{"id":93769,"date":"2024-10-25T07:14:23","date_gmt":"2024-10-25T07:14:23","guid":{"rendered":"https:\/\/expleo.com\/global\/en\/?post_type=insights&p=93769"},"modified":"2026-03-31T07:51:24","modified_gmt":"2026-03-31T07:51:24","slug":"digital-twins-energy-transition","status":"publish","type":"insights","link":"https:\/\/expleo.com\/global\/en\/insights\/blog\/digital-twins-energy-transition\/","title":{"rendered":"Supporting the energy transition: how digital twins can overcome oil and gas industry challenges"},"content":{"rendered":"\t\t
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As companies within the industry continue their transition journey from hydrocarbons to renewables-first, digital twins <\/span>emerge<\/span> as a useful technology. In <\/span>Expleo\u2019s<\/span> recent report, <\/span><\/span>Transitioning to <\/span>r<\/span>enewables at <\/span>s<\/span>cale<\/span><\/span><\/a>, this journey is outlined with an emphasis on laying a robust digital foundation.<\/span><\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Digital twins build on this foundation and enable the detailed monitoring, analysis and control of physical assets throughout their lifecycle, from conception and design through to production, operation and recycling.<\/span>\u00a0<\/span><\/p>

A <\/span>digital twin<\/span><\/a> is any type of representation of a physical asset, process or system. It may be a photorealistic simulation, driven by data from sensors and governed by real-world or simulated principles, or a simple 3D model. Digital twins can incorporate, synthesise and contextualise sensor data, real-world simulations, AI and machine learning data, Computer-Aided Design (CAD) and other design information. They excel at overcoming challenges around efficiency, sustainability and competitiveness in the oil and gas industry landscape.<\/span><\/p>

Here, <\/span>Ketan Kothari<\/a>, Sales Manager \u2013 E&U at Expleo<\/strong>,<\/strong> highlights a few of the challenges that digital twins are helping to overcome in the industry today.<\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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1. Physical and process safety <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The real-time data and simulation inherent in digital twins mean the industry can better predict and prevent safety issues. Anomalies are <\/span>identified<\/span>, and corrective actions can be implemented before incidents occur. Digital twins of small-bore pipes, for example, may <\/span>contain<\/span> virtual sensors to estimate stress from pressure and flow velocity readings [1]<\/span>.<\/span> This stress data is then fed into software environments that use machine learning and Bayesian methods to predict the remaining fatigue life of the pipes. These techniques analyse historical and real-time data to provide <\/span>accurate<\/span> predictions, allowing for <\/span>timely<\/span> maintenance and enhanced process safety.<\/span><\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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2. Production optimisation <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Process digital twins are a virtual model of physical plant processes, modelling activity in real time by integrating sensor data and advanced analytics. These digital twins are used to enhance operational efficiency. In the case of Electric Submersible <\/span>P<\/span>umps (ESPs) in producer wells, algorithms analyse patterns in data to continuously optimise ESP operations, keeping them within their ideal operating conditions [2]<\/span>.<\/span> As well as boosting overall efficiency, their lifecycle is extended.<\/span><\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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3. Asset performance management \n <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Asset Performance Management (APM) aims for improved operational performance \u2013 greater safety, reliability, availability and integrity. The digital twin at the core of APM helps synthesise and contextualise data and overcomes challenges with poor information management. This can consume around a fifth of operational budgets according to DNV, an independent expert in risk management and quality assurance [3].<\/span>\u00a0<\/span><\/p>

APM-based digital twins make deploying analytical solutions easier and can complement deployment of well-established techniques such as Risk-Based Reliability-Centred Maintenance (RCM). APMs for pump operation and maintenance, for example, can provide benefits to system uptime, asset longevity, and both capital and operating expenses. <\/span>\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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4. Operator training simulators <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Approximately 90%<\/span> to 95% of plant accidents are due to human factors [4]<\/span>.<\/span> Operator Training Simulators (OTS) reduce these outcomes. The digital twins (virtual plants), run on PCs so operators can learn crucial operations ahead of start-up and throughout the lifecycle. Without causing any damage to actual equipment or incurring <\/span>real costs<\/span>, industry employees can gain experience in an offline, non-intrusive environment. Through simulators, operators can gain experience of emergency scenarios while being in a safe environment<\/span>.<\/span><\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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5. Remote monitoring and operation of plant equipment and processes <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Many oil and gas facilities are inaccessible or in dangerous locations. Companies can create digital twins of these facilities for remote monitoring and operation so that operators can check the equipment and processes without having to leave their desks. Human operators are spared the risk of being in a potentially hazardous environment, employee travel costs are reduced, and issues can be identified and resolved more quickly.<\/span><\/p>

