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Today's oil and gas industry is a global endeavor. With technological advances in data management and transfer, the ability for experienced engineers to receive, interpret, and make decisions from all over the globe in near real-time is not only achievable, but is becoming more desirable. Provoked by downturns and reduced personnel numbers, methods of increasing efficiency and cost reduction has gradually moved engineers away from the rig site, while still undertaking the same roles and responsibilities. This paper examines one case for an operator in the Caribbean. One major client drilling in the Caribbean was forced to explore reduced staffing options on one of its deep-water drilling rigs after flight cancellations, border closures, and isolation/quarantine procedures were implemented due to the COVID-19 pandemic. This made getting experienced data engineers and sample collection personnel to the rig site impossible. Two data engineers, two mud loggers, and two sample catchers are on the rig during normal operations, but with the above-mentioned challenges, only two mud loggers remained on site. The mudlogging service provider proposed intercompany collaboration with a region experienced in remote operational support, and a remote monitoring station was set up and manned with experienced data engineers to support real-time operations. A focal point between the remote engineers and the rig team was designated, and was responsible for communicating roles and responsibilities, linking the two teams. A robust communication protocol was established between the mudlogging crew, the remote personnel, the drill floor, and the company man which outlined specifics of which events would trigger communication between parties. Two intermediate hole sections were successfully drilled, without any interruption or delay. The remote engineers successfully participated in the rigs well control drills, calling directly to the rig when needed. During drilling, the experienced remote personnel were able to provide topic specific guidance to the less experienced engineers at the rig site, which accelerated their on-the-job training. This guidance encouraged and allowed for decreased reliance on the remote support over the course of drilling. The operator considered the implementation of the remote engineers a success and looked to implement additional remote resources from other service lines and providers. Development of additional remote support opportunities directly reduces risk and cost of personnel at the rig site throughout all aspects of the oil and gas industry. Reduction of personnel on site reduces overall exposure to the hazards associated with the rig site and would decrease the probability of incident. Recent improvements in technology and communication have made it possible for this to be a viable solution to de-manning the rig site in an evolving industry.
Today's oil and gas industry is a global endeavor. With technological advances in data management and transfer, the ability for experienced engineers to receive, interpret, and make decisions from all over the globe in near real-time is not only achievable, but is becoming more desirable. Provoked by downturns and reduced personnel numbers, methods of increasing efficiency and cost reduction has gradually moved engineers away from the rig site, while still undertaking the same roles and responsibilities. This paper examines one case for an operator in the Caribbean. One major client drilling in the Caribbean was forced to explore reduced staffing options on one of its deep-water drilling rigs after flight cancellations, border closures, and isolation/quarantine procedures were implemented due to the COVID-19 pandemic. This made getting experienced data engineers and sample collection personnel to the rig site impossible. Two data engineers, two mud loggers, and two sample catchers are on the rig during normal operations, but with the above-mentioned challenges, only two mud loggers remained on site. The mudlogging service provider proposed intercompany collaboration with a region experienced in remote operational support, and a remote monitoring station was set up and manned with experienced data engineers to support real-time operations. A focal point between the remote engineers and the rig team was designated, and was responsible for communicating roles and responsibilities, linking the two teams. A robust communication protocol was established between the mudlogging crew, the remote personnel, the drill floor, and the company man which outlined specifics of which events would trigger communication between parties. Two intermediate hole sections were successfully drilled, without any interruption or delay. The remote engineers successfully participated in the rigs well control drills, calling directly to the rig when needed. During drilling, the experienced remote personnel were able to provide topic specific guidance to the less experienced engineers at the rig site, which accelerated their on-the-job training. This guidance encouraged and allowed for decreased reliance on the remote support over the course of drilling. The operator considered the implementation of the remote engineers a success and looked to implement additional remote resources from other service lines and providers. Development of additional remote support opportunities directly reduces risk and cost of personnel at the rig site throughout all aspects of the oil and gas industry. Reduction of personnel on site reduces overall exposure to the hazards associated with the rig site and would decrease the probability of incident. Recent improvements in technology and communication have made it possible for this to be a viable solution to de-manning the rig site in an evolving industry.
