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Explore IndustryPredictive analytics in the oil and gas industry
Predictive analytics in the oil and gas industry
Learn how Aker Solutions uses simulation-based predictive analytics to build digital twins of subsea systems for production optimization, saving millions of dollars in deferred production
Measured sensor data combined with data analytics has been widely recognized as an effective means of enabling efficiency and maintenance improvements in many oil and gas facilities. However, there is the opportunity to make an even greater step change if we ask ourselves:
This is where predictive-based analytics delivers the final, but critical, piece of the puzzle. In this webinar, you will hear how Aker Solutions embrace engineering simulation and predictive engineering analytics to ensure their equipment is optimized through the complete lifecycle--from design to operation.
The ability to generate reliable simulation-based predictions--of individual pieces of equipment and full systems-- based on underlying physics, results in valuable additional data on how a system operates; this leads to deeper understanding and insight to make more informed, better-prepared decisions.
By embracing simulation-based digital twins, operators and equipment companies are able to build virtual sensors that can provide unparalleled levels of data in locations that would otherwise be inaccessible, helping them understand how the performance and integrity of their system are changing, and even to assess the impact of possible future operating conditions on their systems and search out improved efficiencies.
From managing complex multiphase flows to ensuring reliable thermal performance in operation to managing and avoiding hydrate risks, a predictive-based approach can save time and cost while delivering greater insight to enable safe and efficient operations.
Henrik Alfredsson
Managing Director, Aker Solutions, Sweden
Javier Garriz
Marketing Manager, Siemens Digital Industries Software
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Learn how Aker Solutions uses simulation-based predictive analytics to build digital twins of subsea systems for production optimization, saving millions of dollars in deferred production
Measured sensor data combined with data analytics has been widely recognized as an effective means of enabling efficiency and maintenance improvements in many oil and gas facilities. However, there is the opportunity to make an even greater step change if we ask ourselves:
This is where predictive-based analytics delivers the final, but critical, piece of the puzzle. In this webinar, you will hear how Aker Solutions embrace engineering simulation and predictive engineering analytics to ensure their equipment is optimized through the complete lifecycle--from design to operation.
The ability to generate reliable simulation-based predictions--of individual pieces of equipment and full systems-- based on underlying physics, results in valuable additional data on how a system operates; this leads to deeper understanding and insight to make more informed, better-prepared decisions.
By embracing simulation-based digital twins, operators and equipment companies are able to build virtual sensors that can provide unparalleled levels of data in locations that would otherwise be inaccessible, helping them understand how the performance and integrity of their system are changing, and even to assess the impact of possible future operating conditions on their systems and search out improved efficiencies.
From managing complex multiphase flows to ensuring reliable thermal performance in operation to managing and avoiding hydrate risks, a predictive-based approach can save time and cost while delivering greater insight to enable safe and efficient operations.
Henrik Alfredsson
Managing Director, Aker Solutions, Sweden
Javier Garriz
Marketing Manager, Siemens Digital Industries Software
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