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Disruptive technology meets the challenge of fugitive-gas emissions

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Oilfield Technology,

Optical-gas imaging makes gas clouds visible and operates as an infrared sensor capable of operating within the thermal spectrum, Laith Amin, Advisian, explains.

Natural gas is well known as a clean fuel that can contribute to a reduction in urban pollution and greenhouse gas emissions. Even the most prominent renewable technology advocates acknowledge natural gas as a clean-fuel stepping-stone from coal or oil towards energy that is less reliant on fossil fuels.

Expanding exploitation of natural gas is working, and globally so. For example, in April 2017, the UK enjoyed its first 24 hr power generation period completely coal free since 1880, and, in the US, natural gas has become the nation's leading power-generating fuel source.

Reasons for uncertainty

Gas is a key weapon in the fight against carbon dioxide (CO2) emissions. In Asia, unease about air quality in post-industrial China has led to some impressive deals with natural gas supply countries, such as Russia and Australia. However, this very supply chain sometimes calls into question the categorization of natural gas as a clean fuel.

Awareness of raw methane emissions in the US is growing. Emissions traces seen from space show concentrations of activity around unconventional oil and gas production. Raw methane is 86 times stronger as a greenhouse gas than CO2 when impact is considered over a 20 year period. Ultimately, experts agree that for natural gas to rival coal in reducing greenhouse-gas emissions, then emissions of raw methane in the supply chain must be less than 1% of total production.

In the US, raw methane emissions estimates range from 2% of overall production to around 17%. Alarmingly, in recent years, the US Environmental Protection Agency (EPA) has increased its estimate of emissions in upstream gas operations by 134%, bringing the overall total to 1.4% of total production (which they sometimes flag as a possible underestimation).

Methods of measurement

But, why do these estimates vary so widely? To answer this question, we must examine the methods of measurement. One method is simply to apply emissions factors and schedules provided by regulators. The emissions-per-equipment item then can be aggregated to a plant total to produce a volume for undesirable leaks, or fugitive emissions. This method takes no account of the actual leak rates, or if in fact the equipment leakage at all.

The second method is referred to as EPA Method 21. A measurement instrument (a flame ionisation detector) is held near the stream of a suspected leak and measures the concentration of the fugitive gas in the atmosphere.

Method 21-type emissions measurements have significantly impacted the oil and gas industry. The method verifies that there is in fact a leak, which can be passed on to repair programmes. This has facilitated significant greenhouse-gas reductions over the years, and the retention of valuable gas in the supply chain for end use.

However, Method 21 testing’s success still does not explain the wide variances in the estimates nor why a methane emissions footprint is visible from satellites to an extent that indicates a growing problem.

Seeing is believing

One technology, which the EPA refers to as optical gas imaging (OGI), has recently been added to the list of regulator-allowable methods of measurement. It is an infrared (IR) sensor capable of operating within the thermal spectrum. It generates an image of a gas leak visible to the human eye. For the first time, users can see a gas cloud.

This was introduced to the public through EPA footage of the Aliso Canyon gas leak in 2015. It was the worst gas leak in US history, with 97 100 t of methane and 7300 t of ethane released into the atmosphere. This is the equivalent carbon footprint of 1.4 million cars or six coal-fired power plants.

This leak showed how important OGI can be in measuring the extent of a leak. However, further OGI deployment has shown that a small number of very large leaks often are responsible for most of the emissions in a defined scope of study. Furthermore, many of the other equipment items are either not leaking or have such small emissions rates that they are not economically viable to fix.

Which way now?

While OGI has been a massive leap forward, one fact remains: an IR sensor cannot provide quantitative information about a fugitive emission. It can only provide a qualitative image of a leak and can either show false positives (e.g., of a moisture vapour cloud) or false negatives (e.g., because of range, focus, shadows or other issues).

Given that ‘you can't improve what you can't measure,’ what is the way forward? Energy companies have been incentivised to invest billions in the development of gas production and supply infrastructure. Coal plants have been shuttered and emissions-reduction commitments have been made in light of the important role that natural gas will play.

Providing a workable solution to this for all the industry is difficult, but without the ability to quantify emissions from leaking equipment, any leak-repair programme will not necessarily be fully based on science. Indeed, if about 20% of a plant-environment fugitive emissions are large leaks that are economically viable to fix, then a technology's ability to quickly determine which 20% of leaks that is will be key.

Prioritising specific repairs means a reduction to total plant emissions in a much shorter timeframe and at greatly reduced cost. Furthermore, if operators also can perform emissions quantification work on a second survey, then they can generate a reliable number for the reduction of greenhouse-gas emissions at the plant resulting from leak detection and repair work. This could then be costed against the monetisation value of the gas and compared to the cost of leak detection and repair to determine a ROI calculation on the activity itself.

Final words

This is closer to reality than one might expect. Advisian is bringing together multiple elements of technology with data science to create a platform for the digital quantification of fugitive gas emissions. A mix of artificial intelligence, unmanned aerial-vehicle technology, and IR sensors has produced very exciting results.

One thing is clear: this technology will have a disruptive effect on how fugitive emissions surveying is done, and will allow natural gas to reclaim its position on the world stage as a clean-burning fuel that can ensure our contribution to carbon footprint reduction for many years to come. 

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