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DOE OSTI2019

Earthquake Hydrogeology

Hydrologic responses to earthquakes such as streamflow increases, water-level changes, and changes in geyser eruption frequency often reflect changes in permeability caused by seismic waves. The dynamic nature of permeability, as revealed by coseismic hydrologic phenomena, offers implications for groundwater systems, geothermal resources, mineral resources, and geologic hazards. Assessment of water-level responses to solid Earth tides and changes in atmospheric pressure provides a passive way to continuously monitor changes in permeability and storage properties in tectonically active regions.

58 GEOSCIENCES↗

DOE OSTI2020

Microbial Community Composition in Deep‐Subsurface Reservoir Fluids Reveals Natural Interwell Connectivity

Abstract The identification of natural fractures and the wells they connect is crucial for the development of geological reservoirs because it may have an important impact on reservoir model construction and hydraulic fracture propagation. In this study we investigated the use of a novel data source, the microbial community composition in the reservoir formation fluids, for identification of interwell connectivity caused by natural fractures. We verified this concept at a newly developed mesoscale enhanced geothermal system (EGS) field testbed located 4,850 ft (1,478 m) beneath ground surface at the Sanford Underground Research Facility in Lead, SD. Fluids produced at or near the EGS testbed were sampled and subjected to high‐throughput 16S rRNA gene amplicon sequencing to analyze the microbial community profile therein. Despite the typically substantial heterogeneity across the community profiles of samples spatially distributed (10 m to 1.9 km apart) throughout the site, samples from two wells at the EGS testbed showed highly similar microbial community composition, suggesting the two wells intersected the same natural fracture. This evidence of natural connectivity between the two wells at the EGS testbed was later corroborated by core log analysis and sewer camera surveys into the boreholes. Besides the field case described in this study, microbial community composition as a reservoir diagnostic tool would be applicable in a much broader context such as unconventional hydrocarbon exploitation, groundwater reservoir characterization, and environmental remediation, adding valuable “hard” data capable of pinpointing the origins of fluids unambiguously.

Zhang, Yuran↗

DOE OSTI2020

Creation of a Mixed-Mode Fracture Network at Mesoscale Through Hydraulic Fracturing and Shear Stimulation

Enhanced Geothermal Systems could provide a substantial contribution to the global energy demand if their implementation could overcome inherent challenges. Examples are insufficient created permeability, early thermal breakthrough, and unacceptable induced seismicity. In this study we report on the seismic response of a mesoscale hydraulic fracturing experiment performed at 1.5-km depth at the Sanford Underground Research Facility. We have measured the seismic activity by utilizing a 100-kHz, continuous seismic monitoring system deployed in six 60-m length monitoring boreholes surrounding the experimental domain in 3-D. The achieved location uncertainty was on the order of 1 m and limited by the signal-to-noise ratio of detected events. These uncertainties were corroborated by detections of fracture intersections at the monitoring boreholes. Three intervals of the dedicated injection borehole were hydraulically stimulated by water injection at pressures up to 33 MPa and flow rates up to 5 L/min. We located 1,933 seismic events during several injection periods. The recorded seismicity delineates a complex fracture network comprised of multistrand hydraulic fractures and shear-reactivated, preexisting planes of weakness that grew unilaterally from the point of initiation. We find that heterogeneity of stress dictates the seismic outcome of hydraulic stimulations, even when relying on theoretically well-behaved hydraulic fractures. Once hydraulic fractures intersected boreholes, the boreholes acted as a pressure relief and fracture propagation ceased. In order to create an efficient subsurface heat exchanger, production boreholes should not be drilled before the end of hydraulic stimulations.

58 GEOSCIENCES↗

DOE OSTI2020

Predictive Inverse Model for Advective Heat Transfer in a Short–Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Identifying fluid flow maldistribution in planar geometries is a well–established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or “engineered”) geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two–dimensional Hele–Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C–Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir–scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding–plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. Here, the results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.

42 ENGINEERING↗

DOE OSTI2024

Formation of a Large Cold Groundwater Mantle Helium Anomaly and High Temperature Geothermal Resources in Response to Bimodal Magmatism Near Roosevelt Hot Springs and Utah FORGE, Milford Valley, Southwest Utah

