not only understands what the rig is doing but what it has been doing for the past five to 10 minutes.
Knowing how the rig performed historically and seeing how the rig is performing at present enables the system to consistently infer what lies ahead. With knowledge of the upcoming operations, the system determines the power needed to accomplish the tasks that will be conducted in the next 10 minutes. Figure 2 shows how the system reads the power level usage and optimizes it based on the task underway.
Because the system knows how much power will be required for the upcoming task, it can automatically bring the optimum number of generator sets online. The system prevents the use of unneeded energy sources during lower power-demand processes, while also eliminating the possibility of blackouts by precisely managing available power sources during high power-demand operations. Optimizing power usage at the appropriate times enables the reduction of fuel consumption and emission levels and maximizes engine output for more cost-effective, streamlined power management.
Automation allows drilling contractors to be less dependent on a master driller. By taking in performance data and analyzing the parameters, the system delivers the same quality results, irrespective of the experience level of the driller and shows how power is being used on the HMI screen. Figure 3 shows how a driller can monitor power usage without having to manually control the generator. Freed from the task of determining the optimal number of engines needed to meet anticipated power demands, rig personnel no longer need to focus on power management issues and can instead focus on higher-value tasks, allowing them to be more productive.
This system can be implemented in two ways. As described, it provides full autonomous control to start and stop engines. Alternatively, it can be used as an advisory tool. As the latter, the system applies A.I.-based decisions driven by real-time drilling data to continuously advise the driller on the optimal number of engines to run per task. Through HMI screen alerts, it provides drillers with recommendations on the correct number of power sources to have online throughout the drilling cycle. Unlike other systems that suggest actions to the driller, this automated system can execute while also giving the driller options to intervene in the process.
A.I. in action. Deployments on land rigs around the world illustrate the value that can be captured through automation, with results from automated drilling programs providing proof that the system consistently optimizes engine and power management across the drilling process, delivers quantifiable reductions in fuel consumption, and decreases engine operating hours to extend routine maintenance intervals.
In tripping operations, for example, the system constantly analyzes EDR data to know the bit depth (how deep the drill string is) and the total depth of the well. As tripping in operations continue, the bit depth readings increase until the bit approaches total depth. At this point, the system knows that the bit depth is approaching total depth and about to tag bottom and anticipates mud pumps will come online, top drive rotation and torque will increase, and the rig will begin a drilling operation. Using A.I., the system predicts the peak power requirements for the drilling operations being carried out and if needed, brings an additional available power source online to meet power demand.
Without A.I., it is virtually impossible to know exactly how much power the rig will need; so the driller has to decide what to do. The limitations of this approach are evident. Manual engine management relies on tribal knowledge and crew experience to understand how the rig is running, when an upcoming task will require more power, and what adjustments should be made to ensure power output will meet demand. Because this approach is imprecise, to be prepared for unforeseen power needs, it is necessary to always have all available power sources online. That means that often, engines are running when they are not needed for drilling operations. It is easy to see how this methodology results in extraneous power sources being online, producing unnecessary emissions and consuming excess fuel.
Employing the system on a drilling operation that runs all forms of available power, at all times, delivers significant savings of up to 15%. Even when the system is used on drilling operations where manual power management practices are implemented, drillers can realize a 4-9% reduction in fuel and emissions. On a recent drilling program in South Texas, a rig using SmartPOWER control has seen a 6% reduction in fuel consumption. Figure 4 summarizes the typical efficiencies drillers can achieved using this system.
Refining automation capabilities. Automating to optimize power management is proving its value and will be an enabler for onshore drilling contractors that are moving toward integrating batteries, dual-fuel engines and grid power for their AC rigs. To date, the system has been used exclusively onshore, but theoretically, it has the potential for offshore applications, which would significantly extend the economies and emissions reduction currently being realized in land-based drilling programs.
Although automation has been applied successfully in range of power usage scenarios and drilling environments, there are more improvements to be made. Development work already is underway to expand the system’s capabilities by adding an engine de-rating module to account for altitude, coolant temperature, oil condition, and filter condition. Forward-thinking engineers are continuing to improve and expand system performance to provide solutions as the industry’s power management needs evolve.
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