Drilling automation promises to reduce costs, increase safety margins, and improve the overall efficiency of drilling operations whilst maintaining a high-quality wellbore. However, realizing this vision necessitates that components which acquire, process, provide intelligence for "situational awareness," and automatically execute instructions, share complete information. Effective decision support capabilities and the automated control of the drilling process can only occur with seamless communication based on standards that provide interoperability through an event-driven architecture. Many standards already exist in both the oil and gas and other manufacturing process industries. Yet, the lack of adoption of these standards and best practices is predominantly due to the fear of intellectual property being compromised. We have witnessed through message-based standards the mobile handheld market's unprecedented proliferation of applications that will automate just about anything for your PDA (think Apple Inc.'s "There's an app for that"). Independent software vendors provide solutions that work seamlessly to interconnect business processes and other software systems enabled by the standards developed and adopted as a result of the Internet and the service-oriented architecture (SOA) movement. Key to this development has been the protection of individuals' intellectual property through the encapsulation of processing and control logic. Harvesting innovation from these next-generation solution developers requires standardized messaging architectures and communication protocols. This paper will examine several industry segments to highlight how standardization at the level of interconnectivity has affected both their interoperability and innovation. Business models that promote and reward open innovation will ultimately drive solutions for automation. But interoperability will drive more than just automation; it is the key to shattering the myth around service complexity. Protecting intellectual property (IP) requires encapsulation of process and control logic and the adoption of appropriate interface standards. Standards enable the prospect of greater interoperability, reduce system complexity through modular packaging, and drive innovation.

Recent events and studies show that wellbore stability and geopressure events continue to plague the oil industry with issues that affect the safety of people and the environment. In addition, events such as kicks and lost circulation also create significant loss of time and productivity, commonly referred to as non-productive time (NPT). Deepwater studies have shown NPT related to kicks, and lost circulation can amount to 4.5% of the total well construction time. Consequently, early kick and lost circulation detection is crucial to eliminating detrimental effects on human and environmental safety, in addition to minimizing NPT.Kicks frequently happen during connections, and flowback fingerprint monitoring has been used for more than a decade across the industry to aid in kick detection. However, setting alarm thresholds and identifying abnormal flowbacks has been a manual process that relies heavily on the experience and intuition of the engineer who performs this critical safety monitoring. This manual process frequently misses early signs of influx, and thus greatly increases the well remediation time .This publication focuses on the development and deployment of an automated flowback monitoring technology. The new solution aids drillers and drilling engineers by generating intelligent alarms relevant to current well conditions for early kick and loss detection, which can result in detecting kicks up to one connection earlier than the existing manual method. This paper demonstrates the benefits of Smart Flowback Fingerprinting over existing practices and how it can significantly reduce safety risks and NPT.

Drilling automation is the control of the drilling process by automatic means, ultimately reducing human intervention to a minimum. The concept of automating the drilling process has generated considerable interest, yet there is a lack of agreement on exactly what it is, what it entails, and how to implement it. As with industrial automation in the 1990s, the adoption of open standards enabling automation will have a significant impact on the underlying business model. In the oilfield drilling industry, the business model describes the relationship between operator, drilling contractor, service company, and equipment supplier.The goal of drilling systems automation is to increase productivity and quality, improve personnel safety, and effectively manage risk. Principal drivers of drilling automation include well complexity, data overload, efficiency, repetitive well manufacturing, access to limited expert resources, knowledge transfer due to the exodus of skilled employees, and health, safety and environmental concerns. With so many drivers, and their potential economic benefits, it is understandable that there are many automation related initiatives within the industry.Drilling through geopressured, possibly erratic lithologies, to a remote and possibly poorly defined target in a safe manner is not a simple task to automate. It is challenging. Drilling automation focuses on the drilling system and drilling operations, which entail combining various sub-systems, including the downhole BHA and its measurement and active components, the drillstring, fluid, and drilling rig and its sub-assemblies. Operations include conventional overbalanced, managed pressure, and underbalanced drilling operations, and their various procedures, such as tripping and making connections. This paper examines and defines drilling systems automation, its drivers, enablers and barriers, and its current state and goals. In particular, the paper looks at the vision of drilling systems automation, and the role played by open collaborative initiatives among all segments of the drilling industry. Although commitment to automation by the drilling industry appears by many to lag other major industries, there are segments of the drilling industry that have reached a high level of automation on a commercial basis. There is also significant collaboration among interested parties in creating a standardized, open environment for data flow to foster the development of systems automation.

Although the oil and gas industry continues to progress with drilling automation, technical challenges remain and must be addressed before this vision can become a reality. One of these challenges is the data aggregation between operators, service companies, drilling contractors and equipment manufacturers. Automation requires that the system not only control sub processes, it must also enable more complex intelligent systems to plan and react to real-time evaluation criteria and respond to predictive intelligence in real time. Data from control systems such as top drives, and evaluation systems such as downhole logging while drilling (LWD) sensors, must be aggregated in a meaningful way so it is portable, contextual, and actionable. Consider controlling the rate of penetration (ROP) based on predictive analytics assessed from formation evaluation (FE) data provided by an LWD sensor. To achieve this, intelligent control and evaluation systems must monitor and exchange information and events within a single, shared perspective.In this paper, we review several technologies currently in use throughout the drilling industry-WITS, WITSML, OPC and PROFIBUS-and present case studies describing the current roles these technologies play and the problems they solve. The authors then analyze the limitations between these interoperable systems and associated barriers in achieving the drilling automation vision. This paper recommends defined goals for the data aggregator and identifies existing challenges surrounding its deployment in current drilling automation environments. The authors also provide recommendations for how the industry should proceed with the implementation of data aggregation for automation. These recommendations ensure drilling automation becomes more than simple process mechanization, but advances towards intelligent systems that transform plans into reality and optimize performance and cost.

Drilling automation is the control of the drilling process by automatic means, ultimately reducing human intervention to a minimum. The concept of automating the drilling process has generated considerable interest, yet there is a lack of agreement on exactly what it is, what it entails, and how to implement it. As with industrial automation in the 1990s, the adoption of open standards enabling automation will have a significant impact on the underlying business model. In the oilfield-drilling industry, the business model describes the relationship between operator, drilling contractor, service company, and equipment supplier.The goal of drilling-systems automation is to increase productivity and quality, improve personnel safety, and effectively manage risk. Principal drivers of drilling automation include well complexity, data overload, efficiency, repetitive well manufacturing, access to limited expert resources, knowledge transfer as a result of the exodus of skilled employees, and health, safety, and environmental concerns. With so many drivers, and their potential economic benefits, it is understandable that there are many automation-related initiatives within the industry.Drilling through geopressured, possibly erratic, lithologies to a remote and possibly poorly defined target in a safe manner is not a simple task to automate. It is challenging. Drilling automation focuses on the drilling system and drilling operations, which entail combining various subsystems, including the downhole bottomhole assembly (BHA) and its measurement and active components, the drillstring, fluid, and drilling rig and its subassemblies. Operations include conventional overbalanced-, managed-pressure-, and underbalanced-drilling operations, and their various procedures, such as tripping and making connections. This paper examines and defines drilling-systems automation, its drivers, enablers and barriers, and its current state and goals. In particular, the paper looks at the vision of drilling-systems automation, and the role played by open, collaborative initiatives among all segments of the drilling industry. Although commitment to automation by the drilling industry appears by many to lag behind the level of commitment in other major industries, there are segments of the drilling industry that have reached a high level of automation on a commercial basis. There is also significant collaboration among interested parties in creating a standardized, open environment for data flow to foster the development of systems automation.