Abstract A large mantle helium anomaly and separate domains of high heat flow are the predominant manifestations of bimodal magmatic activity in the Milford valley. The mantle helium anomaly (1.9–2.6 R/Ra) covers 270 km 2 and is subdivided into two separated domains: a cold shallow groundwater regime and high temperature hydrothermal activity. The zone of anomalous heat flow covers >100 km 2 and is also subdivided into two adjacent domains, comprising hydrothermal activity at Roosevelt Hot Springs (RHS) (3–7 W/m 2 ) and conductive heat flow (100–180 mW/m 2 ). While the transfer of heat and mantle helium at RHS are coupled, heat and helium transfer are decoupled in the adjacent cold groundwater regime to the west. Both the mantle helium and geothermal anomalies are attributed to recent mafic‐felsic magmatic intrusions of >400 km 3 , however, the absence of volcanic eruptions <500,000 years indicates magmas stall before rising to shallow crustal level <10 km depth. Deep level magmatism produces a felsic composition melt, which is inferred to be responsible for the widespread and near uniform range of diluted mantle helium values. A thick and impermeable mass of crystalline granitic basement rock at the mid‐crustal level divides the ascent of mantle helium into separate flow paths. It may also impede the rise of buoyant magma trapping thermal energy that facilitates partial melting, slow cooling, and development of a thick thermal aureole. Partitioning of convective and conductive thermal regimes and independent flow paths supplying deeply derived helium characterize the development of a large long‐lived magma‐related geothermal system.

Geochemistry & Geophysics↗

DOE OSTI2026

Effects of Dissolution Regimes on Flow Channelization and Solute Transport in 3D Fracture Networks: Insights From Graph‐Based Reactive Transport Modeling

We investigate how mineral dissolution reshapes flow pathways and solute transport in three‐dimensional discrete fracture networks using a computationally efficient graph‐based reactive transport model. The DFNs are inspired by field‐site observations of fractured carbonate and represent realistic connectivity and structural heterogeneity. Flow is simulated with the Reynolds equation, and dissolution follows first‐order kinetics with diffusive limitations captured through an effective mass‐transfer coefficient. By systematically varying two key dimensionless parameters, the effective Damköhler number (Da), governing reaction versus advection rates, and a transport parameter (Da), analogous to the Thiele modulus, distinct flow channelization regimes emerge: mildly channelized at low G, highly channelized at intermediate Da, and extreme wormhole formation at high Da and low G. Eulerian and Lagrangian analyses, including breakthrough curves, particle tortuosity, dispersivity, and flow channeling indicators quantitatively characterize the progression of dissolution‐driven network restructuring. Across all regimes, initial fracture heterogeneity persists. The results underscore how the interplay between this initial structure, advection, reaction, and diffusion critically shapes subsurface flow pathways, with implications for applications ranging from groundwater remediation to enhanced geothermal systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Causal mechanism of injection-induced earthquakes through the M w 5.5 Pohang earthquake case study

Causal mechanisms for fluid injection-induced earthquakes remain a challenge to identify. Past studies largely established spatiotemporal correlations. Here, we propose a multi-process causal mechanism for injection-induced earthquakes through a case study of the 2017 M w 5.5 induced earthquake near Pohang Enhanced Geothermal System, Korea, where detailed hydraulic stimulation and on-site seismicity monitoring data provide an unprecedented opportunity. Pore pressure modeling reveals that pore pressure changes initiate seismicity on critically stressed faults and Coulomb static stress transfer modeling reveals that earthquake interactions promote continued seismicity, leading to larger events. On the basis of these results, we propose the following causal mechanism for induced seismicity: pore pressure increase and earthquake interactions lead to fault weakening and ultimately triggering larger earthquakes later in the process. We suggest that it is prudent that pore pressure change, initial seismicity locations, and Coulomb static stress transfer from seismicity earlier in the sequence are assessed in real-time.

58 GEOSCIENCES↗

DOE OSTI2026

Branched-chain amino acid specialization drove diversification within Calditenuaceae ( Caldarchaeia ) and enables their cultivation

Many thermophiles that are abundant in high-temperature geothermal systems have never been cultivated and are poorly understood, including deeply branching members of the archaeal phylum Thermoproteota. Here, we describe the genome-guided cultivation of one such organism, Calditenuis ramacidaminiphagus, and show that it has evolved a heterotrophic metabolism focused on branched-chain amino acids (BCAAs). Initially, fluorescence in situ hybridization and nanoscale secondary ion mass spectrometry (FISH-nanoSIMS) showed that Cal. ramacidaminiphagus assimilated amino acids rapidly in casamino acid-amended enrichment cultures. Metagenome and metaproteome analyses showed a high abundance and expression of BCAA transporter genes, suggesting a BCAA-focused metabolism. This inference was supported by the subsequent enrichment of Cal. ramacidaminiphagus in BCAA-fed cultures, reaching 2.66×10 6 cells/mL and 48.7% of the community, whereas it was outcompeted when polar amino acids were included. Metabolic reconstruction and metaproteomics suggest that BCAAs are channeled into the mevalonate pathway for lipid biosynthesis and fuel ATP production through the TCA cycle coupled with aerobic respiration and through production of branched-chain organic acids by overflow metabolism. Ancestral state reconstructions and phylogenetic analyses of 62 Caldarchaeales genomes revealed multiple horizontal transfers of BCAA transporters to the ancestor of the genus Calditenuis. Our study highlights the crucial role of BCAAs in the early evolution and niche of this genus, and suggests a high degree of resource partitioning even within low-diversity thermophilic communities.

