Geology topics

Drew L. Siler

Publications and source records attributed to Drew L. Siler.

At least 19 recordsLinked to original sources

USGS2023

Structural discontinuities and their control on hydrothermal systems in the Great Basin, USA

Faults are important controls on hydrothermal circulation worldwide. More specifically, structural discontinuities, i.e. locations where faults interact and intersect, host many hydrothermal systems. In the Great Basin, western USA, an extensive characterization effort demonstrated that hydrothermal systems are controlled by one (or more) of eight types of structural discontinuities. Presumably, specific attributes of these structural settings control the generation and maintenance of permeability and porosity, and therefore localize hydrothermal processes. Herein, I examine representative examples of the eight structural settings that host hydrothermal systems in the Great Basin. For each setting, I use a boundary element method to model fault slip on the major faults and track the distribution of stress and strain in the surrounding crust. Results demonstrate that the largest magnitude and most localized stress and strain effects occur in the structural settings that host the largest number of hydrothermal systems; fault stepovers and fault terminations. Structural settings that are common in areas of strike-slip faulting also show localized stress and strain effects. The modelling presented provides process-based explanations for the empirical and conceptual results of regional characterization of Great Basin hydrothermal systems.

Great Basin↗

USGS2023

Three-dimensional geologic map the southeastern Gabbs Valley geothermal area, Nevada

This three-dimensional (3D) geologic map displays the subsurface geology in the upper ~4 kilometers of the Earth’s crust in the southeastern Gabbs Valley geothermal area of west-central Nevada. The 3D map was constructed by integrating the results from detailed geologic mapping, 3D gravity inversion modeling, and potential-field-geophysical studies. This effort was undertaken as part of the Nevada Play Fairway Project, a regional effort to characterize new geothermal resources in the United States. Local data collection and analysis in southeastern Gabbs Valley, Nevada, including the construction of this 3D map, led to the drilling of six temperature gradient wells and identification of previously unknown hydrothermal fluids at 150 meters depth. The measured temperatures, which are as high as 124.9 degrees Celsius, indicate that the southeastern Gabbs Valley hydrothermal system has temperatures that are comparable to geothermal fields that have been developed for electricity generation in the region. We describe the geologic units and structures displayed by the map and discuss the methods used to integrate the geologic and geophysical information into the 3D geologic interpretation. The accompanying map provides horizontal and vertical section views and oblique perspective views from several angles. The digital data for elements of the map, the individual 3D fault surfaces, and stratigraphic surfaces are available from Siler (2022). The accompanying map sheet and video displaying the 3D map are available at https://doi.org/10.3133/sim3498 .

Nevada↗

USGS2022

Modeling subsurface performance of a geothermal reservoir using machine learning

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells—increasing or decreasing the fluid flow rates across the wells—and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. In this study, we describe a new approach combining reservoir modeling and machine learning to produce models that enable such a strategy. Our computational approach allows us, first, to translate sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy, and second, to find optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an “open-source” reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 h, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 s. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs.

Energies↗

USGS2022

Discovering 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 alternative approach based on machine learning (ML) to process a geothermal dataset from southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. Several of these systems are not well characterized because of insufficient existing data and limited past explorative work. This study discovers hidden patterns and relations in the SWNM geothermal dataset to improve our understanding of the regional hydrothermal conditions and energy-production favorability. This understanding is obtained by applying an unsupervised ML algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden signatures characterizing analyzed datasets, (2) the optimal number of these signatures, (3) the dominant data attributes associated with each signature, and (4) the spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, and geothermal attributes at 44 locations in SWNM. Using NMFk, we find data patterns and identify the spatial associations of hydrothermal signatures within two physiographic provinces (Colorado Plateau and Basin and Range) and two sub-regions of these provinces (the Mogollon-Datil volcanic field and the Rio Grande rift) in SWNM. The ML algorithm extracted five hydrothermal signatures in the SWNM datasets that differentiate between low (<90) and medium (90-150)-temperature hydrothermal systems. The algorithm also suggests that the Rio Grande rift and northern Mogollon-Datil volcanic field are the most favorable regions for future geothermal resource discovery. NMFk also identified critical attributes to identify medium-temperature hydrothermal systems in the study area. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored regions. The code to execute the performed analyses as well as the corresponding data can be found at https://github.com/SmartTensors/GeoThermalCloud.jl.

