As stakeholders in energy activities seek to improve resource recovery or storage, minimize risks and reduce adverse impacts, they increasingly rely on powerful computing tools that provide critical science-based predictions.

NETL’s geo-data science experts have developed seven novel big and small data computing solutions now available for licensing that address comprehensive Earth, energy, environmental and engineering needs. These innovative tools offer accurate science-based data, analysis and prediction for Earth-energy applications – including big data and machine learning capabilities – to industry, governments, researchers and other stakeholders requiring research-driven data for energy operations.

Among the recently trademarked and copyrighted tools:

• The Variable Grid Method^©(VGM) leverages geographic information system (GIS) capabilities to simultaneously visualize and quantify spatial data trends and underlying data uncertainty, allowing stakeholders to better evaluate resources, assess potential impacts, understand trends, calculate project feasibility, identify knowledge gaps and more.
• The Cumulative Spatial Impact Layers™ (CSIL) tool integrates data sets related to various social, economic, and environmental information for a region to rapidly assess potential impacts and inform environmental risk reduction efforts.
• The Spatially Weighted Impact Model™ (SWIM) is a decision support tool that evaluates relationships for various decision strategies and potential outcomes and allows users to incorporate weights as it ranks and compares scenarios based on interactions among human and natural systems and other variables.
• The Subsurface Trend Analysis™ (STA) tool combines geostatistical analyses with a prior geologic knowledge of the subsurface to provide an understanding of subsurface characteristics where data is limited.
• The Blowout Spill Occurrence Model^©(BLOSOM) is a comprehensive modeling suite for blowout and spill events that addresses jet/plume behavior, high pressures, gas and hydrate dynamics, droplet-size distributions, and subsurface plume formation to provide a greater understanding of how hydrocarbon leaks are transported throughout offshore systems.
• The Spatially Integrated Multivariate Probability Assessment™ (SIMPA) tool evaluates trends and knowledge gaps associated with engineered natural systems in support of risk, resource and impact assessments.
• The Energy Data eXchange™ (EDX) is NETL’s online collection of capabilities and resources that advance research and customize energy-related needs, created to support collaborative research efforts and technology transfer of research products. All the tools available for licensing can be accessed via EDX.

As NETL strives to develop technological solutions to the nation’s energy challenges, the Lab is exercising its renowned expertise to lead the development of advanced data computing solutions for energy applications. To date, NETL researchers have used these tools and capabilities in studies related to carbon storage, rare earth elements, oil and natural gas, offshore spill prevention, geothermal, and advanced materials applications. They are available for use by scientists, industry and regulators to inform decisions that increase profitability, guide safety and maintenance decisions, forecast risks, and optimize well/facility designs.

This suite of machine learning, big data and advanced visualization tools is flexible and can be paired with commercial and other open-source capabilities, offering stakeholders efficient, flexible, data-driven methods to assess and reduce risks associated with energy exploration and production to ensure the health, safety and security of all Americans.