Speaker: David Kinney, Boeing
Boeing’s newest commercial aircraft, the 787 Dreamliner, has been described by airlines as “a flying node on the IT network.” In addition to incorporating the latest advances in aerodynamics and systems design, it brings significant advances in in-flight data collection and airplane-to-ground connectivity. However, Boeing is pioneering real-time decision making based on in-flight data reporting. Aircraft data analysis to support maintenance and operational decisions has been practiced for decades, with a rapid increase in real-time aspect of data collection and decision making in the past 10 years. This talk will overview the technology that Boeing provides to aircraft operators to enable them to remotely monitor the performance of their worldwide fleet, and how Boeing is using the data to improve products and services.
Session Managers: Gionata Ferroni, Thomas Halland, and Esra Inan
Abundant real-time data from remote locations around the world are readily available and accessible even on the go. It is, however, essential that decisions taken based on this data, consider the reliability of such information in terms of stability, quality, accuracy, relevance, and cost. If we consider the percentage of non-productive time and of unsuccessful wells, and compare ourselves with industries that have similar real-time data requirements, such as the stock exchange, travel, and banking, we have a long way to go.
This session will present a view on the current industry status through a series of case studies from both the operator and the service business point of view, including some of the challenges faced related to real-time data deliverables.
During breakout sessions the participants will be challenged to propose ideas and actions which will help bring our industry to the next level.
Session Managers: Simon Griffin and Oddbjørn Kvammen
Our industry is continually exploring new technologies to enhance our real-time decision making efforts. Often we fail to apply technology in such a manner that it becomes aligned with human factors and capabilities. For instance, today we can receive real-time data from downhole operations with a bandwidth similar to that of a regular computer network in our office. However, we are not able to turn data into valuable, real-time information.
In this session we will explore the following questions:
Session Managers: Nick Gibson and John James
The offshore drilling industry continues to automate key workflows and processes to address high rig-operating costs and HSE issues. In comparison, land-based drilling operations look to automation to standardise similar workflows within a low-cost, low-margin environment—where the operational experience and competence levels can vary. In either environment, the drive for drilling automation continues.
Despite the lower costs observed in land-based drilling operations, there is a strong push to deliver drilling automation. This is because these integrated operations are typically more accessible and lend themselves to proof-of concept, or pilot studies that extend into field wide automated drilling campaigns. For example, there are potentially significant savings to be achieved with the high density, standardised (“factory drilling”) well campaigns, which are often performed in remote and harsher environments, with their own fiscal limitations (e.g. coal bed methane or shale gas drilling operations).
The technical and fiscal challenges posed when drilling unconventional hydrocarbons, along with work in the arctic and other harsh environments, make the business case for new workflows and processes, such as those enabled by drilling automation, to deliver unparalleled results.
Session Managers: Alfio Malossi and Jennifer Market
The increasing complexity of wells, especially in deepwater environments, together with the related geological uncertainties, has increased the likelihood of unplanned drilling events, such as kicks, lost circulation, and borehole stability problems.
At the same time, there have been considerable advances in the quality and type of data available in real time—the challenge is how to effectively use this data. We must consider how the remote collaboration infrastructure and software chain should be set up to support the decision-making process and to mitigate or even avoid any issues related to pressure management and wellbore instability.
The new look-ahead and look-around sensors in addition to telemetry improvements imply that more complex data is transmitted to the surface—this gives us the potential to build up more powerful pore pressure prediction, wellbore stability models, and reliable reservoir characterisation. But are we ready to do that in real time yet?
This session aims to:
Session Managers: Greg Conran and Andy Deady
This session will review the themes and learnings in a bid to change future outcomes in real-time decision making.