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Goodkey, Brennan (Schlumberger Middle East) | Hernandez, Gerardo (Schlumberger Middle East) | Nunez, Andres (Schlumberger Middle East) | Corona, Mauricio (Schlumberger Middle East) | Atriby, Kamal (Schlumberger Middle East) | Rayes, Mohammed (Schlumberger Middle East) | Carvalho, Rafael (Schlumberger USA) | Herrera, Carlos (Schlumberger USA)
Over the past decade, breakthroughs in digital technology have rewarded a variety of industries with a step change in productivity and efficiency. Despite this, the drilling industry has yet to benefit on a large scale from these advances and a significant amount of value remains untapped. This paper details the effort of a service company to leverage modern technology by introducing a drilling automation system in pursuit of achieving a higher degree of consistency and efficiency.
The drilling automation system described in this case study was deployed in the Middle East on two onshore gas drilling rigs in 2019. The deployment was an opportunity to validate the potential of modern drilling automation technology and prove its ability to consistently deliver value. Since the company had extensive experience in the region, the Middle East was selected as the preferred location for field trials. This ensured that the value of automation could be precisely quantified as performance benchmarks were well documented and available for comparison. The automation strategy relied on an intelligent decision management system capable of dealing with constantly changing drilling conditions in order to implement efficient, consistent, and standardized well construction operations, while enhancing safety and reducing NPT. When given authority, the system would take control of the rig surface equipment to enable full automation of most drilling actions and engage optimization engines to monitor and adjust parameters to maximize performance. The system was leveraged to eliminate the variability innate to humans and deliver consistent results, while consolidating the improvements, performance gains, and lessons learned that otherwise would tend to disappear or erode over time or through personnel replacement.
Throughout this document, insight is provided into the technology itself, the deployment process, implementation challenges, the agile development model, and the results achieved. In addition, as the introduction of automation is a major departure from the traditional human operated drilling process, an emphasis will be placed on the results of the change management strategies utilized.
Goodkey, Brennanl (Schlumberger) | Carvalho, Rafael (Schlumberger) | Nunez Davila, Andres (Schlumberger) | Hernandez, Gerardo (Schlumberger) | Corona, Mauricio (Schlumberger) | Atriby, Kamal (Schlumberger) | Herrera, Carlos (Schlumberger)
Abstract As margins tighten, players in the modern O&G landscape are being forced to reimagine their business models and re-evaluate their strategic direction to maintain a competitive edge. This often means doing more with less and spreading ever slimmer margins across increasingly complex well operations. Fortunately, with the wave of digital innovations that are sweeping the industry, most E&P organizations have a wealth of opportunities to streamline activity and increase efficiency while reducing the resources required. However, with the increasing array of digital opportunities, the gauntlet is set: those who adopt quickly and reap early benefits will undoubtedly be tomorrow's leaders. Laggards slow to adapt will fall progressively further behind as leaders successfully navigate through the learning phase and accelerate into new standards of efficiency. This combination of urgency and opportunity will undoubtedly be the force that propels the industry into the fourth great revolution; digital transformation. As observed in a variety of industries, automation has proven to be one of these instrumental digital levers to unlocking the next level of efficiency. Across the O&G industry, we are beginning to see a number of applications in which tasks are not only becoming less labor-intensive but also faster, safer and with increased levels of precision. This ensures that repetitive tasks which often drain and distract workers are re-allocated to automated processes while ensuring that employees remain concentrated on prioritizing safety and operations integrity. The value proposition for automation in drilling is especially compelling as human operators can easily become overwhelmed with the volume of competing priorities and the pressure to make immediate decisions. By carefully delegating some of the decision-making to an intelligent drilling system, the cognitive burden on human operators is reduced resulting in a safer working environment conducive to increased performance and engagement. In this paper, a detailed case study is presented to document the effort of a major service company to deploy a full drilling automation system in the Middle East implemented to autonomously operate rig surface equipment. A detailed description of the system's intelligent management system will be provided to communicate its capacity to interpret and autonomously respond to changing well conditions. A case study approach will be used in attempt to specifically identify the areas where automation delivers a step change in results compared to manual operations. Additionally, given the complexity inherent to executing a digitalization project in drilling, insight will be shared on the strategies leveraged to navigate the intricacies of deployment and adoption. Throughout this paper, it will become evident that automation is quickly becoming a reliable solution for the consistent delivery of top quartile performance by unlocking new levels of consistency and procedural adherence.
