Monday, April 08
Nowadays every plant or any critical production installation is typically equipped with multiple data acquiring points which transmit significant amounts of data. Collecting data is a useful feature, but unless it is understood, analysed, and used to make certain informed business decisions, it would remain only a good feature. That is where a new process of data management must be put in place.
Organisations are getting increasing benefits from the adoption of Artificial Intelligence (AI) deployed on large datasets.
The application of these techniques and effective data management can change the landscape of asset integrity management.
This session is intended to share existing data management best practices and value-added solutions as well as pave a discussion of future applications of data management systems to asset integrity management programmes.
The so-called ‘Internet of Things’ is where objects and equipment, such as sensors, interconnect, and transmit digital information. It generates vast volumes of data, arriving at high speed in varying formats with various degrees of reliability for decision-making. Advanced analytics technology of big data can uncover patterns and make predictions. This can reveal potential new business models “Digital Technology” and give stakeholders a better overview of operations, and more control and independence for managing assets.
In response to the wave of digitalisation sweeping through the world, oil and gas industry should consider new digital technologies to transform operations and create additional profits from existing capacity by reducing capital expenditures by up to 20%.
In this session we will be showcasing real-life case studies, on how oil and gas companies have used technology roadmaps to implement solutions that helped save money and improved efficiencies.
Through efficient preventive maintenance activities, operators, and service providers can avoid any unnecessary shutdowns, equipment failures, and increase the revenue, optimise the preventive maintenance expenditure, and avoid HSE incidents.
Digital transformation opportunities in all preventive maintenance areas can be used with great success in plant inspections, NDT activities, routine maintenance activities, condition based monitoring programmes, fabric maintenance programmes, etc.
Same digital principles can be applied for assets corrosion control and engineering.
Condition based monitoring is key in the works of reliability and integrity and many plants are moving towards digitalisation of condition based monitoring.
This session will bring the world of operations and digital development together. Digitalisation experience, digital applications, lessons learnt, and case histories can be shared in this session.
Tuesday, April 09
Corrosion Engineering Consultant and Author of ‘An Introduction to Corrosion Management in the Oil and Gas Industry’
Session 4: Digitalisation in Operations Integrity
Session Chairs: Marwan Al Shamsi, ADNOC Onshore; Mohammed Kamal Kabbaj, ADNOC HQ; Nawin Singh, McDermott
Asset integrity management—maintaining effective process safety barriers—is our key defence to a threat of a major fire in the oil and gas industry.
History has taught us that major industry disasters had their root causes in failure of operating integrity: operate within the design envelope, and monitor the barriers.
- Alarm overload
- Lack of or insufficient competent operators
- Poor communication of risks across shifts
This workshop will address the digitalisation of all operator tools and processes like shift registers, shift handovers, alarm management, downgraded situations, overrides, competencies, etc. Can the digitalisation be integrated and seamless data transfer happen between all these elements to provide an integrated risk management toolbox for the operator to make the correct timely decision to avoid any plant disasters?
Let us share lessons learnt and case histories in these areas and drive operations excellence.
Inspection and maintenance of plant and machinery has been based on prescriptive time—rule based approach.
Advanced approaches are required to reflect the complexity and innovation involved in the assets, and to operate at an optimal level. Risk-based approaches, give operators flexibility to undertake actions on some identified measures of risk in the management of their assets whilst meeting the same objectives.
Digitisation and statistical analysis enable you to take risk based decisions for RBI programmes and reliability cantered maintenance which allowed you yo hit target immediately and be more effective and efficient by saving potentially 50% of inspection costs if it is implemented.
This session is intended to probe the areas of digital development in risk-based approaches and how these could help the overall risk management process.
The oil and gas business is accelerating the effort recently trying to catch-up with what is considered imminent evolution. Artificial intelligence is one of the most exciting subjects in the journey, despite the fact that the oil and gas industry is not yet trying to adopt the definition of the AI as it’s known by the other industries to achieve autonomous systems to be able to make decision by its own. The effort is rather directed to more cautious learning following trends and using the analytics to being the first steps toward the true Artificial Intelligence.
To which extent is the industry ready to allow decision by autonomous systems to maintain the asset integrity in the future? What are the main challenges? Moreover, is (AI) considered the most efficient way to close the gap in talent availability in the near future?