As the energy industry increasingly digitalises, and companies push towards net zero, it is ever more important that companies fully understand their operations and how to most efficiently deploy projects. A vital part of that understanding comes from increasing access to data and using it to make the best choices available about energy projects. With the proper use of tools such as geospatial intelligence, power companies can better empower themselves to make those choices.
We hear more from Dr Sandra Merten, MSc in structural geology & tectonics, PhD in thermochronology & tectonics, at academic publishing company Elsevier.
Scarlett Evans (SE): Why is data expected to be (and currently is) so important for the energy industry?
Dr Sandra Merten (SM): Many energy companies are transitioning to achieve a net-zero emission future. Data will be essential in informing a successful, efficient energy transition while meeting growing energy demand, for example, when screening sites for offshore wind or screening for potential geological carbon storage sites.
With the right data – and the right analysis – geoscientists and engineers can make better decisions, optimise processes, and identify new opportunities. This makes processes more efficient, reduces operational costs, improves success rates, and limits environmental, health, and safety risks.
SE: What are the current challenges seen in the industry that data can help to alleviate?
SM: With a massive push towards renewable energy sources and reducing carbon emissions, identifying sites for wind farms, geothermal energy, or geological carbon storage is a major challenge – particularly for offshore operators. Offshore sites are more isolated, often in environmentally extreme locations, and as such are usually more expensive than onshore sites. To identify safe and viable sites for renewable energy production or carbon storage, huge amounts of data must first be assessed.
Geospatial intelligence on wind resource availability, geological and geophysical characteristics, grid connection options, and environmental impact must all be considered when selecting sites for offshore wind. Geospatial intelligence is also critical because in order to get the best view of a potential site, wind data, site characteristics, and information on existing energy infrastructure need to be layered on top of each other and used to inform recommendations and decisions.
Analysing this data means that viable sites can be more easily identified, and unviable ones avoided. But if data is difficult to find and are not in an actionable format, then identifying potential sites is intensely time consuming, difficult, and prone to error – ultimately impacting profitability. If offshore wind is to live up to its full potential as an energy source, the industry must tackle issues around data accessibility and usability.
SE: You say a digital overhaul is required, can you elaborate on this? Do we need to see a change in infrastructure/policies to actually see widespread deployment of data solutions?
SM: Data is the foundation on which offshore projects are safely built. To screen and develop new sites, teams must first access vast amounts of geological, geophysical, oceanographical, meteorological, and environmental data. Such data is often locked away in siloes, making this process far more laborious than it needs to be.
By having as much available data as possible in a single, easily accessible location, and unlocking hidden data from scientific articles and other sources, researchers can use data to its full potential.
Integrating better data practices and deploying user-friendly technology reduces the time and cost of research; for example, by using semantic technologies such as natural language processing, which uses artificial intelligence to scan and analyse text, pulling out relevant information based on the search requirements.
With technologies such as these, researcher time is saved, and data is less likely to be missed. These technologies are key in giving organisations the extra edge and empowering research teams to make confident, data-driven decisions. They also provide an extra layer of trust in research, ensuring data is discoverable, actionable, and accurate.
SE: What are the opportunities and dangers provided by big data for the energy sector?
SM: Data is the currency that will spur on the success of the energy transition. The opportunities provided by data are enormous, and data holds the key to the net-zero energy transition. But with more data constantly being produced, researchers are facing an uphill battle. Without a user-friendly data solution, the time required to conduct data searches and to analyse and interpret the data is huge and only set to increase.
Researchers spend almost as much time searching for articles as actually reading them, averaging more than four hours for searching and only five hours for reading – this is clearly not sustainable and is further compounded by the risk of data being misinterpreted. By embracing digital technology, offshore companies will be able to repurpose their existing expertise and take the next step in energy transition.
SE: Where does Elsevier fit in this?
SM: We help customers move towards achieving their net-zero targets, empowering customers to make data-driven decisions when designing energy transition projects. Elsevier’s Geofacets is a geospatial intelligence solution that allows geoscientists to uncover reliable, actionable geoscience information and data sourced from scientific publications.
It answers complex questions about the surface and subsurface in a modern way to support energy transition projects. Covering everything from companies looking for geologically appropriate conditions to store captured CO2, to those seeking the best placement for offshore wind opportunities.
SE: What is the most important thing that energy corporations should know about data and its uses?
SM: Data can bring us all closer to meeting renewable energy targets and can be used to streamline the energy transition at every stage. In particular, pre-investment research does not have to be cumbersome – through efficient data access and analysis, geological and environmental desk studies, and early-stage analyses of areas of interest can be faster and better.