Erick R Burns
Erick is a Research Hydrologist at the USGS Geology, Minerals, Energy, and Geophysics Science Center. He specializes in the development of methods and tools for analysis and simulation of groundwater and heat flow in the subsurface, particularly in the volcanogenic terranes of California, Idaho, Oregon, and Washington.
Erick Burns is a Research Geologist with the USGS Geology, Minerals, Energy, and Geophysics Science Center. His research experience is varied, including groundwater flow and transport, geothermal energy, geostatistical methods and stochastic analysis, process thermodynamics, agricultural water pollution, and seawater intrusion. Additionally, Erick has taught hydrology and geostatistics courses.
Non-USGS Partners:
- U.S. Department of Energy - Geothermal Technologies Office
Education and Certifications
Ph.D. Bioresource Engineering, Oregon State University, 2004
M.S. Mathematics, Oregon State University, 2004
M.S. Hydrologic Sciences (Groundwater), University of Nevada - Reno, 1996
B.S. Geology (extended major: Geophysics), Northern Arizona University, 1994
Science and Products
Renewable Resilience: City-Scale Geothermal Energy Everywhere
Geothermal Resource Investigations Project
Hydrogeologic and Geothermal Conditions of the Northwest Volcanic Aquifers
Columbia Plateau Groundwater Availability Study
Three-dimensional temperature model of the Great Basin, USA
Maps of elevation trend and detrended elevation for the Great Basin, USA
MODFLOW-NWT model used to evaluate the groundwater availability of the Columbia Plateau Regional Aquifer System, Washington, Oregon, and Idaho
Wells and water levels used in the Columbia Plateau Regional Aquifer System Study, Idaho, Oregon, and Washington
Heat flow maps and supporting data for the Great Basin, USA
Compiled reference list to support reservoir thermal energy storage research
SUTRA model used to evaluate Saline or Brackish Aquifers as Reservoirs for Thermal Energy Storage in the Portland Basin, Oregon, USA
Updated three-dimensional temperature maps for the Great Basin, USA
Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions
Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify area
Cursed? Why one does not simply add new data sets to supervised geothermal machine learning models
Recent advances in machine learning (ML) identifying areas favorable to hydrothermal systems indicate that the resolution of feature data remains a subject of necessary improvement before ML can reliably produce better models. Herein, we consider the value of adding new features or replacing other, low-value features with new input features in existing ML pipelines. Our previous work identified st
Predicting large hydrothermal systems
We train five models using two machine learning (ML) regression algorithms (i.e., linear regression and XGBoost) to predict hydrothermal upflow in the Great Basin. Feature data are extracted from datasets supporting the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems project (INGENIOUS). The label data (the reported convective signals) are extracted from meas
Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability
Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis
Geologic energy storage
Introduction As the United States transitions away from fossil fuels, its economy will rely on more renewable energy. Because current renewable energy sources sometimes produce variable power supplies, it is important to store energy for use when power supply drops below power demand. Battery storage is one method to store power. However, geologic (underground) energy storage may be able to retain
City-scale geothermal energy everywhere to support renewable resilience – A transcontinental cooperation
When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates
New maps of conductive heat flow in the Great Basin, USA: Separating conductive and convective influences
Effects of structure and volcanic stratigraphy on groundwater and surface water flow: Hat Creek basin, California, USA
Discovering hidden geothermal signatures using non-negative matrix factorization with customized k-means clustering
Science and Products
- Science
Renewable Resilience: City-Scale Geothermal Energy Everywhere
Despite the proven efficacy of geothermal energy as a city-scale heating and cooling resource, the relative newness of most city-scale applications using diverse technologies has resulted in limited widespread adoption. We aim to develop authoritative information suitable for city-managers and other decision-makers. Geothermal resources are ubiquitous and diverse, with technologies available botGeothermal Resource Investigations Project
Geothermal energy is a significant source of renewable electric power in the western United States and, with advances in exploration and development technologies, a potential source of a large fraction of baseload electric power for the entire country. This project focuses on advancing geothermal research through a better understanding of geothermal resources and the impacts of geothermal...Hydrogeologic and Geothermal Conditions of the Northwest Volcanic Aquifers
