Coming to Grips With Carbon Data – Here’s Why It’s Problematic

Part 2 of a 3-Part Sponsored Article Series brought to you by Hewlett Packard Enterprise and Powerland.   If you are interested in reading Part 1 of the Article Series, please click here: Carbon is Now a Commodity Too Valuable to Overlook – Here’s Why

by Geoffrey Cann 

Industry professionals understand the mechanical aspects of emissions management. In the main, oil and gas infrastructure is not designed to waste value by emitting hydrocarbons in the first place (it’s money, after all) and the few places where it is intentional by venting or flaring, emissions are highly regulated. Scope 1 GHG estimates are usually readily calculable based on equipment features, load, fuel characteristics, and expected fuel consumption. Engineering models of facilities are carefully developed to provide rock-solid estimates of likely infrastructure emissions so that trade offs can be made at design between capital and operating costs, revenues, regulations, and value. These models are then often the basis for estimating GHG emissions over the life of the asset.   

But this is no longer fit for purpose. 

Flawed analytics

The problem with models is that they can drift out of alignment with the real infrastructure they represent. Grime builds up on valves, gaskets harden and degrade, and lubricants on moving parts lose efficiency. Infrastructure becomes leaky. The model might not even reflect the actual infrastructure or activity at the site because the as-installed gear is not captured correctly in corporate systems or on the engineering models. Inevitably, models under-measure the actual emissions, as repeated analysis has shown. 

Today, the application silos provided by software suppliers include sufficient analytic tools for the application data within the software’s domain of operations, and usually a few extra data sources. However, rarely are these applications set up to handle large numbers of diverse data sets and sources. Older solutions may not even be cloud enabled, or provide the clever application interfaces to allow for easy data movement between solutions or between companies in the supply chain.  

Even traditional commercial models for applications and analytics technologies (per seat pricing, annual maintenance charges) are no longer attractive. Industry wants solutions that are in the ‘as-a-service’ model, with charges based on usage, not access or headcount. 

A data problem

Data about actual measurements comes from hundreds of sources, with wildly varying measurement times and locations, across a large and diverse landscape. The volume of data is enormous and is growing over time. The lack of standards creates a human data preparation problem—before the data can be used or interpreted, an engineer must invest valuable time treating the data, usually with tools like Excel.

Aggregated company carbon data is built up manually from any available actual data, and from the original engineering models to produce the necessary emissions estimates for reporting purposes. Most operators find themselves tied to an awkward month end process and relying on very complex Excel spreadsheets, with all their usual flaws (hidden errors, incorrect calculations, rigidity, inadequate change control, and version control issues). This is a high cost, unscalable, poor quality solution. In this context the industry cannot reliably trace either its commodity products (petroleum, gas) or its carbon completely through the complete value chain, putting paid to any claims that energy products are somehow ‘green’. 

The industry is in desperate need for better data handling tools and better analytics to help with the mounting data challenge.

A security problem

Carbon data is sensitive information in an environment where capital now rewards carbon leaders and punishes the laggards. Oil and gas companies are rightfully concerned about their data and models being introduced into the public domain  should there be a security breach of a public cloud provider. Many operators still place a high value on on-premises analytics so that data sources (such as SCADA systems and historians) are not willingly exposed to the internet. These older systems are typically not encrypted, are often out of circulation and support, are not patchable in the event of a security issue, and even lack the tools to monitor for unauthorized use.

Changing technology

The field of carbon data and analytics is changing rapidly because of technology advances. Instead of relying on expensive hand-held cameras and infrequent manual data collection of actual emissions, operators are moving to continuous measurement using on-site low-cost cameras that are internet enabled and interpreting data live. These systems are very data and compute intense. 

Other vendors are developing soft sensors to synthetically measure GHG levels, avoiding the investments in permanent physical facilities dedicated to the task.  

Other technologies, such as satellite imagery, are revealing the extent of emissions challenges, while at the same time offering opportunity for improved measurement. Combined with cloud-enabled machine tools to interpret the data, satellite imagery is becoming another key data source in the hunt for value. 

Keeping pace with technology suggests a strategy of flexibility so that solutions can be developed quickly with minimal regret.   

Capital constraints

Capital markets continue to exert robust fiscal discipline on the industry, even in the face of the post-pandemic demand upswing, and the energy security concerns from the Russia-Ukraine crisis. Producers scrutinise every penny of cost, and will only reluctantly allocate capital to improve data and analytics. Prudent capital management means less capital is available to purchase more internal computer capacity, particularly for areas of the industry that are under-developed and not standardized, such as carbon emissions management. On-demand solutions that do not lock in long term costs are highly desirable. 

The talent crisis

Oil and gas is no longer viewed by the next generation talent pool as an attractive employer. As the current generation of workers is poised to retire, the industry is careening towards a talent crisis where it will not have the resources to maintain its existing business, allow for growth, and enable decarbonization and diversification. Capitalizing on the carbon commodity boom will require access to scarce skills in demand across all industries.

The third article in this series will explore a new solution offering that looks well suited to overcoming these challenges. 

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