The North Sea has always been a pioneer for the adoption of remote operations services (ROS) in offshore drilling applications. Drilling services such as Measurement While Drilling (MWD), Logging While Drilling (LWD) and/or mud logging (ML) have been performed with an element of ROS for over the last two decades. Early adoption of these remote services delivered initial benefits to operators such as reducing HSE risks related to the travel and accommodation of field service employees at offshore rig sites. Meanwhile service companies were able to explore the added efficiencies gained by having multi-skilled employees providing a higher level of support to customers while also gaining additional agility to manage their personnel through tighter market cycles. The mutual benefit of this early adoption created a solid foundation for ROS to expand the scope of influence in drilling operations to include Directional Drilling (DD). Despite the maturity of ROS within a select community of operators in the North Sea, the industry standard for service delivery in offshore operations has continued to require field service employees to perform DD, MWD, and LWD services at rig sites until this past year. With the COVID-19 pandemic in 2020, operators and service companies were quickly and abruptly confronted with the challenges of new HSE regulations, travel restrictions, and increased financial scrutiny. ROS presented a tailored solution to not only sustain business continuity but also create added efficiency, consistency, and risk management. Over the course of 2020, adoption of ROS rapidly accelerated across offshore operations in the North Sea and reached up to 100% penetration in key sectors. This tremendous achievement has made a significant impact on project performance and HSE efficiencies by ensuring on time service delivery while reducing personnel on board (POB). In addition, as more operators and services companies explore ways of reducing their carbon footprints and achieving a net zero future, ROS has proven to be a way to significantly reduce carbon emissions associated with transportation and utilities of offshore personnel. This paper discusses the methods that enabled a record high adoption rate for ROS and explores the critical components of its success. It illustrates the management of change in service delivery processes, the introduction of new technology to unlock greater productivity and synergies, and the new approach to design the core competencies needed to support ROS. It also describes the need for flexible ROS service models to meet the specific project needs of various operators. The paper concludes with the numerous benefits realized through ROS such as improved performance and consistently reliable service delivery. The paper also examines the resulting carbon emission reduction, how to quantify it, and the role ROS plays in achieving a net zero emissions future.
Automation of well construction combines process and machine automation to deliver cost savings and efficiency gains, alongside safer operations and faster collaborative decision making. Integration of well planning and execution improves performance, minimizes risk, and creates the framework for batch control of well construction. Generating intuitive and standardized insights from historical and live data streams enables reducing uncertainty and driving technical limit performance at every stage, for the safest and most economical well delivery possible. Remote operations have become standard practice in well construction and drilling automation is rapidly growing. Machine-learning based models can predict hazards and best operating parameters. The paper describes how these elements are combined to easily analyze offset well data from multiple sources for performance benchmarking, deep technical analysis, and risk management. Integration with physics-based models (the digital-twin) establishes a coherent execution roadmap, a real-time digital recipe that is directly used in rigsite automation. During execution, model assumptions are replaced by live sensor data. Those models are then re-calculated in real-time for automated process control and become available for future planning. The viability of integrated well planning and automation systems is no longer disputed, and industry focus has shifted towards proving the potential of this approach. Pertinent case examples from drilling operations are examined in the paper, including optimizing performance through harnessing analytics of large data sets from offset wells, and on exploring the integration of AI techniques for risk prediction and mitigation. The insights gained, coupled with the digital well plan, are instrumental for optimization and automation of tripping equipment in and out of hole, and of drilling ahead operations. Integrating the digital well plan with "lessons learned" from the analysis of all available data and using a digital-twin concept with physics-based and data driven models, provides the foundation for the next step in process automation: the creation of digital procedures for process automation of well construction. This capability extends the cost savings and efficiency gains realized in recent years through remote operations.
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