In an exclusive Q&A, Sandra Merten, senior product manager at Elsevier, explores the importance of data within the energy transition
How vital will data be in supporting the transition to a sustainable future?
Many organisations in the energy industry are setting out on their transition to more sustainable and renewable practices – to do so successfully, data-led decision making is critical. Companies typically need a wide variety of data to assess a broad range of factors for energy projects, for example when screening sites for offshore wind, geological carbon storage or geothermal energy potential.
For instance, when identifying and assessing potential subsurface carbon storage sites, project teams typically need geospatial intelligence on carbon storage licensing areas, geological structure, stratigraphy, reservoir properties, potential seals, environmental impact and risks, CO2 emission sources, existing infrastructure, transport feasibility and more. By combining, layering and analysing the different types of data in a geographic information system (GIS), they can achieve the best potential view of a site. This enables them to make more informed and confident decisions about the feasibility of the site and to ensure that it is environmentally appropriate, equitable and commercially viable.
What are some of the data challenges associated with launching net zero projects?
Finding and aggregating the different types of data is a time-consuming and arduous process. Moreover, data are typically stored in inconsistent formats, so it can be very labour-intensive to normalize the data so that they can be assembled. Due to these challenges, geoscientists and geo-engineers spend up to 80% of their time searching for and formatting geoscience information and data, leaving limited time for analysis and interpretation. This increases the risk of overlooking important information, error, and project delays.
Is data access a barrier to this transition? If so, how can we resolve this?
Many geoscientists and engineers struggle to access the information they need for energy transition projects because the data are often locked away in silos. Organisations have a lot of data – in both structured and unstructured formats – sitting in different pockets throughout the organisation. Similar issues apply to external data, typically sourced from multiple different data providers.
Better data practices alongside the adoption of user-friendly digital tools can help to resolve this. Data silos can be broken down by using technologies that can help to aggregate, enrich, standardise and structure data from multiple repositories in a scalable way. These include automated processing pipelines that can handle multiple file types, the use of taxonomies and semantic technologies, such as Natural Language Processing (NLP), machine learning, and geotagging.
With so much data available in so many different locations, how can engineers be sure they are accessing the most relevant resources whilst staying efficient?
With new data constantly being produced, geoscientists and engineers can find it difficult to keep up. Not only is it challenging to find and assemble the data, but also identifying the relevant data and generating insights from the data can be hampered due to vast volumes of data. We are approaching a point that without embracing digital technology, researchers are at risk of being left behind.
Curated databases and domain-specific search and refinement options, such as geospatial discovery capabilities, are important to ensure that geoscientists and engineers get the most relevant results. Moreover, using geospatial intelligence and AI-driven solutions can further support in finding the most appropriate data and efficiently gaining insights from the available information and data.
What are some of the most exciting opportunities opened up by using data to drive the transition towards net zero?
Better application of data will ultimately bring the energy industry closer to meeting net zero targets and accelerate energy transition timelines. In particular, the use of geospatial intelligence is an exciting opportunity. Existing geological, geophysical, geotechnical and environmental data from scientific publications can be leveraged and spatially analysed to identify and assess potential renewable energy and decarbonisation opportunities.
Another interesting opportunity is the repurposing of existing proprietary data originally collected for other natural resource projects. For example, existing data collected and held by the petroleum and mining industries - such as well data, seismic surveys and temperature data - can be reused for identifying and assessing a site’s potential as a source of geothermal energy. Especially when combining published and proprietary data, energy transition teams can take advantage of the available breadth of information and data to identify opportunities to drive the transition to net zero.