New Mexico↗

USGS2022

Advancing geophysical techniques to image a stratigraphic hydrothermal resource

Sedimentary-hosted geothermal energy systems are permeable structural, structural-stratigraphic, and/or stratigraphic horizons with sufficient temperature for direct use and/or electricity generation. Sedimentary-hosted (i.e., stratigraphic) geothermal reservoirs may be present in multiple locations across the central and eastern Great Basin of the USA, thereby constituting a potentially large base of untapped, economically accessible energy resources. Sandia National Laboratories has partnered with a multi-disciplinary group of collaborators to evaluate a stratigraphic system in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The goal of this study is to inform an optimized strategy for subsequent exploration and development of this and analogous resources. Building from prior Nevada Play Fairway Analysis (PFA), this team is primarily 1) collecting additional geophysical data, 2) employing novel joint geophysical inversion/modeling techniques to update existing 3D geologic models, and 3) integrating the geophysical results to produce a working, geologically constrained thermo-hydrological reservoir model. Prior PFA work highlights Steptoe Valley as a favorable resource basin that likely has both sedimentary and hydrothermal characteristics. However, there remains significant uncertainty on the nature and architecture of the resource(s) at depth, which increases the risk in exploratory drilling. Newly acquired gravity, magnetic, magnetotelluric, and controlled-source electromagnetic data, in conjunction with new and preceding geoscientific measurements and observations, are being integrated and evaluated in this study for efficacy in understanding stratigraphic geothermal resources and mitigating exploration risk. Furthermore, the influence of hydrothermal activity on sedimentary-hosted reservoirs in favorable structural settings (i.e., whether fault-controlled systems may locally enhance temperature and permeability in some deep stratigraphic reservoirs) will also be evaluated. This paper provides details and current updates on the course of this study in-progress.

Geothermal Resources Council Transactions↗

USGS2022

A geophysical characterization of structure and geology of the Northern Granite Springs Valley Geothermal System, Northwestern Nevada

The northern Granite Springs Valley in northwestern Nevada is the focus of recent studies for its potential for hosting undiscovered geothermal resources. Although the area lacks definitive surface manifestations of an active hydrothermal system, previous studies identify this region as having potential for hosting a blind geothermal resource, based on elevated subsurface temperatures and a favorable structural framework of the area. As part of the Nevada Play Fairway Project, we conducted high resolution geophysical surveys to better characterize the valley’s geothermal resources. This included ground magnetic, gravity, magnetotelluric, and rock property studies aimed at mapping and modeling subsurface geology and structure. Various derivative and filtering methods were employed to delineate buried faults and contacts from gravity and magnetic data. A depth to basement gravity inversion reveals that the basin is deepest on the west side of the valley. Flanking the basin to the east is a prominent gravity high interpreted as an intra-basin horst. A new high-resolution ground magnetic survey reveals a prominent elongate NW-trending magnetic high, interpreted as an unexposed subsurface dike swarm situated near the boundary between the basin and horst and confined to basement. Geophysical models help constrain basin fill comprised of Cenozoic sediments and volcanic rocks. These overlie Mesozoic crystalline basement that, in the west, consists of Cretaceous granitic intrusives and, to the east, dominantly Mesozoic metasedimentary rocks. The contact between these basement lithologies is not certain but inferred to coincide with the geophysically mapped dike swarm. This is partly supported by the fact that the dikes, as projected along strike to the northwest, intersect the contact between the Cretaceous intrusions and older Mesozoic basement rocks to the north of the study area. Although the age of the inferred dike swarm is not known, the trend of the anomaly is consistent with some of the Tertiary dikes in the nearby Sahwave Range, suggesting emplacement predated or was coeval with early development of the basin. The coincidence of the geothermal system, horst, dike swarm, and terminating normal fault zone suggests that basin tectonics and hydrothermal activity were influenced by both pre-existing basement structure and recent deformation. This relationship may pertain more generally to other hydrothermal settings throughout the Great Basin. If so, future efforts focused on mapping basement geology and structure may prove important to understanding underlying structural controls on geothermal systems. This work is supporting the next phase of research involving additional 3D geophysical and geologic modeling under the U.S. Department of Energy funded INGENIOUS project. The focus of this new work is on the western flank and structural corners of the horst block, based on evidence from detailed geophysical structural mapping, new shallow temperature data, and detailed 3D geologic and geophysical modeling, all aimed at identifying sites for temperature gradient drilling that may intersect zones with sufficient permeability and temperature to support geothermal development.

