Digital Winner

Our project provides an engaging introduction to geothermal energy. Designed for a public audience without prior knowledge of geothermal, our piece visually presents current challenges and opportunities for the expansion of geothermal energy development.

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Print Winner

Our poster summarizes the results of a Geothermal Locality Index model that pinpoints accessible geothermal resources near large numbers of people who need heat and energy. We used a GIS overlay fuzzy model to rank U.S. counties based on (1) presence of at least 80?C temperatures, (2) within the ideal 3,000-meter depth, (3) near residents who have high heat and energy demands (4) in densely populated areas. Our goal was to find ideal locations for public education on low-temperature enhanced geothermal resources.

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Our method was to proceed with site selection based on a less densely populated area of Colorado. We stuck to target areas visible in some GDR.openei.org data. After selecting the Glenwood Springs target area for direct use, we added a 10 km buffer to expand our exploration. Glenwood Springs has several adjacent towns within a short distance, which gave the resources more grid offset potential. We looked through magnetic, gravity, gradient, heat-at-depth maps, geologic information, faults, water resources, and surface manifestations. From those we simplified maps of the area for public presentation. Further, we built out a 3D version of the conceptual model with some freeware. Using a collection of Glenwood Springs rock properties, geothermometry reports and feasibility studies from the area, we ran the techno-economic simulation through GEOPHIRES. GEOPHIRES pointed out a potential of approximately 4 times current production in the resource area, using a deviated well doublet into the controlling fault(s).

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Geothermal energy in southeast Alaska is a vastly underutilized resource, considering the region’s geology, which features hundreds of volcanos and hot springs. The study site includes Chichagof Island (to the north) and Baranof Island (to the south), chosen because it hosts nine hot spring areas, the Mt. Edgecumbe volcano and hundreds of mapped faults, all relatively close to population centers. The submission is in the form of an arcGIS story map for logic and clarity. The format is a combination of digital and static maps, given that most of the analysis was performed on static maps. Our conclusions were that two regions in the study site area have potential to produce geothermal energy and nine regions have the ability to utilize direct use geothermal.

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Our team wanted to look at the potential availability of geothermal sources in the western United States and determine what locations would be best suited for geothermal development. We specifically looked at towns and cities that currently use non-renewable power sources to determine if they could slowly be replaced by geothermal technology. We first mapped geothermal source data and ranked areas of high and low potential. We then analyzed population densities and mapped them in areas within the good to high geothermal range. Next, we categorized and mapped non-renewable power plant technologies in these prioritized areas. We also reviewed and mapped areas of research for potential geothermal use.

The final product was a visually appealing map that showcases geothermal layers overlaid with population densities, cities and towns prioritized for geothermal development potential.

View the project here.

Until recently geothermal energy was only commercially viable near volcanoes and active plate boundaries, and geoscientists scouted these locations using GIS. However, with the advent of enhanced geothermal systems (EGS) vastly expanding the feasible locations for geothermal energy generation the question arises: If geothermal energy can be found anywhere, is GIS mapping of geothermal resources still necessary? We address this question in a clear, step-by-step manner that is accessible to beginner audiences as well as informative for geothermal researchers. We begin by reviewing what geothermal energy is, its uses and advantages, and the role GIS has played in finding geothermal resources. Then we explore the development of EGS, its effect on the field of geothermal energy, and on the role of GIS mapping. Along the way, visitors are invited to explore GIS maps and additional geothermal geospatial data, which are incorporated into the text.

