Many fire and gas mapping practitioners are performing fire and gas mapping studies without first performing a hazard assessment to select the required coverage targets for the system.  This typically involves setting a “standard” target for coverage which is applied across all areas of the process plant.  While this is acceptable and will typically result in a conservative design (if the standard coverage target is set conservatively), there is great value in selecting coverage targets using performance based design practices.

Performance based fire and gas system design is predicated on the idea that the level of performance of the system should be commensurate to the level of risk posed by a fire or gas release in the area being monitored.  The level of performance of fire and gas detection largely governed by the probability that the system is capable of detecting a hazard, this is referred to as the coverage of the system.  For example, stating that a flame detection system can achieve 90% coverage for a 1 ft diameter pool fire is the same as saying that on average, we expect the system to detect 9 out of 10 fires of this size.  Using a 90% coverage target for fire and gas systems is typical for FGS mapping studies which are performed without first selecting coverage targets using a performance based method.  While this may seem practical,  this decision could carry unintended financial consequences as achieving this target may require substantially more detectors then are required, particularly in areas where the risk of fires or gas release are low.  Selecting coverage targets with performance based methods will ensure both a safe and cost-effective design.

Developing a performance based method for selecting coverage targets may seem like a daunting task for a project engineer, especially if you have minimal experience in quantitative risk analysis.  Typically, a performance based design requires that a quantitative risk assessment (QRA) be performed to determine the level of risk in an area.  That level of risk is then compared against risk tolerance criteria governed by corporate guidelines to determine the required level of performance for the fire and gas system.  This process can be extremely time consuming and requires expertise in methods which are unfamiliar to many practitioners of fire and gas mapping.  Based on Kenexis’ experience in performing fire and gas mapping studies we found that a more practical solution was required.

What we’ve found after performing many fire and gas design studies is that we are able to predict the appropriate coverage targets based on a few risk aggregating factors.  These factors include:

Equipment Type (Leak Frequency)

Occupancy in the Area

Potential Ignition Sources in the Area

Stability of Process Fluid at Atmospheric Conditions

Process Pressure

Flammable Environment (Level of Confinement and Congestion)

Toxic (typically H2S) Concentration

After recognizing this, Kenexis began to develop a semi-quantitative method for performance based fire and gas system design which reduces the level of effort required for determination of the coverage targets substantially.  Over time, we have analyzed thousands of “typical” process areas in oil & gas facilities using the time-intensive QRA method to select coverage targets.  This experience was leveraged to adjust the inputs, parameters and required coverage targets of the semi-quantitative method so that the selected coverage targets will ensure the appropriate levels of risk reductions given the most common risk tolerance criteria used in the oil & gas industry.  To date, this method has been applied successfully at more than 50 facilities world-wide including offshore wellhead, satellite and processing platforms, FPSO’s and a wide range of onshore facilities.

The semi-quantitative is a simple scoring procedure which can easily be understood without a strong background in risk assessment.  The following figure is the workflow for the process:

Performance Based FGS Workflow

While the process is simple enough to describe in this blog it has already been published in great detail in Appendix G the Kenexis FGS Engineering Handbook, which can be downloaded for free from the resources section of our website at the following link (