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NETL Researchers Publish Novel Geospatial Data Science Method in the Journal of Structural Geology for Predicting Faults and Fractures
Journal of Structural Geology

A novel geospatial data method developed by NETL researchers for modeling and predicting geologic structural complexity within the subsurface has been published in the Journal of Structural Geology. By helping to develop better tools and techniques to predict the storage and behavior of carbon dioxide, natural gas and other resources within the subsurface, NETL’s innovative research is enabling hydrocarbon extraction efforts to operate cheaper and more efficiently while leaving a lighter environmental footprint.

The data science method developed by the Lab aims to improve predictions in areas both with and without high-resolution subsurface data through the development of a knowledge-data framework and leveraging the Spatially Integrated Multivariate Probabilistic Assessment (SIMPA) tool and methodology. The process of developing the data framework puts data sets into spatial arrays suitable for both the software’s processing capabilities and the fuzzy logic modeling system within the SIMPA tool.

SIMPA is a Python-based fuzzy logic tool designed to help assess the likelihood of a variable of interest, such as fluid or gas migration pathways through the subsurface. Fuzzy logic is a technique that enables control devices to think more like humans, which helps in the automation of systems that previously required constant human monitoring and intervention. Fuzzy logic tools accommodate changes in machine functions required by product changeovers without the need to program new settings.

Results derived from SIMPA can improve the prediction of the magnitude and extent of natural and man-made subsurface flow pathways, which can improve assessments and industry decision making. Most notably, SIMPA can offer new insights into areas with little data to help inform oil and natural gas site selection and production, evaluate leakage risks and more.

In an example application and validation, this approach successfully predicted areas of higher potential for previously undetected faults and fracture zones to exist at a site in Oklahoma. Ultimately, this software can provide a new framework for assessing structural complexity and thereby improve decision making associated with a variety of subsurface applications, including carbon storage, induced seismicity, geothermal resources and other interests of the energy industry.

“By equipping stakeholders with a better tools for understanding the geological complexities within the subsurface, such as faults and fractures, we can open many doors simultaneously,” said Kelly Rose, a geo-data scientist on NETL’s GeoAnalysis & Monitoring Team who worked on the model. “Whether used by members of industry or policymakers, this software can lower the costs and expenditure of time and resources that would otherwise be required to analyze the subsurface, leveling the playing field for all involved.”

The new method is just one example of work conducted by NETL’s scientists and engineers to power the future using the nation’s subsurface resources in a safe and sustainable manner. More information on the software featured in Journal of Structural Geology can be viewed here.

NETL is a U.S. Department of Energy national laboratory that produces technological solutions for America’s energy challenges. From developing creative innovations and efficient energy systems that make coal more competitive, to advancing technologies that enhance oil and natural gas extraction and transmission processes, NETL research is providing breakthroughs and discoveries that support domestic energy initiatives, stimulate a growing economy, and improve the health, safety, and security of all Americans. Highly skilled men and women at NETL’s sites in Albany, Oregon; Anchorage, Alaska; Houston, Texas; Morgantown, West Virginia; and Pittsburgh, Pennsylvania conduct a broad range of research activities that support DOE’s mission to advance the national, economic, and energy security of the United States.