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The goal of our project is to grow understanding of geothermal energy resources in the United States by using GIS to optimize access to information in the Geothermal Data Repository (GDR). We improve access to submissions to the GDR by visualizing their location and giving the viewer context. We make submissions easy to filter — by time, public availability, and major geothermal resource categories — optimizing a user’s ability to find the information they are looking for. And we analyze spatial patterns of research submissions against other important data, like enhanced geothermal potential and the existence of current or developing geothermal stations, to find locations where the value of new research might be highest. By using GIS to visualize this information for the GDR user, we created a tool to quickly synthesize existing information geographically and target new research and exploration efforts where their impact will be high. Our project consists of a custom-built landing page, explaining the thinking behind our project, project goals, and a link to our online mapping app, custom built using the ArcGIS API for Javascript. The primary data source in our project is the GDR submission metadata, obtained from Jon Weers, who works on the GDR. We also used data sources from NREL: EGS potential, operating, and developing geothermal plants. Beyond playing with the filter options, clustering, and layer toggles in our map, we encourage you to poke through individual data points, EGS potential polygons, and research potential hexes. Selecting any single data point in our map pops up a dialogue box that will help you explore further. This map helps us identify the “known knowns” about geothermal energy resources in the U.S. By looking at holes in this information, it also helps us see the “known unknowns.” Targeting research, exploration and funding to these areas is the fastest way to a more complete understanding of our nation’s geothermal energy resources.

View the project here.

The first place team, BALO Data Science Team, was a collaboration between DePaul University and Georgia Institute of technology and included team members: Sierra Sellman and Michelle Rodrigue.

The winning team, comprised of data science students with backgrounds in geographic information systems, submitted data visualizations targeting an audience unfamiliar with enhanced geothermal systems (EGS) and machine learning. Figure 5 is a screenshot from the team’s submission. Their final portfolio suitability map and proposed well location was based upon robust analyses using Python and ESRI’s ArcMap, ArcScene and strong understanding of the FORGE data.

The BALO Data Science team submission can be found at the following link:
ArcGIS

The second place team, W-Team, was from the Colorado School of Mines and included team members Bane Sullivan and Adam Kinard.

This team created a suite of open-source Python packages, enabling available datasets to be incrementally integrated into a 3D scene. Tools used included The Open Mining Format, ParaView, SGeMS, and SimPEG, along with additional tools made by the team itself. Figure 6 is a screenshot from the team’s submission. Three-dimensional (3D) visualizations such as this submission could enable researchers and scientists to rapidly explore data, communicate findings, and facilitate the reproducibility of results.

The W-Team submission can be found at the following link:
Vimeo

The third place team, Stanford Geothermal Gals, was from Stanford University and included team members Ahinoam Pollack and Ayaka Abe.

This team’s submission was geared toward an audience with little knowledge of geothermal and laid out the basic concepts of geothermal exploration and well siting using lithology and subsurface temperatures. Figure 7 is a screenshot from the team’s submission. The visualization portfolio was created in Tableau, and can be easily integrated into a classroom curriculum.

The Stanford Geothermal Gals’ submission can be found at the following link:
Tableau Viz

The Grand Prize Winning Team was from Carnegie Mellon University. Members Tiffany Lai, Susie Lee, Marisa Lu made up the team, Infinity and Below.

Quotes from team: “By researching the advantages of it and comparing it to other renewable energies, I learned that geothermal energy is not only cost effective, but also a viable solution to a cleaner, greener energy future. Its benefits outweigh many other renewable energy sources, which was something I had never considered before.”
“Geothermal systems is a practical solution to the energy crisis as a renewable resource that is able to provide more energy than the remaining oil and gas. EGS is stable as well in terms of cost as it does not depend on other sources in order to operate. Geothermal energy is an alternative resource that should be heavily considered.”

View the full infographic here

The University 1st Place Winning Team was from Yale University. Members Dana Patterson, Daniel Shapiro, Christopher Paolini made up the team, YalEnergy Rockstars. The link below opens the team’s winning entry, “A Humanistic Portrait of Geothermal Energy”.

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The High School 1st Place Winning Team was from Eleanor Roosevelt High School. Members Edward Belsoi, Rokhaya Niang, Hunter Whaples made up the team, Team Roosevelt.

Quote from team: ” I have learned more about specific processes that make geothermal energy possible as well as the possible future scope of geothermal energy.”  “I realize that geothermal has applications far beyond electricity – in the realms of agriculture, civil engineering, and basic building design.”

View the full infographic here