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Total E&P UK PLC

Country: United Kingdom

Total E&P UK PLC

9 Projects, page 1 of 2
  • Funder: UK Research and Innovation Project Code: EP/R026173/1
    Funder Contribution: 14,635,600 GBP

    The international offshore energy industry currently faces the triple challenges of an oil price expected to remain less than $50 a barrel, significant expensive decommissioning commitments of old infrastructure (especially North Sea) and small margins on the traded commodity price per KWh of offshore renewable energy. Further, the offshore workforce is ageing as new generations of suitable graduates prefer not to work in hazardous places offshore. Operators therefore seek more cost effective, safe methods and business models for inspection, repair and maintenance of their topside and marine offshore infrastructure. Robotics and artificial intelligence are seen as key enablers in this regard as fewer staff offshore reduces cost, increases safety and workplace appeal. The long-term industry vision is thus for a completely autonomous offshore energy field, operated, inspected and maintained from the shore. The time is now right to further develop, integrate and de-risk these into certifiable evaluation prototypes because there is a pressing need to keep UK offshore oil and renewable energy fields economic, and to develop more productive and agile products and services that UK startups, SMEs and the supply chain can export internationally. This will maintain a key economic sector currently worth £40 billion and 440,000 jobs to the UK economy, and a supply chain adding a further £6 billion in exports of goods and services. The ORCA Hub is an ambitious initiative that brings together internationally leading experts from 5 UK universities with over 30 industry partners (>£17.5M investment). Led by the Edinburgh Centre of Robotics (HWU/UoE), in collaboration with Imperial College, Oxford and Liverpool Universities, this multi-disciplinary consortium brings its unique expertise in: Subsea (HWU), Ground (UoE, Oxf) and Aerial robotics (ICL); as well as human-machine interaction (HWU, UoE), innovative sensors for Non Destructive Evaluation and low-cost sensor networks (ICL, UoE); and asset management and certification (HWU, UoE, LIV). The Hub will provide game-changing, remote solutions using robotics and AI that are readily integratable with existing and future assets and sensors, and that can operate and interact safely in autonomous or semi-autonomous modes in complex and cluttered environments. We will develop robotics solutions enabling accurate mapping of, navigation around and interaction with offshore assets that support the deployment of sensors networks for asset monitoring. Human-machine systems will be able to co-operate with remotely located human operators through an intelligent interface that manages the cognitive load of users in these complex, high-risk situations. Robots and sensors will be integrated into a broad asset integrity information and planning platform that supports self-certification of the assets and robots.

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  • Funder: UK Research and Innovation Project Code: EP/W001136/1
    Funder Contribution: 1,915,360 GBP

    The international offshore energy industry is undergoing as revolution, adopting aggressive net-zero objectives and shifting rapidly towards large scale offshore wind energy production. This revolution cannot be done using 'business as usual' approaches in a competitive market with low margins. Further, the offshore workforce is ageing as new generations of suitable graduates prefer not to work in hazardous places offshore. Operators therefore seek more cost effective, safe methods and business models for inspection, repair and maintenance of their topside and marine offshore infrastructure. Robotics and artificial intelligence are seen as key enablers in this regard as fewer staff offshore reduces cost, increases safety and workplace appeal. The long-term industry vision is thus for a digitised offshore energy field, operated, inspected and maintained from the shore using robots, digital architectures and cloud based processes to realise this vision. In the last 3 years, we has made significant advances to bring robots closer to widespread adoption in the offshore domain, developing close ties with industrial actors across the sector. The recent pandemic has highlighted a widespread need for remote operations in many other industrial sectors. The ORCA Hub extension is a one year project from 5 UK leading universities with over 20 industry partners (>£2.6M investment) which aims at translating the research done into the first phase of the Hub into industry led use cases. Led by the Edinburgh Centre of Robotics (HWU/UoE), in collaboration with Imperial College, Oxford and Liverpool Universities, this multi-disciplinary consortium brings its unique expertise in: Subsea (HWU), Ground (UoE, Oxf) and Aerial robotics (ICL); as well as human-machine interaction (HWU, UoE), innovative sensors for Non Destructive Evaluation and low-cost sensor networks (ICL, UoE); and asset management and certification (HWU, UoE, LIV). The Hub will provide remote solutions using robotics and AI that are applicable across a wide range of industrial sectors and that can operate and interact safely in autonomous or semi-autonomous modes in complex and cluttered environments. We will develop robotics solutions enabling accurate mapping , navigation around and interaction with assets in the marine, aerial and ground environments that support the deployment of sensors for asset monitoring. This will be demonstrated using 4 industry led use cases developed in close collaboration with our industry partners and feeding directly into their technology roadmaps: Offshore Renewable Energy Subsea Inspection in collaboration with EDF, Wood, Fugro, OREC, Seebyte Ltd and Rovco; Aerial Inspection of Large Infrastructures in Challenging Conditions in collaboration with Barrnon, BP, Flyability, SLAMCore, Voliro and Helvetis; Robust Inspection and Manipulation in Hazardous Environments in collaboration with ARUP, Babcock, Chevron, EMR, Lafarge, Createc, Ross Robotics; Symbiotic Systems for Resilient Autonomous Missions in collaboration with TLB, Total Wood and the Lloyds Register. This will see the Hub breach into new sectors and demonstrate the potential of our technology on a wider scale.