Digital twin supplier, <\/span>FRAMENCE,<\/span><\/a> has teamed up with robotics provider <\/span>ANYbotics<\/span><\/a> to offer an advanced joint solution to power company <\/span>Entega AG<\/span><\/a>, one of Germany’s largest suppliers of green energy and climate-neutral natural gas. Safe in their offices, employees send autonomous inspectors to tour a real-world power plant and check vitals while they follow its progress on a photorealistic digital twin.\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Expleo and digital twins <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Expleo has used digital twins<\/span><\/a> to solve issues around design, maintenance and manufacture, bringing together industry and data experts to increase efficiency and save costs. Below, we have noted a few examples.<\/span>\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Complex data synthesis for quicker design decisions <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Expleo developed a new system for our client, a world-leading aircraft engine manufacturer, that makes predicting the fatigue life of aircraft parts faster and more accurate. By combining advanced data management, storage optimisation and tools for automated geometrical detection, the digital twin helps engineers to make more accurate design decisions. The increased operational efficiency and reduced reliance on physical testing show how digital twins can tackle product optimisation challenges in complex engineering environments.<\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Optimising production lines for drone manufacture <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Our client, an aerospace and defence company, needed to optimise its drone production assembly lines to the best cost and time-efficient industrial level. <\/span>Expleo<\/span> delivered a 3D model and <\/span>V<\/span>irtual <\/span>R<\/span>eality (VR) manufacturing flows of the industrial factory via data collected from the prototype factory, combining knowledge of lean manufacturing with mastery of next-generation smart manufacturing products. As a result, the client can better respond to demanding industrial levels of production with the most optimised assembly and sub-assembly line flows.<\/span><\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Digital twins to predict maintenance costs of plane engines <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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To increase competitiveness, the customer support department of a world-leading aircraft engine manufacturer needed to know and predict the maintenance cost of engines leased to the aviation industry. Expleo\u2019s data project managers and data scientists created a digital twin to detail each unit\u2019s lifecycle. This helped to boost the client\u2019s revenues and expand its market share.<\/span><\/p>

For more insights into how digital twins are revolutionising industry within the context of the energy transition, download our <\/span>Transitioning to renewables at scale<\/span><\/a> report today.<\/span><\/p>

Expleo offers <\/span>digital twin and digital thread services<\/span><\/a>, helping to bridge data silos on all processes across development, from design to testing to production, by combining our engineering and digital skills. Digital twins are especially relevant in the energy & utilities industry, as they bring real potential to improve everyday operations, customer satisfaction and future sustainability.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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References<\/span><\/b><\/p>

  1. Department of Mechanical, Electronics and Chemical Engineering, Oslo Metropolitan University, Norway, Use of Digital Twins for Process Safety Management by Arvind Keprate and Nikhil Bagalkot.<\/span>\u00a0<\/li>
  2. Honeywell, Essential Digital Twins, p5.\u00a0 https:\/\/process.honeywell.com\/content\/dam\/process\/en\/documents\/document-lists\/doc-list-onshore-production\/WhitePaper_EssentialDigitalTwinsForUpstreamOilAndGas_APC.pdf<\/span><\/a><\/li>
  3. DNV, Data Smart Asset Solutions \u2013 Digital twin.
    https:\/\/www.dnv.com\/services\/data-smart-asset-solutions-digital-twin-65556\/<\/span><\/a><\/li>
  4. Yokogawa, Operator Training Simulator, Key areas for Operational Excellence Transformation.
    https:\/\/www.yokogawa.com\/eu\/solutions\/products-and-services\/lifecycle-services\/training-services\/operator-training-simulator\/<\/span><\/a><\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

    As companies within the industry continue their transition journey from hydrocarbons to renewables-first, digital twins emerge as a useful technology. In Expleo\u2019s recent report, Transitioning to renewables at scale, this journey is outlined with an emphasis on laying a robust digital foundation.\u00a0 Digital twins build on this foundation and enable the detailed monitoring, analysis and […]<\/p>\n","protected":false},"author":81,"featured_media":93772,"parent":0,"template":"","meta":{"_oasis_is_in_workflow":0,"_oasis_original":0,"_oasis_task_priority":"","_angie_page":false,"footnotes":""},"topic":[154,212,145,149,146],"insights-single-templates":[],"industry-taxonomy":[163],"content-type":[23],"country":[141],"service":[216,224,211,215,51,56,83],"class_list":["post-93769","insights","type-insights","status-publish","has-post-thumbnail","hentry","topic-compliance-and-regulation","topic-data-science-and-cybersecurity","topic-digital-transformation","topic-engineering-design","topic-sustainability-and-environment","industry-taxonomy-energy-and-utilities","content-type-blog","country-global","service-digital-transformation","service-industrial-process-operation-optimisation","service-innovation-management-solutions","service-manufacturing-supply-chain","service-people-and-change-management","service-sustainable-design-life-cycle-assessment","service-transformation-consultancy"],"yoast_head":"\nExpleo 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