Abstract This paper describes a collaborative effort between an operator, a drilling contractor and a service company to introduce specific aspects of automated technology to a major drilling operation. The application of automated technologies to the process of well construction is emerging as a key lever to improve the overall efficiency of drilling performance. Though not yet mainstream, several recent applications have demonstrated that the technology maturity is no longer the limiting factor in accelerating the uptake and realizing the benefits that automation can bring to drilling. A major challenge that has emerged in implementing drilling automation is the fragmented and often non-symbiotic business model that exists between key stakeholders. Additionally challenges exist around the lack of inter-operability between various parties' specific hardware and software. This issue extends to the multiple data streams involved, the data's robustness and how to integrate these adequately to drive automated processes. As with any technology introduction, new complications appear and this is no different for implementing automation technologies in drilling. Among the many new challenges are the increased cyber-security risks introduced by exposing the drilling control system to external networks, as well as the human factors challenges associated with changing well established workflows on the rig floor. The sum of these is to manifest itself in improved drilling performance without compromising on the safe operation of the rig. In this particular case, the discussion centers on the application of automation to drilling parameter control as it relates to improving the rate of penetration in hard rock drilling environments. Successful implementation of automation technologies in drilling is a significantly complex endeavor, and the measures of success may not be immediately apparent. Instead, a vision that encapsulates a longer term, strategic view on the potential benefits that automation can bring to well construction is required, with shorter term tactical milestones being well defined, and a systematic plan engaged to achieve them. The paper explores how the above issues were managed over a testing and implementation period of approximately three years covering the transition from an advisory mode system to an automated one. Automated process control applications on drilling rigs will continue to increase in both the number of deployments as well as the breadth of functions covered. The project described illustrates one approach that is unique to date in terms of the technology and the degree of collaboration employed by the stakeholders to successfully deliver the objectives. Early adoption initiatives as discussed here are essential for the technology to evolve. They provide the industry with a series of lessons that help to sustain and direct the future of drilling automation and its role in enhancing well construction capabilities.
Abstract This paper presents a case history of drilling automation system pilot deployment, inclusive of wired drill pipe on an Arctic drilling operation. This builds on the body of work that BP (the operator) previously presented in 2017 related to the deployment of an alternate drilling automation system. The focus will be on the challenges and lessons learned during this deployment over a series of development wells. Two major aspects of technology were introduced during this pilot, the first being a drilling automation software platform that allowed secure access to the rig's drilling control system. This platform hosts applications that interpret the activity on the rig and issue control setpoints to drive the operation of the rig's top drive, mud pumps, auto driller, drawworks, and slips. The second component introduced was a wired drill string, which provides access to high speed delivery of downhole data from a series of distributed downhole sensors, providing an opportunity to improve both automated control and real-time interpretation of downhole phenomena. The project team identified several key performance indicators both at the project level and for each well. The project level key performance indicators (KPIs) were designed to give the operator an understanding of the reliability and robustness of the hardware and software components of the automation system. The KPIs for the well were designed to assess the impact of the technology on drilling efficiency through aspects of invisible lost time reduction (connection and survey times). The well level KPIs also fed into the project KPIs by capturing uptime, reliability, and repeatability of the hardware and software components of the system. The paper describes several specific examples of where the benefits of the technology were realized as related to the KPIs above and describes some of the technical challenges encountered and fixes employed during the pilot campaign. The paper also gives an insight into some of the non-technical challenges related to deployment of this system, around human behavioral characteristics. It discusses how focused collaboration and communication from all the stakeholders was managed and directed towards a successful deployment. The work delivered on this project incorporates several technological innovations that were deployed for the first time on an active drilling operation. Delivery of these were important milestones for both the operator and the automation technology provider as part of their collaboration to increase the capability and reliability of these systems. The operator believes that this effort is key to allowing its drilling operations to realize longer term and sustainable benefits from automation.
Abstract The paper provides a technical overview of an operator's Real-Time Drilling (RTD) ecosystem currently developed and deployed to all US Onshore and Deepwater Gulf of Mexico rigs. It also shares best practices with the industry through the journey of building the RTD solution: first designing and building the initial analytics system, then addressing significant challenges the system faces (these challenges should be common in drilling industry, especially for operators), next enhancing the system from lessons learned, and lastly, finalizing a fully integrated and functional ecosystem to provide a one-stop solution to end users. The RTD ecosystem consists of four subsystems as shown in architecture Figure 1. (I) The StreamBase RTD streaming system, which is the backbone of the ecosystem. It takes the real-time streaming log data as well as other contextual well data (for example, OpenWells), processes it through analytical models, generates results, and delivers them to the web-based user interface; (II) The analytics models, which include the Machine Learning (ML)/Deep Learning (DL) models, the physics-based models and the stream analytical/statistical models; (III) The digital transformation solution, which wasdesigned to address contextual well data digitization issues to enable real-time physics-based modeling. Contextual well data like bottom hole assemblies (BHAs) and casing programs are challenging to aggregate and deliver to models, as this data is often stored in locations across multiple systems and in various formats. The digital transformation applications are designed to fit into the drilling teams' workflows and collect this information during the course of normal engineering processes, enhancing both the engineering workflow and the data collection process; (IV) the cloud based ML pipeline, which streamlines the original ML workflows, as well as establishes an anomaly detection and re-training mechanism for ML models in production. Figure 1: RTD ecosystem architecture All of these subsystems are fully integrated and interact with each other to function as one system, providing a one-stop solution for real-time drilling optimization and monitoring. This RTD ecosystem has become a powerful decision support tool for the drilling operations team. While it was a significant effort, the long term operational and engineering benefits to operators designing such a real-time drilling analytics ecosystem far outweighs the cost and provides a solid foundation to continue pushing the historical limitations of drilling workflow and operational efficiency during this period of rapid digital transformation in the industry.