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  • Nick Bailey

Innovations in Methane Surveying

Updated: Jun 19, 2020

Methane is around thirty times more potent a greenhouse gas than CO2, over a one-hundred-year period. Understandably then, society and governments put significant pressure on oil and gas asset owners to reduce fugitive methane emissions. There is also the internal pressure from management to conserve what is, after all, valuable product; methane has significant value and the 2-3% total losses estimated within typical supply chain are worth the mitigation effort.


Traditionally, operators carry out LDAR programs regularly in order to detect, fix and prove leaks: first finding leaks, next attempting a fix – either immediately or at next shut down – and finally revisiting the detection process to prove that the leak has been eliminated. It’s common for asset owners to carry out surveys annually, bi-annually or quarterly. Some operators monitor facilities on a monthly basis or even have a process of rolling surveys in order to keep losses at a minimum. Such vigilance keeps regulator, stakeholder and management confidences in check.


The primary issue with having to perform regular surveys is cost. A typical field-based emissions survey starts with an engineer visiting a facility, which could be several hours drive from base and possibly in a very remote location. The engineer will work asset-by-asset, through a P&ID, alongside the report from the previous survey, first using an OGI camera to detect any emissions and, when detected, using an FID or similar device to sample concentration readings. The engineer then drives back to base to write up the results and file a report. For a small facility such as a battery or single wellhead, it is common for such a survey to take a day. Large facilities such as a complete refinery can take months to survey. If a leak is found, a maintenance engineer will then be dispatched to the facility in order to fix the leak. This involves a second truck roll and associated costs. OGI cameras and FID sensors are expensive devices that need to be amortised into the cost of delivering surveys. An engineer will need a truck and safety equipment.





There is, therefore, reason for looking for ways to innovate: to find technologies that reduce cost, by reducing survey time, survey cost and even the need to survey in the first place.

OGI, optical gas imaging, has emerged over the past decade as a useful technique for locating leaks. A skilled operator can ‘see’ fugitive emissions using an OGI camera. However, OGI remains a qualitative technique in that it cannot give the operator a quantitative mass rate for the escaping gas. QOGI, or quantitative optical gas imaging, is a technology that takes raw OGI footage and provides a predicted quantification value from it. This can be used alongside or instead of traditional Method 21 calculations to ‘size’ the leak, and this value subsequently used to prioritise the order in which leaks are fixed.

Upstream facilities are, as identified by the IEA Methane Tracker*, where quickly eliminating leaks can provide maximal additional profit – such is the amount of product lost and the relatively low cost of recovery. For such facilities, allowing a leak to go unresolved between surveys for up to three months can be very costly.


Static, or in-situ, monitoring of remote facilities offers a way of continually monitoring for leaks without the need for performing inspection truck rolls. If an emission is detected, it can be monitored in real-time. If the static monitoring technology deployed can perform a prediction of quantification for the emission, then the fix can be prioritised. The fix engineer can immediately see, via the static monitoring solution, whether the fix has been successful and, if so, the job can be closed immediately, without a secondary – out of phase – inspection required. The financial savings are significant: reducing inspection truck rolls and fixing leaks in near real-time. Payback periods tend to be short.


There are some assets where inspection is a full-time process. Take, for example, pipeline surveys. It is not uncommon for an engineer to be permanently associated with a single section of pipeline to continually survey. This engineer will spend the day driving along the pipeline, stopping at each potential leak zone and using OGI and concentration sensing equipment to detect and report any fugitive emissions. Not only does this require a full-time resource but, in many cases, leaks occur in areas that are not actively monitored, either between survey points or, for example, if the pipeline is buried or unreachable.

A solution to this is wide-area surveying – either by drone or using a truck-mounted system. Rather than using OGI or a ‘sniffer’ type device, a long-range sensing technology is deployed. These technologies can measure differences in methane concentrations in the parts per billion. Algorithms parse this concentration data as the sensor travels along the pipeline, and leak positions and mass emission rates predicted, providing a prioritised list of fixes. Not only is this technology much more accurate and inclusive than traditional survey techniques, but it is also much faster and therefore less expensive.


Each of the technologies discussed above have one thing in common; they produce large quantities of data. This data needs to be collected in the field and centrally managed. Algorithms that absorb large amounts of field data can then be used to analyse these datasets and present results back to users in an intelligent, value-added dashboard. With a facility’s data in one place, the complete narrative relating to an asset, its maintenance records and leak performance can be viewed in relation to its peers and neighbours. Bench-marking can take place, preventative maintenance improved, safety enhanced, and costs refined from the process.


In conclusion, technologies are emerging that allow asset operators in the oil and gas sector to migrate cost out of LDAR programs. Furthermore, by reducing the time and frequency of surveys, leaks are detected much faster and product loss is reduced. The monitoring of assets becomes a valuable tool for profit maximisation.


Sedolabs, in partnership with Worley, has been innovating in this space for many years and has developed QOGI, Static Monitoring, Wide-Area technologies and the FETCH4 emissions data platform discussed in this article.


*https://www.iea.org/weo/methane/

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