Although sparsely populated, this area in southeastern Oregon, northeastern California, northwestern Nevada, and southeastern Idaho has high geothermal heat flow that may be used to generate large amounts of electricity.Columbia Plateau Groundwater Availability Study
The Columbia Plateau Regional Aquifer System (CPRAS) covers about 44,000 square miles of eastern Oregon and Washington and western Idaho. The primary aquifers are basalts of the Columbia River Basalt Group and overlying basin-fill sediments. Groundwater availability issues in the basin include: 1) widespread water-level declines caused by pumping, 2) reduction in base flow to rivers and associated... - Data
Three-dimensional temperature model of the Great Basin, USA
As part of the periodic update of the geothermal energy assessments for the USA (e.g., last update by Williams and others, 2008), a new three-dimensional temperature map has been constructed for the Great Basin, USA. Williams and DeAngelo (2011) identified uncertainty in estimates of conductive heat flow near land surface as the largest contributor to uncertainty in previously published temperaturMaps of elevation trend and detrended elevation for the Great Basin, USA
Topography provides information about the structural controls of the Great Basin and therefore information that may be used to identify favorable structural settings for geothermal systems. Specifically, local relative topography gives information about locations of faults and fault intersections relative to mountains, valleys, or at the transitions between. As part of U.S. Geological Survey efforMODFLOW-NWT model used to evaluate the groundwater availability of the Columbia Plateau Regional Aquifer System, Washington, Oregon, and Idaho
A three-dimensional groundwater flow model (MODFLOW-NWT) of the Columbia Plateau Regional aquifer (CPRAS) in Washington, Oregon, and Idaho was developed to provide an integrated understanding of the hydrologic system to implement effective water-resource management strategies. The U.S. Geological Survey (USGS) Groundwater Resources Program assessed the groundwater availability as part of a nationaWells and water levels used in the Columbia Plateau Regional Aquifer System Study, Idaho, Oregon, and Washington
These data describe the wells and groundwater level elevations compiled for the Columbia Plateau Regional Aquifer Study (CPRAS). The well data included are well ids used in the study, the X and Y coordinates of each well, in feet, in Washington State Plane South NAD 1983 coordinate system (zone 4602), land-surface elevation, in feet, of each well in North American Vertical Datum of 1988 (NAVD 88),Heat flow maps and supporting data for the Great Basin, USA
Geothermal well data from Southern Methodist University (SMU, 2021) and the U.S. Geological Survey (Sass et al., 2005) were used to create maps of estimated background conductive heat flow across the greater Great Basin region of the western US. The heat flow maps in this data release were created using a process that sought to remove hydrothermal convective influence from predictions of backgrounCompiled reference list to support reservoir thermal energy storage research
This text file (Reference_List_V1.txt) lists references that describe relevant characteristics for reservoir thermal energy storage (RTES) research in the United States. References are grouped by corresponding city, including: Albuquerque, New Mexico; Charleston, South Carolina; Chicago, Illinois; Decatur, Illinois; Lansing, Michigan; Memphis, Tennessee; Phoenix, Arizona; and Portland, Oregon. TheSUTRA model used to evaluate Saline or Brackish Aquifers as Reservoirs for Thermal Energy Storage in the Portland Basin, Oregon, USA
This archive documents five 30-year SUTRA simulations summarized in Burns at al. (2020), and provides output from one short (2-year) simulation to allow verification that the archive model code runs properly. A modified version of SUTRA 2.2 was used to evaluate Reservoir Thermal Energy Storage by simulating layered system conditions (grid spacing varies depending on simulation run time to prevent - Publications
Filter Total Items: 36
Updated three-dimensional temperature maps for the Great Basin, USA
As part of the periodic update of the geothermal energy assessments for the USA (e.g., last update by Williams and others, 2008), a new three-dimensional temperature map has been constructed for the Great Basin, USA. Williams and DeAngelo (2011) identified uncertainty in estimates of conductive heat flow near land surface as the largest contributor to uncertainty in previously published temperaturAuthorsErick Burns, Jacob DeAngelo, Colin F. WilliamsDon’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions
Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify area
AuthorsPascal D. Caraccioli, Stanley Paul Mordensky, Cary R. Lindsey, Jacob DeAngelo, Erick Burns, John LiporCursed? Why one does not simply add new data sets to supervised geothermal machine learning models