Geothermal Resources Council Transactions↗

USGS2021

Bottom-up and top-down control on hydrothermal resources in the Great Basin: An example from Gabbs Valley, Nevada

The Great Basin in the western United States hosts various hydrothermal systems, including both active geothermal systems and ancient systems preserved as mineral deposits. New magnetotelluric and structural geologic data were collected in the Gabbs Valley area of western Nevada to demonstrate the advantage of imaging the full crustal column below known hydrothermal systems. Three-dimensional models are developed and jointly interpreted where the key findings are bottom-up and top-down controls on hydrothermal systems. Bottom-up control is dictated by weaknesses in the brittle-ductile transition that allow hydrothermal fluids to propagate into the crust; these are often collocated with Miocene volcanic structures. Top-down control is dominated by modern Walker Lane and Basin and Range tectonics that control fluid transport through the middle and upper crust. This study demonstrates that the characterization of regional mineral and geothermal resources is better informed by imaging lower crustal structures and preferential pathways to the surface.

Geophysical Research Letters↗

USGS2021

Machine learning to identify geologic factors associated with production in geothermal fields: A case-study using 3D geologic data, Brady geothermal field, Nevada

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid-flow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fluid-flow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k -means clustering (NMF k ), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.

Nevada↗

USGS2021

Three-dimensional geologic map of the Brady geothermal area, Nevada

The three-dimensional (3D) geologic map characterizes the subsurface in the Brady geothermal area in the northern Hot Springs Mountains of northwestern Nevada. We built the 3D map by integrating the results from detailed geologic mapping, seismic-reflection, potential-field-geophysical, and lithologic well-logging investigations completed in the study area. This effort was undertaken to investigate the geologic structure in the geothermal field and geologic controls on hydrothermal circulation. This characterization of the controls on hydrothermal circulation is applicable to the assessment, exploration, and development of analogous geothermal resources. The 3D map area is 4 kilometers (km) wide along the west-northwest-to-east-southeast axis and 6 km wide along the north-northeast-to-south-southwest axis and extends to 1.0 km below sea level, approximately 2.5 km below the land surface. We describe the geologic units and structures in the map area, discuss the methods used to integrate the geologic and geophysical information into the 3D geologic interpretation, and calculate several geologic factors that may aid in our understanding of hydrothermal circulation. Map sheet 1 provides horizontal and vertical section views and oblique perspective views from several angles of the 3D geologic map. Map sheet 2 provides views of derivative calculations based on the 3D geologic data, 3D density of faults, 3D density of fault intersections and terminations, slip tendency on 3D faults, and dilation tendency on 3D faults. We provide digital data for all elements of the map, such as individual 3D fault and stratigraphic surfaces, 3D fault density, 3D fault intersection density, 3D slip tendency on fault surfaces, and 3D dilation tendency on fault surfaces. A brief movie displaying the 3D map is available at https://doi.org/10.3133/sim3469 .