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  • Funder: UK Research and Innovation Project Code: EP/F017448/1
    Funder Contribution: 235,485 GBP

    This proposal addresses the vital issue of prediction of multiphase flows in large diameter risers in off-shore hydrocarbon recovery. The riser is essentially a vertical or near-vertical pipe connecting the sea-bed collection pipe network (the flowlines) to a sea-surface installation, typically a floating receiving and processing vessel. In the early years of oil and gas exploration and production, the oil and gas companies selected the largest and most accessible off-shore fields to develop first. In these systems, the risers were relatively short and had modest diameters. However, as these fields are being depleted, the oil and gas companies are being forced to look further afield for replacement reserves capable of being developed economically. This, then, has led to increased interest in deeper waters, and harsher and more remote environments, most notably in the Gulf of Mexico, the Brazilian Campos basin, West of Shetlands and the Angolan Aptian basin. Many of the major deepwater developments are located in water depths exceeding 1km (e.g. Elf's Girassol at 1300m or Petrobras' Roncador at 1500-2000m). To transport the produced fluids in such systems with the available pressure driving forces has led naturally to the specification of risers of much greater diameter (typically 300 mm) than those used previously (typically 75 mm). Investments in such systems have been, and will continue to be, huge (around $35 billion up to 2005) with the riser systems accounting for around 20% of the costs. Prediction of the performance of the multiphase flow riser systems is of vital importance but, very unfortunately, available methods for such prediction are of doubtful validity. The main reason for this is that the available data and methods have been based on measurements on smaller diameter tubes (typically 25-75 mm) and on the interpretation of these measurements in terms of the flow patterns occurring in such tubes. These flow patterns are typically bubble, slug, churn and annular flows. The limited amount of data available shows that the flow patterns in larger tubes may be quite different and that, within a given flow pattern, the detailed phenomena may also be different. For instance, there are reasons to believe that slug flow of the normal type (with liquid slugs separated by Taylor bubbles of classical shape) may not exist in large pipes. Methods to predict such flows with confidence will be improved significantly by means of an integrated programme of work at three universities (Nottingham, Cranfield and Imperial College) which will involve both larger scale investigations as well as investigations into specific phenomena at a more intimate scale together with modelling studies. Large facilities at Nottingham and Cranfield will be used for experiments in which the phase distribution about the pipe cross section will be measured using novel instrumentation which can handle a range of fluids. The Cranfield tests will be at a very large diameter (250 mm) but will be confined to vertical, air/water studies with special emphasis on large bubbles behaviour. In contrast those at Nottingham will employ a slightly smaller pipe diameter (125 mm) but will use newly built facilities in which a variety of fluids can be employed to vary physical properties systematically and can utilise vertical and slightly inclined test pipes. The work to be carried out at Imperial College will be experimental and numerical. The former will focus on examining the spatio-temporal evolution of waves in churn and annular flows in annulus geometries; the latter will use interface-tracking methods to perform simulations of bubbles in two-phase flow and will also focus on the development of a computer code capable of predicting reliably the flow behaviour in large diameter pipes. This code will use as input the information distilled from the other work-packages regarding the various flow regimes along the pipe.

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  • Funder: UK Research and Innovation Project Code: EP/S023208/1
    Funder Contribution: 6,905,220 GBP

