WHITE PAPER
Advanced Analytics for Oil & Gas Downstream
Democratize analytics to build operational resilience and achieve more predictable business outcomes
Modern-day business pressure for maximizing process profitability and reliability has never been higher than it is today. At the same time, competitive positioning for the more innovative organizations will be very dependent on implementation of new LEAN and successfully sustainable climate strategies linked to future decarbonization target challenges. There has never been a more critical time to reduce cost and risk and embrace the value of digital technology by building operational resilience.
Learn how Advanced Analytics can fast-track your digitalization journey, improve operational performance and increase plant safety.
This white paper provides example application areas for refining, petrochemical and specialty chemical operations, including maintenance opportunities and indicates how the TrendMiner self-service advanced process analytics platform can support sites with their digital transformation journey.
Refinery processing opportunities:
- Energy management
- Find the best energy operating point: Utilities side
- Reduce energy consumption: Process side
- Improve transient operations: Start-up events, process upsets
- Cross Asset Analytics
Chemical processing opportunities:
- Increase plant throughput: Ammonia plants
- Improve plant availability: Ethylene plants
- Increase production ef f iciency and product quality: Specialty
Download the White Paper
Read How Self-service Advanced Analytics Can Help You Achieve a More Predictable Business Outcome
In recent years, the adoption of advanced process analytics technology has started to become a critical part of the digitalization journey for the more forward-thinking players in the industry. Downstream processes including refineries, petrochemicals and specialty chemicals plants are not an exception. Making the energy transition towards de-carbonization is one of the first challenges to tackle in parallel with improvements of plant availability, performance and resilience as well as an effective way to manage, diagnose and monitor assets.
About the Authors
Paul Blackhurst is an internationally experienced Oil & Gas process automation and engineering professional with proven major project/R&D delivery leadership/execution skills, fundamentally biased towards operational excellence from a wide range of successful past operational technical roles. Paul retains a passionate track record for driving sustainable and operable technology deployment, spanning all sectors of O&G facilities including LNG. Such passion is fundamentally underpinned by strong project management skills focussed on business bottom line impacting technologies and the essential ingredient of fostering active leadership development of people via in-role experiences.
Julian Pereira is Head of Customer Success EMEA at TrendMiner and Process Chemical Engineer by education. Julian has built his key industrial process expertise by delivering a variety of on-site engineering solution services around the globe for Oil & Gas, petrochemical and manufacturing processes. Among his expertise, Julian has 10 years of experience in process simulation and optimisation, energy optimization and integration, data analytics and continuous improvement. Currently Julian is helping the industry to work towards a successful digitalization journey with TrendMiner.
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Low-code and No-code AI & Analytics Solutions Yield High-Value Use Industrial Use Cases13 September 2024 - 15:19- Building a Foundation for AI & Analytics with an Industrial Data Fabric30 August 2024 - 23:12
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