Nevada↗

USGS2021

3-D geologic controls of hydrothermal fluid flow at Brady geothermal field, Nevada, USA

In many hydrothermal systems , fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydraulic conductivity. Vertical connectivity (a throughgoing network of permeable areas that allows advection of heat from depth to the shallow subsurface) is rare and is confined to relatively small volumes that have highly variable spatial distribution. This local compartmentalization of connectivity represents a significant challenge to understanding hydrothermal circulation and for exploring, developing, and managing hydrothermal resources. Here, we present an evaluation of the geologic characteristics that control this compartmentalization in hydrothermal systems through 3-D analysis of the Brady geothermal field in western Nevada. A published 3-D geologic map of the Brady area is used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity. The 3-D distribution of these variables is compared to the distribution of productive and non-productive fluid flow intervals along production wells and non-productive wells via principal component analysis (PCA). This comparison elucidates which geologic and structural variables are most closely associated with productive fluid flow intervals. Results indicate that production intervals at Brady are located: (1) within or near to known and stress-loaded macro-scale faults, and (2) in areas of high fault and fracture density.

Nevada↗

USGS2021

Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data for geologically realistic structural models: Patua Geothermal Field case study

Financial risk due to geological uncertainty is a major barrier for geothermal development. Production from a geothermal well depends on the unknown location of subsurface geological structures, such as faults that contain hydrothermal fluids. Traditionally, geoscientists collect many different datasets, interpret the datasets manually, and create a single model estimating faults' locations. This method, however, does not provide information about the uncertainty regarding the location of faults and often does not fully respect all observed datasets. Previous researchers investigated the use of stochastic inversion schemes for addressing geological uncertainty, but often at the expense of geologic realism. In this paper, we present algorithms and open-source code to stochastically invert five typical datasets for creating geologically realistic structural models. Using a case study with real data from the Patua Geothermal Field, we show that these inversion algorithms are successful in finding an ensemble of structural models that are geologically realistic and match the observed data sufficiently. Geoscientists can use this ensemble of models to optimize reservoir management decisions given structural uncertainty.

Nevada↗

USGS2021

Subsurface characterization and machine learning predictions at Brady Hot Springs

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulations have been conducted in TETRAD-G and CMG STARS to explore different injection and production fluid flow rates and allocations and to develop a training data set for ML. This process included simulating the historical injection and production since 1979 and prediction of future performance through 2040. ML networks were created and trained using TensorFlow based on multilayer perceptron, long short-term memory, and convolutional neural network architectures. These networks took as input selected flow rates, injection temperatures, and historical field operation data and produced estimates of future production temperatures. This approach was first successfully tested on a simplified single-fracture doublet system, followed by the application to the BHS reservoir. Using an initial BHS data set with 37 simulated scenarios, the trained and validated network predicted the production temperature for six production wells with the mean absolute percentage error of less than 8%. In a complementary analysis effort, the principal component analysis applied to 13 BHS geological parameters revealed that vertical fracture permeability shows the strongest correlation with fault density and fault intersection density. A new BHS reservoir model was developed considering the fault intersection density as proxy for permeability. This new reservoir model helps to explore under-exploited zones in the reservoir. A data gathering plan to obtain additional subsurface data was developed; it includes temperature surveying for three idle injection wells at which the reservoir simulations indicate high bottom-hole temperatures. The collected data assist with calibrating the reservoir model. Data gathering activities are planned for the first quarter of 2021.