    Robots and autonomous systems (RAS) will revolutionise the world's economy and society for the foreseeable future, working for us, beside us and interacting with us. The UK urgently needs graduates with the technical skills and industry awareness to create an innovation pipeline from academic research to global markets. Key application areas include manufacturing, construction, transport, offshore energy, defence, and health and well-being. The recent Industrial Strategy Review set out four Grand Challenges that address the potential impact of RAS on the economy and society at large. Meeting these challenges requires the next generation of graduates to be trained in key enabling techniques and underpinning theories in RAS and AI and be able to work effectively in cross-disciplinary projects. The proposed overarching theme of the CDT-RAS can be characterised as 'safe interactions'. Firstly, robots must safely interact physically with environments, requiring compliant manipulation, active sensing, world modelling and planning. Secondly, robots must interact safely with people either in face-to-face natural dialogue or through advanced, multimodal interfaces. Thirdly, key to safe interactions is the ability for introspective condition monitoring, prognostics and health management. Finally, success in all these interactions depends on foundational interaction enablers such as techniques for vision and machine learning. The Edinburgh Centre for Robotics (ECR) combines Heriot-Watt University and the University of Edinburgh and has shown to be an effective venue for a CDT. ECR combines internationally leading science with an outstanding track record of exploitation, and world class infrastructure with approximately £100M in investment from government and industry including the National ROBOTARIUM. A critical mass of over 50 experienced supervisors cover the underpinning disciplines crucial to RAS safe interaction. With regards facilities, ECR is transformational in the range of robots and spaces that can be experimentally configured to study both the physical interaction through robot embodiment, as well as, in-field remote operations and human-robot teaming. This, combined with supportive staff and access to Project Partners, provides an integrated capability unique in the world for exploring collaborative interaction between humans, robots and their environments. The reputation of ECR is evidenced by the additional support garnered from 31 industry Project Partners, providing an additional 23 studentships and overall additional support of approximately £11M. The CDT-RAS training programme will align with and further develop the highly successful, well-established CDT-RAS four-year PhD programme, with taught courses on the underpinning theory and state of the art and research training, closely linked to career relevant skills in creativity, RI and innovation. The CDT-RAS will provide cohort-based training with three graduate hallmarks: i) advanced technical training with ii) a foundation international experience, and iii) innovation training. Students will develop an assessed learning portfolio, tailored to individual interests and needs, with access to industry and end-users as required. Recruitment efforts will focus on attracting cohorts of diverse, high calibre students, who have the hunger to learn. The single-city location of Edinburgh enables stimulating, cohort-wide activities that build commercial awareness, cross-disciplinary teamwork, public outreach, and ethical understanding, so that Centre graduates will be equipped to guide and benefit from the disruptions in technology and commerce. Our vision for the CDT-RAS is to build on the current success and ensure the CDT-RAS continues to be a major international force that can make a generational leap in the training of innovation-ready postgraduates, who will lead in the safe deployment of robotic and autonomous systems in the real world.

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  • Funder: UK Research and Innovation Project Code: EP/F016565/1
    Funder Contribution: 214,858 GBP

    This proposal addresses the vital issue of prediction of multiphase flows in large diameter risers in off-shore hydrocarbon recovery. The riser is essentially a vertical or near-vertical pipe connecting the sea-bed collection pipe network (the flowlines) to a sea-surface installation, typically a floating receiving and processing vessel. In the early years of oil and gas exploration and production, the oil and gas companies selected the largest and most accessible off-shore fields to develop first. In these systems, the risers were relatively short and had modest diameters. However, as these fields are being depleted, the oil and gas companies are being forced to look further afield for replacement reserves capable of being developed economically. This, then, has led to increased interest in deeper waters, and harsher and more remote environments, most notably in the Gulf of Mexico, the Brazilian Campos basin, West of Shetlands and the Angolan Aptian basin. Many of the major deepwater developments are located in water depths exceeding 1km (e.g. Elf's Girassol at 1300m or Petrobras' Roncador at 1500-2000m). To transport the produced fluids in such systems with the available pressure driving forces has led naturally to the specification of risers of much greater diameter (typically 300 mm) than those used previously (typically 75 mm). Investments in such systems have been, and will continue to be, huge (around $35 billion up to 2005) with the riser systems accounting for around 20% of the costs. Prediction of the performance of the multiphase flow riser systems is of vital importance but, very unfortunately, available methods for such prediction are of doubtful validity. The main reason for this is that the available data and methods have been based on measurements on smaller diameter tubes (typically 25-75 mm) and on the interpretation of these measurements in terms of the flow patterns occurring in such tubes. These flow patterns are typically bubble, slug, churn and annular flows. The limited amount of data available shows that the flow patterns in larger tubes may be quite different and that, within a given flow pattern, the detailed phenomena may also be different. For instance, there are reasons to believe that slug flow of the normal type (with liquid slugs separated by Taylor bubbles of classical shape) may not exist in large pipes. Methods to predict such flows with confidence will be improved significantly by means of an integrated programme of work at three universities (Nottingham, Cranfield and Imperial College) which will involve both larger scale investigations as well as investigations into specific phenomena at a more intimate scale together with modelling studies. Large facilities at Nottingham and Cranfield will be used for experiments in which the phase distribution about the pipe cross section will be measured using novel instrumentation which can handle a range of fluids. The Cranfield tests will be at a very large diameter (250 mm) but will be confined to vertical, air/water studies with special emphasis on large bubbles behaviour. In contrast those at Nottingham will employ a slightly smaller pipe diameter (125 mm) but will use newly built facilities in which a variety of fluids can be employed to vary physical properties systematically and can utilise vertical and slightly inclined test pipes. The work to be carried out at Imperial College will be experimental and numerical. The former will focus on examining the spatio-temporal evolution of waves in churn and annular flows in annulus geometries; the latter will use interface-tracking methods to perform simulations of bubbles in two-phase flow and will also focus on the development of a computer code capable of predicting reliably the flow behaviour in large diameter pipes. This code will use as input the information distilled from the other work-packages regarding the various flow regimes along the pipe.

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