Operators can now use the latest machine learning and analytics tools to reduce the costs and complexities of drilling operations while improving each asset’s performance. In planning stages, advanced tools help operators find ideal drilling spots and create detailed pore pressure models. And when drilling is underway, autonomous machinery and data-driven drill optimisation improves safety and cost-efficiency.
Real-time drill analytics
This system optimises the drilling plan by updating geological models in real time. While drilling is in progress, the system measures forces acting over the drill string, the appearance of vibrations, static pressures and dynamics inside the drill string. It then transmits data to the drill operator, helping to identify higher ore concentrations. Measurements with the system can take around four minutes, compared to one-to-two hours with traditional technology. Benefits include decreased drilling costs and a reduced need to have geologists present, plus increased production rate and overall recovery.
Time saved compared to traditional directional measurements
IoT-enabled drill technology
This IoT-enabled advanced analytics solution uses well field data to improve drilling performance and optimise speed to production.The technology uses IoT-enabled advanced analytics from sensors deployed across well fields to collect data on everything from rates of penetration to RPM on the drill floor. This real-time drilling data is then visualised on a single dashboard. Based on this data, the system automatically adjusts the weight placed on a drill bit as well as its speed, in order to optimise the timeline to production.
Decrease in time taken for new well drilling
Automated handling of pipes and casing
This system automates the handling and racking of pipes and casing. Operators use a simple control unit to activate the machinery, which picks up individual pipes and moves them to specific locations on the drill floor. With the ability to carry pipes both vertically and horizontally, the machinery can handle a huge variety of offshore drill pipes, drill racks and casings of any size, and can also be manually controlled when needed. This means that fewer people are needed on the drill floor, which improves safety. Automation also adds greater speed, precision and efficiency to the process.
Speed in increase in casing running
Digital drilling tool to reduce capex
This machine learning technology is designed to increase drilling performance and safety conditions at oil and gas facilities, while reducing capex. Through real-time data gathering and analysis, the digital drilling tool provides oil and gas companies with actionable insights into their drill rigs’ operations. Using the digital tool drives down drilling costs, which make up a significant proportion of upstream capex activities.
Advanced analytics to optimise drilling
This advanced analytics solution enables drilling operators to maximise productive work time. Using machine learning, it advises operators on daily risks and performance optimisation opportunities, improving their understanding of their wells and operations. Its built-in machine learning models can predict well problems including circulation losses, fluid influx, stuck pipe and borehole instability. This can lead to increased productivity and a dramatic reduction in blow-out risk. It also acts as a single source of truth for drilling and completion engineers interacting between the well site and the office.
Digital twin for drilling
This drilling digital twin creates virtual models of a well that can be used for well preparation, automated monitoring and real-time optimisation. The technology features two high-fidelity simulators that accurately model real-life scenarios using engineering data, sensors, and life cycle information. These simulations can uncover new opportunities for optimisation so the operator can improve workflows and specific operations throughout the asset’s life cycle. Benefits include increased output, reduced costs, and improved health and safety.
Reduction in drilling costs
Subsurface pressure model to aid drilling
This tool is designed to build detailed pore pressure models for geoscience teams. Integrating disparate seismic and well data, the tool then applies AI techniques to build pore pressure models and create helpful visualisations. This results in reliable pore pressure data which provides greater clarity on the way data is analysed and presented. Subsurface teams can use this to inform real-time decisions around drilling operations and provide an enhanced level of support.
Potential saving per year
Increased drilling rate
Our team has decades of collective experience, spanning all areas of industrial operations.
Dr Nick Mayhew
Chief Commercial Officer
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