Recent advances in machine learning (ML) identifying areas favorable to hydrothermal systems indicate that the resolution of feature data remains a subject of necessary improvement before ML can reliably produce better models. Herein, we consider the value of adding new features or replacing other, low-value features with new input features in existing ML pipelines. Our previous work identified st
AuthorsStanley Paul Mordensky, Erick Burns, John Lipor, Jacob DeAngeloPredicting large hydrothermal systems
We train five models using two machine learning (ML) regression algorithms (i.e., linear regression and XGBoost) to predict hydrothermal upflow in the Great Basin. Feature data are extracted from datasets supporting the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems project (INGENIOUS). The label data (the reported convective signals) are extracted from meas
AuthorsStanley Paul Mordensky, Erick Burns, Jacob DeAngelo, John LiporDetrending Great Basin elevation to identify structural patterns for identifying geothermal favorability
Topography provides information about the structural controls of the Great Basin and therefore information that may be used to identify favorable structural settings for geothermal systems. The Nevada Machine Learning Project (NVML) tested the use of a digital elevation map (DEM) of topography as an input feature to predict geothermal system favorability. A recent study re-examines the NVML data,AuthorsJacob DeAngelo, Erick Burns, Stanley Paul Mordensky, Cary Ruth LindseyExploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis
Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that prodAuthorsConnor M. Smith, James E. Faulds, Stephen C. Brown, Mark Coolbaugh, Jacob DeAngelo, Jonathan M.G. Glen, Erick Burns, Drew Lorenz Siler, Sven Treitel, Eli Mlawsky, Michael Fehler, Chen Gu, Bridget F. AylingGeologic energy storage
Introduction As the United States transitions away from fossil fuels, its economy will rely on more renewable energy. Because current renewable energy sources sometimes produce variable power supplies, it is important to store energy for use when power supply drops below power demand. Battery storage is one method to store power. However, geologic (underground) energy storage may be able to retain
AuthorsMarc L. Buursink, Steven T. Anderson, Sean T. Brennan, Erick R. Burns, Philip A. Freeman, Joao S. Gallotti, Celeste D. Lohr, Matthew D. Merrill, Eric A. Morrissey, Michelle R. Plampin, Peter D. WarwickCity-scale geothermal energy everywhere to support renewable resilience – A transcontinental cooperation
Cities have important and varying incentives to transform their energy sector to all-electric with low carbon emissions. However, they often encounter a number of impediments when attempting to implement such a change. For example, while urban areas have the highest energy demand-density, cities often lack the space for installing additional energy generation and/or long-duration energy storage syAuthorsGregor Goetzl, Erick R. Burns, Andrew J. Stumpf, Yu-Feng Lin, Amanda Kolker, Maciej R. Klonowski, Cornelia Steiner, Ryan Cain Cahalan, Jeff D. PepinWhen less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates
Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of errAuthorsStanley Paul Mordensky, John Lipor, Jacob DeAngelo, Erick R. Burns, Cary Ruth LindseyNew maps of conductive heat flow in the Great Basin, USA: Separating conductive and convective influences
Geothermal well data from Southern Methodist University and the U.S. Geological Survey (USGS) were used to create maps of estimated background conductive heat flow across the Great Basin region of the western United States. These heat flow maps were generated as part of the USGS hydrothermal and Enhanced Geothermal Systems resource assessment process, and the creation process seeks to remove the iAuthorsJacob DeAngelo, Erick R. Burns, Emilie Gentry, Joseph F. Batir, Cary Ruth Lindsey, Stanley Paul MordenskyEffects of structure and volcanic stratigraphy on groundwater and surface water flow: Hat Creek basin, California, USA
Hydrogeologic systems in the southern Cascade Range in California (USA) develop in volcanic rocks where morphology, stratigraphy, extensional structures, and attendant basin geometry play a central role in groundwater flow paths, groundwater/surface-water interactions, and spring discharge locations. High-volume springs (greater than 3 m3/s) flow from basin-filling (<800 ka) volcanic rocks in theAuthorsMarina Francesca Marcelli, Erick R. Burns, L. J. Patrick Muffler, Andrew J Meigs, Jennifer A. Curtis, Christian E. TorgersenDiscovering hidden geothermal signatures using non-negative matrix factorization with customized k-means clustering
Discovery of hidden geothermal resources is challenging. It requires the mining of large datasets with diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used play fairway analysis approach typically incorporates subject-matter expertise to analyze regional data to estimate geothermal characteristics and favorability. We demonstrate an alternatiAuthorsVelimir V. Vesselinov, Bulbul Ahmmed, Maruti K. Mudunuru, Jeff D. Pepin, Erick R. Burns, Drew L. Siler, Satish Karra, Richard S. Middleton - News