Nevada↗

USGS2020

Play fairway analysis in geothermal exploration: The Snake River plain volcanic province

The Snake River volcanic province (SRP) has long been considered a target for geothermal development. It overlies a thermal anomaly that extends deep into the mantle and represents one of the highest heat flow provinces in North America, but systematic exploration been hindered by lack of a conceptual model. Play Fairway Analysis (PFA) is a methodology adapted from the petroleum industry that integrates data at the regional or basin scale to define favorable plays for exploration in a systematic fashion. The success of play fairway analysis in geothermal exploration depends critically on defining a systematic methodology that is grounded in theory and adapted to the geologic and hydrologic framework of real geothermal systems. This study focused on identifying three critical resource parameters for exploitable hydrothermal systems in the Snake River Plain: heat source, reservoir and recharge permeability, and cap or seal. Data included in the compilation for Heat were heat flow, the distribution and ages of volcanic vents, groundwater temperatures, thermal springs and wells, helium isotope anomalies, and reservoir temperatures estimated using geothermometry. Permeability was derived from stress orientations and magnitudes, post-Miocene faults, and subsurface structural lineaments based on magnetic and gravity data. Data for Seal included the distribution of impermeable lake sediments and clay-seal associated with hydrothermal alteration below the regional aquifer. These data were used to compile Common Risk Segment (CRS) maps for Heat, Permeability and Seal, which were combined to create a Composite Common Risk Segment (CCRS) map for all of southern Idaho that reflects the risk associated with geothermal resource exploration and helps to identify favorable resource tracks. Our data suggests that important undiscovered geothermal resources may be located in several areas of the SRP, including the western SRP (associated with buried lineaments capped by lacustrine sediment), at lineament intersections in the central SRP, and along the margins of the eastern SRP. These blind resources are associated with temperatures sufficient to support electricity production, and may be exploitable with existing deep drilling technology. We are testing our methodology by drilling a geothermal test well in Camas Prairie, ID, confirm our predictions of permeability and reservoir temperature.

Idaho↗

USGS2020

Geothermal play fairway analysis of the Sou Hills, northern Nevada: A major quaternary accommodation zone in the Great Basin region

To facilitate discovery and development of blind geothermal systems in the Great Basin region, as well as assessment of known systems with surface hot springs, a play fairway approach was developed to evaluate and integrate multiple geologic and geophysical parameters for permeability and heat. Phase 1 of the project produced a geothermal potential map of 96,000 km2 of Nevada. This analysis yielded 24 highly favorable locations with particularly high fairway scores, from which five promising sites were selected for detailed studies. The Sou Hills was chosen as a detailed study area due to a complex structural setting, plethora of Quaternary normal faults, and relatively high rates of both regional strain and slip on Quaternary faults. Our analysis of the Sou Hills utilized: 1) detailed geologic mapping of ~60 km2, 2) reconnaissance mapping of >200 km2, 3) analysis of Quaternary faults, 4) detailed logging of cuttings from four, previously drilled wells (~2,000 m) and integration of ~5,500 m of existing logs from nine other wells, 5) a new gravity survey (355 stations), 6) LiDAR acquisition for 290 km2, 7) a shallow temperature survey (82 stations), 8) interpretation of seven seismic reflection profiles, 9) slip and dilation tendency analyses, and 10) geochemical analyses of 23 water samples. Integration of these datasets shows that the Sou Hills occupies a major accommodation zone between oppositely dipping Quaternary normal fault systems. As such, the area is characterized by multiple, closely-spaced, west- and east-dipping Quaternary normal faults, many of which are favorably oriented for slip and dilation in the current stress regime. Seismic reflection and gravity data show an extensional anticline in northernmost Dixie Valley directly south of the Sou Hills. The anticline marks a zone of multiple intersecting, oppositely dipping normal faults and represents a particularly favorable site for potentially hosting a geothermal system.

