A Standard Real-Time Information Architecture for Drilling and Completions

Abstract

BP is looking to implement a standard data architecture for real-time drilling & completions information. This will enable us to make wider use of our collaboration centres through a common approach and will allow us to leverage the developing WITSML standard more effectively in our operations. BP uses many different service organisations to deliver its global drilling & completions agenda. In the past, this has resulted in a lack of standardisation in real-time information flow. We have been unable to share data and expertise readily between different operating centres. Applying a common approach to information access on a global basis will enable us to streamline our operations and make wider use of emerging collaboration technologies. WITSML is now finding greater uptake in our industry and we are seeing new compliant intelligent software tools emerging from different vendors. These will undoubtedly enable us to drill and complete smarter but we need a standard information infrastructure to deploy them widely and consistently. It is these smart tools that will ultimately deliver real value to oil companies. The adoption of a standard D&C information architecture may seem an obvious step but there are very few oil companies that can claim to have delivered it. WITSML is the vehicle to allow this to happen and over the next few years it is likely that there will be much more emphasis on open connectivity between different vendors and services supporting the drilling & completions functions. 1. Introduction The rapid development of digital technology is touching all disciplines in the oil industry and is providing exciting new opportunities and capabilities in areas such as automation, remote monitoring, simulation and enhanced visualisation. In terms of capital employed in digital technology, there can be few functional areas that have the potential to deliver a higher return on investment than drilling and completions due to the sheer magnitude of today's operational costs. A saving of at least a few percent in non-productive time should be readily achievable for most oilfield operators and service companies with more effective use of real-time data to improve operational efficiency and the productivity of scarce, highly qualified discipline specialists. Data capture from drilling rigs has for a long time been the responsibility of the service contractors (typically the MWD/LWD contractors). Their task has been to monitor information real-time on the rig and increasingly at remote onshore data centres. The oil company has generally had the option to have a real-time WITSML feed from the service contractors' data centres and has been able to monitor offshore operations using a proprietary real-time viewer. Typically, at the end of the drilling and completions operation, the oil company is supplied with an archive of the real-time information on a portable media such as tape or CD-ROM. How effectively this information is then used varies widely across the industry. When this approach was first introduced, it was excellent as it represented a significant step forwards from paper logs and other manually gathered data. However, with the expansion of the digital world, the demand for information has grown significantly and a number of opportunities now exist to make better use of real-time information:-Remote operation and support at oil company collaboration centres.Smart algorithms to improve operational efficiency.A greater desire to capture lessons learned and to influence future operations.Integration of all data sources from the rig including MWD/LWD, weather, anchor, positional, etc.

Real-Time Drilling Operations Centers: A History of Functionality and Organizational Purpose—The Second Generation

“…A foundational aspect of BP's strategy for drilling is covered by Pickering et al (2007) who describe "a standard real-time information architecture for drilling and completions." This is evidence of the maturing of the WITSML standard and a move toward more operator ownership of the architecture to reduce reliance on vendor-developed implementations of WITSML, with vendor-specific components.…”

“…The resulting architecture may largely comprise vendor products, but overall design and evolution are owned by the operator. Statoil (Deeks and Halland 2008), BP (Pickering et al 2007(Pickering et al , 2009Sawaryn et al 2009), and Saudi Aramco (Khudiri et al 2009) appear to be assuming more ownership and control of internal real-time data architectures. This second wave of adoption of WITSML also refl ects the maturing of the standard itself to a point at which it is capable of implementing higher-level processes.…”

Real-Time Drilling Operations Centers: A History of Functionality and Organizational Purpose—The Second Generation

“…The paper represents a more holistic approach to managing change across these five areas when developing and implementing ACE opportunities. A foundational aspect of BP's strategy for drilling is covered by Pickering et al (2007) who describe "A Standard Real-Time Information Architecture for Drilling and Completions". This is evidence of the maturing of the WITSML standard and a move toward more operator ownership of the architecture to reduce reliance on vendor developed implementations of WITSML, with vendor-specific components.…”

“…The resulting architecture may be comprised largely of vendor products, but overall design and evolution are owned by the operator. Statoil (Deeks et al, 2009), BP (Pickering et al, 2007, Sawaryn et al, 2009) and Saudi Aramco (Khudiri et al, 2009) appear to be assuming more ownership and control of internal real-time data architectures. This second wave of adoption of WITSML also reflects the maturing of the standard itself to where it is capable of implementing higher level processes.…”

Applying Simultaneous Variable Control Strategies for ROP Optimization and Offshore Well Costs Mitigation

“…Al (2008). Al (2009), Rajaieyamchee and Bratvold (2009) and Lyadina-Saville (2009 discuss drilling performance optimization and NPT reduction based on real time data coupled with different statistical and artificial intelligence strategies. Al (2009), Rajaieyamchee and Bratvold (2009) and Lyadina-Saville (2009 discuss drilling performance optimization and NPT reduction based on real time data coupled with different statistical and artificial intelligence strategies.…”