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Delivering the right approach to emissions management

Published by , Editorial Assistant
World Pipelines,

It’s no secret that the oil and gas industry is under intense pressure to reduce emissions from production. Currently totalling around 3% of all UK greenhouse gas emissions, the industry plays a major role in the UK’s push towards net-zero objectives.

Delivering the right approach to emissions management

Yet, despite its importance on the world stage, reports warn that emissions targets won’t be achieved.

The North Sea Transition Authority (NSTA) has been the latest to cast doubt, stating that, although the industry was on track to meet interim emission reduction targets of 10% by 2025, and 25% by 2027, it needed ‘bold measures’ to halve them by the end of the decade.

With this in mind, plus 100 new North Sea exploration licenses and plans for a new Rosebank oil field , it’s clear the sector must focus efforts to lower emissions wherever possible.

Reliance on heavy machinery

One way to do this is to tackle the level of emissions that come from heavy machinery – the backbone of oil and gas production. As extraction processes can be extremely energy-intensive, solutions that can monitor, log, and calculate energy needs should be welcomed with open arms.

Whilst this type of data is available to some extent, it’s often received and processed in retrospect, some weeks or months after the work has already taken place. This makes the industry sluggish to respond, resulting in tons of wasted emissions each year due to a lack of agility and major inefficiencies.

There’s life in the data

Whilst a mountain of data is collected during drilling and production, much of it focuses on areas other than energy expenditure, for example, the pressure and temperature of drilling fluids as well as seismic activity. Unfortunately, the energy usage of large machinery is an area often overlooked, despite the savings it can bring both in terms of emissions and project costs when optimised properly.

Largely, this is down to a lack of CO2 benchmarking – which the industry so desperately needs. Companies are failing or are simply unable to understand their greenhouse gas emissions relative to previous years or projects. This is compounded by a lack of up-to-date data, which arrives too little, too late. As a result, both the environment and firms pay a high price in every sense of the word.

Understanding the real impact

What’s needed is closer monitoring of machine metrics, so that companies can identify clear patterns of operational inefficiencies. We need to understand how often machinery is being used, and how long it sits idle. What are the production yields for the time that the machine is in operation? How can machinery be used more efficiently, particularly if it’s rented and charged according to usage predictions? These are all valuable questions that can make a big difference to the overall emissions and profitability of any project.

However, without a CO2 benchmarking framework in place, supported by improved levels of easily shared data, we’ll continue to see an industry with no handle on machinery emissions and likely, a continued pattern of emission target failures.

Refining the process

There are, however, solutions to this problem and access to technology that offers easy-to-read and interpret telematics is one of them. With the right software, users can see in real-time when machinery is on or idling. Often, equipment operators manually record this information, which is then entered into a central database – a slow process that leaves obvious data holes and inaccuracies. Instead, tech that reports this information automatically streamlines the flow of data and allows companies to respond with agility.

As well as emissions data, having access to this detailed information can benefit all areas of a business, saving energy and boosting profits. Fuel consumption, staffing decisions, maintenance scheduling and rental costs are all affected and can be managed more effectively.

Future-proofing the right way

Ultimately, improving access to emissions data is the first step in creating an effective CO2 benchmark strategy. The use of AI is more time and cost-effective, allowing live data from across multiple projects to be streamed to one shared location, leading to a sharp rise in operational efficiencies.

Given the urgency of the issue and the impact oil and gas can have on lowering emissions, investment into this strategy is what’s needed at a crucial turning point in our environmental future. It’s now up to companies to understand, act, and begin placing as much importance on operational emissions as well as our future energy sources.

Image: Jennifer Thomson, CPO, MachineMax.

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