Nevada↗

USGS2019

Three-dimensional geologic map of the southern Carson Sink, Nevada, including the Fallon FORGE area

The three-dimensional (3–D) geologic map characterizes the subsurface in the southern Carson Sink region. We created the 3–D map by integrating the results from seismic-reflection, potential-field-geophysical, and lithologic well-logging investigations completed in and around the Fallon FORGE site as part of the U.S. Department of Energy Frontier Observatory for Research in Geothermal Energy (FORGE) initiative from 2015–2018. The FORGE initiative was part of an effort to develop the technologies, techniques, and knowledge needed to make enhanced geothermal systems a commercially viable electricity-generation option for the United States. Geologic units and structures mapped during the Fallon FORGE study, which particularly focused on the Mesozoic basement, were extrapolated to create the 3–D map of the southern Carson Sink area. The 3–D map area is 10 km wide along the east-west and north-south axes and extends 2.5 km below sea level, ~3.7 km below the land surface. Views of the map include horizontal and vertical sections and oblique perspective views from several angles. We describe the geologic units and structures and discuss the methods used to integrate the geologic and geophysical information in a 3–D geologic interpretation. We provide digital data for elements of the map, such as individual 3–D fault and stratigraphic surfaces and surface-fault traces. Input data are available from various data repositories through cited web links. A brief movie displaying the 3–D map is available at https://doi.org/10.3133/sim3437 .

Nevada↗

USGS2019

Three-dimensional geologic mapping to assess geothermal potential: Examples from Nevada and Oregon

Geologic structure plays an important role in controlling fluid flow in geothermal systems. In particular, very complex structural settings, consisting of many closely spaced and intersecting faults, host many geothermal systems. To elucidate the key geologic factors that affect fault-controlled geothermal circulation, it is critical to precisely characterize the structural and stratigraphic geometries in these complex settings. Here, we present a methodology and the results of 3D geologic analyses of two geothermal systems in the Basin and Range, USA. This methodology is a quantitative and geologically focused technique that can be used to precisely characterize geothermal areas, in a time when future geothermal growth demands increased exploration precision and efficiency. Surficial and subsurface geologic and geophysical data are synthesized in the construction of detailed 3D geologic maps of geothermal areas. Based on these 3D geologic maps, we examine several geologic attributes that control permeability development and geothermal fluid flow along faults. We use the stress state of faults and the distribution of structural discontinuities (i.e., fault intersections and fault terminations) to identify locations of upflow along faults in these geothermal systems. These results and the methodology presented herein are directly applicable to structurally controlled geothermal fields in the Basin and Range and worldwide. As development focus shifts toward blind geothermal resources, integration of precisely characterized subsurface structural information into exploration methods will be increasingly critical to continued growth in geothermal exploration and development.

Nevada, Oregon↗

USGS2019

Uncertainty and risk evaluation during the exploration stage of geothermal development: A review

Quantifying and representing uncertainty for geothermal systems is often ignored, in practice, during the exploration phase of a geothermal development project. We propose that this occurs potentially because the task seems so formidable. The primary goal of this paper is to initiate a dialogue within the geothermal community about: which geothermal uncertainties should receive the most attention and which uncertainty analysis methods could provide the greatest benefit for the advancement of the geothermal energy industry. Specifically, in this paper, we review uncertainty quantification techniques that are applicable to geothermal exploration. In general, uncertainty associated with data acquisition/processing (i.e., objective uncertainty) is small compared to the uncertainty in interpretational space (i.e., subjective uncertainty) that lies between data points where extrapolation is required. Therefore, it is important to classify, assess, and quantify uncertainty to help select strategies to reduce uncertainty and to better gauge the impact that separate uncertainties have on the overall likelihood of project success. The discipline of geostatistics provides multiple quantitative methods for producing stochastic models which adhere to measured data and spatial correlation. The petroleum industry has successfully used both geostatistics and decision analysis methods to combine diverse and multiple types of uncertainties. We argue that instead of one single and final interpretation of the geothermal system, numerous interpretations may be more indicative of the possible subsurface scenarios, and these different scenarios can be evaluated using decision analyses and value of information methodologies. Finally, we recommend that the potential power generation of a geothermal reservoir should be grounded in the geologic data and modeling for a specific field and their estimated uncertainties.