Biological and medical sciences↗

DOE OSTI2025

Deep learning forecasts the spatiotemporal evolution of fluid-induced microearthquakes

Microearthquakes generated by subsurface fluid injection record the evolving stress state and permeability of reservoirs. Forecasting their spatiotemporal evolution is therefore critical for applications such as enhanced geothermal systems, carbon dioxide sequestration and other geoengineering applications. Here we propose a transformer neural network model that ingests hydraulic stimulation history and prior microearthquake observations to forecast four key quantities: cumulative microearthquake count, cumulative logarithmic seismic moment, and the 50th- and 95th-percentile extents of the microearthquake cloud. Applied to the EGS Collab Experiment 1 dataset, the model achieves R2 > 0.98 for the 1-s forecast horizon and R2 > 0.88 for the 15-s forecast horizon across all targets, and supplies uncertainty estimates through a learned standard deviation term. These accurate, uncertainty-quantified forecasts enable real-time inference of fracture propagation and permeability evolution, demonstrating the strong potential of deep-learning approaches to improve seismic-risk assessment and guide mitigation strategies in future fluid-injection operations.

Chung, Jaehong↗

DOE OSTI2026

AnisONet: A deep neural operator-based anisotropic permeability upscaler from pore to Darcy scale

Directional permeability variations, which govern directional fluid flow in porous media with anisotropy, are important to accurately predict flow behavior, reactive transport, and fluid–solid interactions for various processes such as enhanced geothermal systems, energy storage devices, and biological systems. However, the intricate architecture of porous media makes it difficult to predict directional permeabilities. In this work, we present a novel machine learning (ML) framework, AnisONet, built upon an integration of a convolutional neural network, Swin transformer, and the deep operator network architecture, designed to predict anisotropic permeability and upscale predictions to larger spatial domains. First, AnisONet was evaluated with three classes of two-dimensional (2D) porous media, including synthetic circular and elliptical grains and natural sandstone grains from micro-computed tomography images. A lattice Boltzmann model (LBM) was used to calculate directional permeabilities at every 10° angle, producing 19 data points per image of porous media. AnisONet is then trained to predict permeability as a function of rotation angle. AnisONet showed strong predictive capability of directional permeability. Second, we tested our model for five upscaling cases with a large image size in the finite-element method (FEM) for 2D Darcy flow with various permeability tensor construction methods. Overall, upscaled permeability tensors in FEM simulations produce a reasonably good match with LBM results, highlighting the importance of selecting appropriate tensor formation strategies for accurate permeability upscaling. AnisONet, as a directional permeability estimator, could be further developed for more complex geometries, with the potential to develop a foundational ML model for various applications in porous media.

42 ENGINEERING↗

DOE OSTI2021

Cement sensors with acoustic bandgaps using carbon nanotubes

Cement is widely used in wellbores to stabilize the steel casing used in wellbore operations for oil and gas production, enhanced geothermal systems and carbon sequestration, and to limit fluid movement between sub-surface strata. Flaws such as microcracks in wellbore cement can lead to leakage along the wellbore compromising wellbore integrity. There is an increasing need for methods to monitor cement crack propagation in wellbore environments. In this study, we develop and report the first cementitious sensors capable of exhibiting high frequency acoustic bandgaps (ABGs) using carbon nanotubes (CNTs). Computational simulations of a sensor unit cell are used to design cement-multi walled carbon nanotubes (MWCNTs) sensors that show a wide bandgap. When the cement-MWCNTs sensors is embedded in cement specimens, bandgaps were measured experimentally under 300 kHz and under 600 kHz, consistent with the computationally predicted bandgaps in the range of 290–360 kHz, 410–460 kHz and 515–585 kHz. These bandgap features were absent in homogeneous cement specimens. X-ray tomographic reconstructions showed microscopic debonding at cement-MWCNTs sensor interface. Frequency response analysis of a three-dimensional computational model indicated a shift of frequency of minimum transmission due to the interface debonding, but no perturbation of bandgap response was observed. Here, the cement-MWCNTs sensors developed in this study show the potential of a packed CNT inclusion material in cementitious matrix to create ABGs in a cement matrix.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Compartmentalization of the Coso East Flank geothermal field imaged by 3-D full-tensor MT inversion

Previous magnetotelluric (MT) studies of the high-temperature Coso geothermal system in California identified a subvertical feature of lowresistivity (2-5Ohmm) and appreciable lateral extent (>1 km) in the producing zone of the East Flank field. However, these models could not reproduce gross 3-D effects in the recorded data. We perform 3-D full-tensor inversion and retrieve a resistivity model that out-performs previous 2-D and 3-D off-diagonal models in terms of its fit to the complete 3-D MT data set as well as the degree of modelling bias. Inclusion of secondary Zxxand Zyydata components leads to a robust east-dip (60°) to the previously identified conductive East Flank reservoir feature, which correlates strongly with recently mapped surface faults, downhole well temperatures, 3-D seismic reflection data, and local microseismicity. We perform synthetic forward modelling to test the best-fit dip of this conductor using the response at a nearby MT station. We interpret the dipping conductor as a fractured and fluidized compartment, which is structurally controlled by an unmapped blind East Flank fault zone.

