Risk-informed decisions: A decision-support tool for integrity management
A lackluster approach to risk management undercuts risk and integrity management effectiveness and it virtually ensures the mis-allocation of resources in managing asset integrity.
DNV GL’s approach to risk management guides integrity management efforts from a risk-informed perspective leading to optimized resource allocation and fully compliant operation, all while enhancing public safety.
Our risk management methodology enables a clear ‘risk picture’ of the overall asset and its components. Benefits of a clear risk picture can be realized in a number of ways:
1. Delivers a long-term decision-support tool for managing integrity efforts,
including the ability to measure risk in dollars of RISKEX™ for use in
balancing CAPEX and OPEX budgets.
2. Helps quantify levels of uncertainty inherent to assessing risk, providing
a measure of ‘completeness’.
3. Generates a visualization of changing risks along the pipeline route while
demonstrating aggregate trends across the entire asset.
4. Builds ultimate trust in the risk results through transparency while promoting
5. Enables the integration of asset risks directly into the broader enterprise risk
Risk assessment framework: A foundation from which to build
One of the most important aspects of effective risk management is to establish a solid framework early in the process – a functional framework that will:
- Outline how risks are established and used
- Define key roles and responsibilities
- Support work flows throughout the on-going and ever-improving program
DNV GL’s methods provide a formalized process with a logical, structured approach for laying the foundation on which a robust risk assessment can be built.
A functional framework will allow for the construction of a risk model(s) that is integrated into the operator’s integrity management program (IMP).
In addition to ensuring proper integration of data across multiple departmental boundaries, the framework helps to establish work flows of risk information providing accessible and functional outputs across the organization, readily supporting decision making.
Converting data to knowledge
The core of DNV GL’s risk methodology is transparent, data driven risk modeling which produces quantitative risk results. All efforts are made to assign real (verifiable) numbers to estimates in order to measure a probability of failure (PoF) and potential consequence for all isolated and interacting failure mechanisms.
Our assessment methods and modeling tools augment and support the operator’s existing models and software when possible. As data gaps can be frequently encountered during the risk assessment process, we identify those gaps, then close them with the use of operator subject matter experts, computational modeling, and additional data collection.
In the event some gaps cannot be readily addressed, DNV GL can assist with its staff of science and engineering specialists crossing a wide range of integrity disciplines. Still other gaps can be closed using publicly available information for which we’ve become adept at mining from sources such as NOAA, USGS, incident databases, and one-call data.
Through years of pipe analysis in both field and laboratory conditions, we have also developed an expansive database of line pipe properties that aids us in assessing material and construction properties of virtually all types of vintage pipe.
Our methods take into account the uncertainty associated with using estimated data sources, enabling the operator to quantify the source’s effect on the overall risk picture. Quantifying this uncertainty facilitates a sensitivity analysis to guide additional data collection in areas having the highest effect on calculated pipeline risk, thereby optimizing the collection process.
Although we carry complimentary risk management software solutions in the form of our Synergi Pipeline and MARV™ software, our risk calculations can be supported by readily available platforms including Microsoft® Excel, meaning no specialized software is required.
Exploiting knowledge into actionable results
Regulatory directives call for risk management systems to be accurate, verifiable, and complete. DNV GL’s endeavor to produce measures of failure probability and potential consequence in verifiable units using transparent modeling leads to a higher level of trust in risk results and the ability to verify data and program reliability.
Modeling pipeline risk is inherently complex due to the numerous failure scenarios possible for any given section of pipeline. In order to efficiently extract the critical knowledge regarding risk drivers and trends useful for decision making, DNV GL incorporates analytics utilizing our risk management experience, providing operators with actionable risk intelligence.
Our comprehensive risk modeling provides a more accurate profile of the risk reality along the entire pipeline. This continuous risk profile in addition to risk intelligence along the line and at discrete locations of elevated risk provides for efficient, more reliable risk-based decision making while enhancing communications between stakeholders.