The photo above is a view "underground". This Real-time Four-Dimensional Subsurface Imaging Software created at the Pacific Northwest National Laboratory utilizes E4D-RT to image fractures in real time. This software provides faster, more accurate interpretations of data from simulation models, and improves the cost competitiveness of EGS development.

Energy sources originating from beneath the Earth’s surface satisfy over 80% of total U.S. energy needs, and a key energy challenge today is to ensure safe, sustainable, and affordable availability of these natural resources in the subsurface. A key issue, however, is being able to “see” what is in the subsurface. The Department of Energy (DOE) is busy at work funding R&D to advance technologies that allow access to this reliable, secure energy source under the SubTER crosscut - a DOE initiative that unites five key DOE agencies in a collaborative effort to ultimately improve our nation’s energy security and availability.

SubTER is providing solutions to subsurface challenges by dramatically accelerating technology development with the aim of achieving mastery of subsurface processes. Next generation advances in subsurface technologies will enable increases in domestic energy supplies, including more than 100 gigawatts of renewable geothermal energy from conventional hydrothermal and enhanced geothermal systems (EGS) - man-made reservoirs created by drilling wells thousands of feet below the earth to access hot rock at the earth’s crust.

Before the widespread development of EGS can occur, however, the high upfront exploration and installation costs must be reduced dramatically. Moving one step closer, researchers at the Pacific Northwest National Laboratory (PNNL) successfully developed a “tool” called E4D-RT processing with the ability to “see underground”, or better image the subsurface, through a research and development project funded by DOE’sOffice of Science and Office of Environmental Management.  This tool provides faster, more accurate interpretations of data from simulation models, and improves the cost competitiveness of EGS development. PNNL and Sandia National Laboratories (SNL) successfully imaged a fracture network that was created using Sandia’s explosive technology in a SubTER project titled “Imaging Fracture Networks Using Joint Seismic and Electrical Change Detection Techniques.”

As a co-principal investigator, PNNL used E4D-RT to image the fractures in real time. Using the data generated by the E4D-RT tool, researchers are able to improve current models used to predict fracture networks. Through the use of E4D-RT, "snapshots" of subsurface conditions are collected by measurements made at the surface or by electrodes inserted in boreholes that pass an electrical current through the material being studied and record how difficult it is for that electrical current to move through the material.

These models are important for geothermal energy investors, decision makers, and stakeholders because it reduces uncertainty and helps to more accurately target where geothermal wells should be drilled. Using this technology is one of the many steps that will help reduce these costs and make widespread EGS and geothermal power production a reality.

The software accomplishes what no other existing commercial subsurface modeling software does: it combines supercomputers to analyze large-scale problems with data processing; provides real-time imaging that allows investigators to understand subsurface processes at the time they are occurring; and enables the modeling of buried metallic infrastructure.

This Real-time Four-Dimensional Subsurface Imaging Software and its inventor, PNNL scientist Timothy C. Johnson, were recognized November 3, 2016 at the R&D 100 Awards. “It’s very much like medical imaging. One of the unique things that we’ve done is bring high performance computing to this problem. We have sensors in the field that are monitoring, and then this information is sent to the super computers that process it. Then, they deliver data back to the field in near real-time. That’s really, really powerful. We can do big imaging problems, and we can do them really fast,” Johnson noted.