Some operators are now moving beyond static QRA models to make better use of the huge volume of data that are collected in a process involving considerable time, effort, and cost. They are starting, or planning to, update data more frequently using a dynamic approach to risk-based safety management. New cloud-based tools, combining secure data storage and analytics, are assisting them on this journey in pursuit of potential cost, operational, and safety benefits (Figure 1).

Dynamic risk estimation helps decision making in risk management

In one example of a dynamic approach, integrated energy company Chevron has begun a pilot project with DNV GL to develop enhancements to QRA and related studies by using digital technologies. 

The findings of a pilot project were published in a paper at the AIChE 2018 Spring Meeting and 14th Global Congress on Process Safety. It identifies lessons learned and best practices in designing safer production facilities that can be realized from key advancements in the process and application of QRA. 

“We need to make effective use of QRA early during project engineering design and related risk-based decision making,” said SreeRaj R Nair, one of the paper’s authors and Technical Lead, technical safety engineering and risk management for multinational energy company Chevron’s major capital projects in the Gulf of Mexico.

Taking a new approach to QRA

Nair identifies several general industry challenges beyond the sheer range and volume of input data required for QRA. Changes made in rapid design development, a feature of more flexible projects in the lower oil price era, create a need to update QRA with increased frequency, for example. 

Risk evaluation results and the suitability of safeguards can also change as operating conditions evolve. Static QRA studies do not consider changes in personnel (manning) distribution, for example. They also lack visibility to wider stakeholders, and limited access to the results of a study means that the full potential of data cannot be extracted. 

The dynamic quantification of risk, based on real or near-real time automated analysis of data from sensors and manual input, can help to address some of these issues. Compared with static QRA, this will be a positive step forward for the industry and has significance for decision making, Nair said.

The use of asset-specific dynamic input, such as pressure, temperature, strain, corrosion, leakage, and other readings from sensors, helps to calibrate the input – such as leak counts and effectiveness of safeguards – for an asset. This avoids unnecessary expenditure on risk reduction based on generic industry data, Nair noted. 

“Furthermore, use of input from instrumented process control system and field detection – including weather data – can contribute to efficiently responding to an emergency due to loss of containment of hydrocarbon.” 

Information and change challenges in risk assessment 

One challenge that arises from aggregating QRA results to create static reports is that it can mask the detail of how risk profiles will vary if parameters such as manning distribution change, according to Koheila Molazemi, global service area leader for risk management advisory, DNV GL - Oil & Gas. This means that if QRA starts too early, information may rest on assumptions that lead to underestimating or overestimating risk.

“Underestimates may contribute to incidents that expose operators to reputational and financial risk; overestimates may mean capex being higher than is really required to cover the real level of risk for an asset,” Molazemi added. 

Another issue is that many businesses and organizations – among them, engineering, procurement, and construction contractors – are stakeholders in producing a typical QRA report. Some play key roles before operators review documentation. The huge number of handover documents risks information being ‘lost in translation’ or simply neglected. 

Digital technologies are addressing such challenges. They enable real-time, dynamic interaction on user-friendly, secure online software platforms. These host and analyse huge amounts of information to display correlated, relatable, and reliable reports. 

“They can unlock the value of QRA data and combine it with other operational information. It lets us create a single ‘set of truths’, so that operators are not overrun with data they do not know what to do with and are unsure whether to trust,” Molazemi said. 

One big advantage of automated data entry in the cloud through connection to a customer’s design information is that it enables QRA earlier in the lifecycle. The reduction in overhead makes it practical to run models earlier, before the design is detailed and final; the model updates every time a change is made. 

“It enables the operator to implement inherently safer designs by optimizing layouts, which in turn increases operational reliability,” Molazemi said.

Getting the most from digital technology in QRA

Digital technology can be used very effectively to enhance the interface of input data from project/asset to the quantitative risk assessment tool (Figure 2), Nair confirmed.

“For example, it can deliver an automated parts count from an electronic piping and instrumentation diagram. Also, inventory estimation using a 3D piping model from the project can be linked directly to the QRA tools, rather than recreating the asset from 2D drawings.” 

Digital technologies also enable effective risk communication to wider stakeholders, including clearer understanding of what contributes to risk, he added. 

“Visual representation of potential events – such as a jet fire with flame and radiation – can be used for training and emergency response planning. To some degree, data crunching and visualization also allow end users to conduct sensitivity analyses. Using a single portal to access a QRA model for multiple assets can assist the simplification and standardization of risk management efforts.” 

Online tool helps to unlock the full value of safety studies

DNV GL’s digital service MyQRA unlocks opportunities from digitalization in risk management. It supports customers already using DNV GL to perform QRA to get even more value from the data at no additional cost. Its features are described in this short video.  

The MyQRA approach offers significant cost advantages, Molazemi said: “Our estimate is that an operator may end up spending 30–40% less on safety studies over the 25- to 30-year lifecycle of a medium- to large-sized asset, while getting much more value out of the data generated in their QRA studies.” 

Disclaimer: 

DNV GL prides itself on providing accurate information but makes no claims or guarantees about the accuracy, completeness or adequacy of contents in this publication, and disclaims liability for any errors or omissions. The authors’ views here do not necessarily reflect DNV GL’s views.