58 GEOSCIENCES↗

DOE OSTI2019

Deep‐sea hydrothermal vent metagenome‐assembled genomes provide insight into the phylum Nanoarchaeota

Summary Ectosymbiotic Nanoarchaeota live on the surface of diverse archaeal hosts. Despite being broadly distributed in global geothermal systems, only three Nanoarchaeota have been successfully co‐cultivated with their hosts, and until now no nanoarchaeotal cultures or genomes have been described from deep‐sea hydrothermal vents. We recovered three nanoarchaeotal metagenome‐assembled genomes (MAGs) from deep‐sea hydrothermal vent sites at the Eastern Lau Spreading Center (M10‐121), Guaymas Basin (Gua‐46) and the Mid‐Cayman Rise (MC‐1). Based on average amino acid identity analysis, M10‐121 is a novel species in the candidate genus Nanoclepta, while the other two MAGs represent novel genera in the Nanoarchaeota . Like previously sequenced Nanoarchaeota, each MAG encodes at least one split protein‐coding gene. The MAGs also contain a mosaic of key nanoarchaeotal features, including CRISPR repeat regions and marker genes for gluconeogenesis and archaeal flagella. MC‐1 also encodes the pentose bisphosphate pathway, which may allow the nanoarchaeote to bypass several steps in glycolysis and produce ATP.

St. John, Emily↗

DOE OSTI2012

Fracturing And Liquid CONvection

Source record↗

DOE OSTI2012

Fracturing And Liquid CONvection

FALCON has been developed to enable simulation of the tightly coupled fluid-rock behavior in hydrothermal and engineered geothermal system (EGS) reservoirs, targeting the dynamics of fracture stimulation, fluid flow, rock deformation, and heat transport in a single integrated code, with the ultimate goal of providing a tool that can be used to test the viability of EGS in the United States and worldwide. Reliable reservoir performance predictions of EGS systems require accurate and robust modeling for the coupled thermal-hydrological-mechanical processes. Conventionally, these types of problems are solved using operator-splitting methods, usually by coupling a subsurface flow and heat transport simulator with a solid mechanics simulator via input files. FALCON eliminates the need for using operator-splitting methods to simulate these systems, and the scalability of the underlying MOOSE architecture allows for simulating these tightly coupled processes at the reservoir scale, allowing for examination of the system as a whole (something the operator-splitting methodologies generally cannot do).

Podgorney, Robert↗

DOE OSTI2025

pnnl/GeoCLUSTER

GeoCLUSTER is a Python-based web application that provides a collection of interactive methods for streamlining the visualization of the technical and economic modeling of closed-loop geothermal systems.

Buchko, Alex [Pacific Northwest National Laborator↗

DOE OSTI2015

The effect of spatial aperture variations on the thermal performance of discretely fractured geothermal reservoirs

Not Available

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Induced seismicity potential based on probabilistic geomechanics for the San Juan Basin CarbonSAFE project

Although geologic carbon sequestration projects have yet to induce — or may never induce — a damaging earthquake, experiences from other deep injection industries such as hydraulic fracturing, enhanced geothermal systems, and saltwater disposal suggest that effective quantitative seismic risk assessment is necessary for deep saline carbon capture and sequestration (CCS) projects. One such imminent CCS project is the San Juan Basin CarbonSAFE Phase III program. We use Monte Carlo probabilistic geomechanical analyses combined with observations of the geologic and operational parameters of the San Juan Basin site and suggest that this project is of low-induced seismic risk. The primary analysis is split into four sections. First, we assess the literature for faults and past seismicity, and at least five faulting scenarios are directly relevant. Second, we develop and calibrate an integrated earth model for the project site. Third, we perform Monte Carlo simulations that consider reasonable uncertainties of the geomechanical parameters. Of five tested faulting scenarios, only one presents high Coulomb failure functions, but fourth, we determine the risk to be low based on the combined lack of historical seismicity, the geologic framework of the faulting scenario, and the presence of saltwater injection at the same depth as the proposed supercritical carbon dioxide injection. The most sensitive parameters in the geomechanical calculations are the fault dip and the coefficient of friction. The least sensitive are the fault strike and the orientation of the maximum horizontal principal stress.

58 GEOSCIENCES↗