Geothermics↗

USGS2019

Discovering blind geothermal systems in the Great Basin Region: An integrated geologic and geophysical approach for establishing geothermal play fairways: All phases

Most geothermal resources in the Great Basin region of the western USA are blind, and thus the discovery of new commercial-grade systems requires synthesis of favorable characteristics for geothermal activity. The geothermal play fairway concept involves integration of multiple parameters indicative of geothermal activity to identify promising areas for new development. This project integrated multiple datasets to apply the play fairway concept and assess geothermal potential in a large region of the Great Basin in Nevada. It is therefore referred to as the Nevada play fairway project. This project was a strong collaborative effort between several organizations, led by the Nevada Bureau of Mines and Geology at the University of Nevada, Reno, but with key support from the U.S. Geological Survey, ATLAS Geosciences, Inc,, Hi-Q Geophysical, Inc., Lawrence Berkeley National Laboratory, Utah Geological Survey, and Innovative Geothermal Ltd. In Budget Period 1 of this project, available data for nine geologic, geochemical, and geophysical parameters were initially synthesized to produce a new detailed geothermal potential map of 96,000 km2 from west-central to eastern Nevada (Figure 1). These parameters were grouped into subsets and individually weighted (Figure 2) to delineate rankings for local permeability, intermediate permeability, regional permeability, and thermal potential, which collectively defined geothermal play fairways (i.e., most likely locations for significant geothermal fluid flow). This initial work was aimed at reducing the risks in regional exploration and therefore facilitating discovery of new commercial-grade systems in blind settings, as well as in areas with surface expressions of geothermal activity. Budget Period 2 of the project involved detailed analysis of some of the most promising areas identified in Phase 1. Twenty-four highly prospective areas, including both known undeveloped systems and previously undiscovered potential blind systems, were identified for further analysis (Figures 3 and 4). After reconnaissance of these areas, five of the most promising sites were selected for detailed studies. Multiple techniques were employed in the detailed studies, including geologic mapping, shallow temperature surveys, gravity surveys, Lidar, geochemical studies, seismic reflection analysis, and 3D modeling. The goal of the detailed studies was to identify specific areas with the highest likelihood for high permeability and thermal fluids, such that drill sites could be targeted. Three main sets of predictive maps were generated for each detailed study area: 1) play fairway maps, 2) play fairway error maps, and 3) direct evidence maps. Local- and intermediate-scale permeability models were revised to reflect results of the detailed geologic, geophysical, and geochemical analyses. Budget Period 3 of the project involved more detailed geophysical analyses and temperature-gradient (TG) drilling in southeastern Gabbs Valley and northern Granite Springs Valley (Figure 4), deemed the two most promising sites, with the goal of providing preliminary validation of the play fairway methodology. In southeastern Gabbs Valley, the collocation of a favorable structural setting (displacement transfer zone and fault intersections), Quaternary faults, intersecting and terminating gravity gradients, magnetic low, shallow (2 m) temperature anomaly, low resistivity anomaly, and promising geothermometry from nearby water wells provided evidence for a blind system. Drilling of six TG holes defines an apparent geothermal system at this locality with temperatures as high as 124°C at 152 m. This system is blind, with no surface hot springs, fumaroles, or paleo-geothermal deposits. For northern Granite Springs Valley, a favorable structural setting (termination of a major Quaternary normal fault), terminating gravity gradient, magnetic gradient, newly discovered sinter deposits, nearby warm water wells, previously drilled TG holes in the vicinity, and promising geothermometry suggest a hidden system. Drilling of six new TG holes yields temperatures of ~96°C at ~250 m, suggesting the presence of a geothermal system. Major lessons learned in the course of this project include: 1) initially identified sites commonly include multiple favorable structural settings at a finer scale; 2) promising sites in Cenozoic basins cannot be recognized without detailed geophysical surveys; and 3) play fairway analysis should be refined as the exploration program vectors into the most promising sites and finer-scale data are acquired. In addition to producing copious amounts of data, this project resulted in 16 published papers, 10 abstracts, more than 40 presentations across the U.S. and abroad (including several keynote addresses), 2 Masters theses, and 7 media reports.

Nevada↗