Asset performance management for the oil and gas industry
The rise of asset performance in oil and gas
Asset performance management offers a powerful platform to increase reliability and availability of assets in the oil and gas industry. It is changing the landscape of how oil and gas companies are managing their assets and offers an integrated approach to many existing methods and builds on top of the powerful analytical solutions.
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What is asset performance management?
Asset performance management is a framework encompassing the next generation of methods used to ensure that performance is optimum throughout the entire asset lifecycle.
DNV GL is redefining asset performance management toward an all-encompassing risk-based approach to design and operations. This means incorporating to the short and long-term decision-making process with well-established techniques taking advantage of industry knowledge and standards. At DNV GL, asset performance management encompasses the capabilities of data capture, integration, visualization and analytics tied together for the explicit purpose of improving the operational performance of physical assets. APM includes the concepts of condition monitoring, predictive forecasting and reliability-centred maintenance (RCM), risk-based inspection (RBI), quantitative risk assessment (QRA), safety integrity level (SIL), and integrity operating window (IOW).
APM in design phase
The ability to influence cost becomes limited as the project evolves throughout the design phase, with design optimization. Thus, methodologies such as reliability, availability and maintainability analysis (RAM analysis) and operational forecasting are vital in the development of capital projects in the oil and gas industry. The earlier in the project the decision to change something is made, the more effective it will be from a cost perspective.
APM in operations and maintenance phase
Risk-based methods such as risk-based inspection (RBI), safety integrity level (SIL), assessment and reliability-centered maintenance (RCM) can be used to rank system and equipment criticality and to develop strategies for maintenance and inspection to manage the risks. Taking the risk approach has significant impact in many areas, including cost, staff morale, maintenance resources allocation, control of maintenance budgets, efficiency and reduced production scrap, to mention just a few.
Companies with mature reliability and safety programs typically make use of quantitative and more advanced methods such as quantitative risk-based inspection or failure mode effect and criticality analysis.
Effective information management with a digital twin
Poor information management is a hidden cost that can account for up to a fifth of operational budgets. The digital twin addresses this weakness. The digital twin is a digital, virtual representation of an asset, maintained throughout the lifecycle and easily accessible at any time. Central to this new concept is the creation of the digital asset ecosystem. The digital asset ecosystem is a network of interconnecting and interacting data, software and hardware relating to the asset and its system. One powerful aspect of this approach is enabling a new generation of advanced predictive analytics that are central to advancing asset performance management.
Intelligent analytical solutions in APM
The main analytical methods used in the asset performance management solution are:
- Risk-based inspection (RBI)
- Reliability centered maintenance (RCM)
- Performance forecasting
- Safety integrity level (SIL)
The digital asset ecosystem
The digital asset ecosystem offers an integrating and collaborative environment which ensures information is shared amongst different departments, facilitates the breakdown of operational silos and helps make full asset lifecycle based decisions. Breaking these data and process silos, between lifecycle phases and operational areas is a critical step in developing effective asset performance management schemes.
Plant integrity management
DNV GL's asset performance management (APM) offering also includes Synergi Plant for plant integrity management. It empowers companies to capture, integrate and visualize data, which can be further integrated with analytical tools such as reliability-centered maintenance (RCM), risk-based inspection (RBI), performance forecasting (RAM analysis) and safety integrity level (SIL) with the clear objective of improving the reliability and availability of assets.
RAM analysis - Reliability, Availability and Maintainability
Reliability, Availability and Maintainability (RAM) analysis allows you to simulate the entire lifetime performance of an asset in terms of availability, production efficiency and profitability. By using this well-established analytical method, you are able to predict problems before they occur. RAM analysis is performed in design and operation, from upstream oil and gas extraction through processing and transport logistics to the delivery of refined products to the customer. Armed with a complete analysis of a system's performance, you can vary system configurations, maintenance strategies and operational initiatives to determine the optimum approach for your enterprise.
Process hazard analysis
Materials such as oil and gas can present a significant hazard due in part to their high-energy content. Pharmaceuticals and petrochemicals may be flammable, explosive and toxic. To add to the risk, hazardous pressures and temperatures are often necessary to process these materials to create usable products. For these reasons the process industry is a source of major hazards to people, property and the environment. The global community of process safety professionals continuously strives to manage these hazards. DNV GL's hazard analysis tools contain world-leading, experimentally validated models for simulation of the behaviour of loss of containment of hazardous materials.
Risk analysis - QRA
Traditionally, the purpose of conducting a risk analysis has been to comply with regulatory requirements. This paradigm has evolved into risk-based design and risk-based operations. Quantification of risk forms a valuable basis on which to help determine where to focus avoidance, prevention and mitigation measures, given finite resources. DNV GL's risk analysis tools have been adopted globally in the oil and gas, petrochemicals, chemicals, pharmaceutical, insurance, steel and other industries for the purpose of understanding and therefore managing risk.
Offshore oil and gas reserves continue to be explored and produced. New installations, extension of life for old installations and novel approaches such as Floating Liquefied Natural Gas Facilities (FLNG) continue to be developed to the the world's growing energy demands. The nature of hydrocarbon extraction facilities are such that complex operations, chemical processes and logistics take place in remote locations on densely populated and spatially restricted asses. Handling large quantities of high energy products at high pressure can lead to risk to life on a large scale. Built on DNV GL’s long history we provide world-leading QRA software tool tailored to the challenges posed by offshore installations and offshore safety.