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At least 271 records · Page 15

The emergence of hydrogeophysics for improved understanding of subsurface processes over multiple scales

Geophysics provides a multidimensional suite of investigative methods that are transforming our ability to see into the very fabric of the subsurface environment, and monitor the dynamics of its fluids and the biogeochemical reactions that occur within it. Here we document how geophysical methods have emerged as valuable tools for investigating shallow subsurface processes over the past two decades and offer a vision for future developments relevant to hydrology and also ecosystem science. The field of “hydrogeophysics” arose in the late 1990s, prompted, in part, by the wealth of studies on stochastic subsurface hydrology that argued for better field-based investigative techniques. These new hydrogeophysical approaches benefited from the emergence of practical and robust data inversion techniques, in many cases with a view to quantify shallow subsurface heterogeneity and the associated dynamics of subsurface fluids. Furthermore, the need for quantitative characterization stimulated a wealth of new investigations into petrophysical relationships that link hydrologically relevant properties to measurable geophysical parameters. Development of time-lapse approaches provided a new suite of tools for hydrological investigation, enhanced further with the realization that some geophysical properties may be sensitive to biogeochemical transformations in the subsurface environment, thus opening up the new field of “biogeophysics.” Early hydrogeophysical studies often concentrated on relatively small “plot-scale” experiments. More recently, however, the translation to larger-scale characterization has been the focus of a number of studies. In conclusion, geophysical technologies continue to develop, driven, in part, by the increasing need to understand and quantify key processes controlling sustainable water resources and ecosystem services.

58 GEOSCIENCES↗

Improved sampling technique to collect natural gas from hydrate-bearing pressure cores

High quality gas compositional data are an important factor in interpreting the genetic source of natural gas hosted in hydrate-bearing sediments and other subsurface systems. In order to accurately characterize the composition of gas samples degassed from hydrate-bearing pressure cores, one must use a reproducible sampling technique that minimizes artifacts of the sampling process. Herein, we review sediment core degassing techniques and compare data obtained from a commonly used degassing approach, which we term the standard quantitative degassing (SQD) technique, to our newly developed modified quantitative degassing (MQD) method designed to minimize atmospheric contamination and gas-water interactions. The SQD method allows sample gas to interact with water in a bubbling chamber, which we hypothesize could alter the gas composition following mixing with water or dissolved gases in the bubbling chamber. Whereas, the MQD method allows for the collection of sample gas prior to the bubbling chamber. To compare the SQD and MQD methods, we performed a side-by-side comparison of noble (He, Ne, Ar, Kr, and Xe), major (H 2 , N 2 , O 2 , and CO 2 ), and hydrocarbon (CH 4 , C 2 H 6 , C 3 H 8 , i-C 4 H 10 , C 4 H 10 , i-C 5 H 12 , C 5 H 12 ) gas concentrations and select isotopic compositions obtained using both sample collection techniques. Gas samples were collected from hydrate-bearing pressure cores recovered and maintained under hydrate stable conditions from the northern Gulf of Mexico during the UT-GOM 2 -1 Expedition. The MQD method displayed significantly lower concentrations of atmospheric gases, higher proportions of hydrocarbon gases, lower ratios of C 1 /C 2 + , and heavier stable carbon and hydrogen isotopes of methane than the SQD method. These results demonstrate that the MQD method reduced air contamination and minimized alteration of the hydrocarbon gases. Finally, we conclude this method may be important for future work that seeks to determine the composition of natural gas from pressure cores using quantitative degassing experiments, especially those seeking to measure major (e.g., N 2 ) and noble gases.

58 GEOSCIENCES↗

Recovering the microseismic response from a geomechanical simulation

The assessment of microseismic events is one of a few tools available for characterizing processes that occur within the subsurface. Here, we have developed a method for modeling microseismic activity in the subsurface that allows us to model microseismic events at the reservoir scale. By embedding this method in a fully coupled hydromechanical numerical code, we simulate the development of hydraulic fractures in an unconventional reservoir with an explicitly represented discrete fracture network for a relatively simple synthetic model and a more complicated model based upon field observations. The findings demonstrate that the model can be effectively calibrated against measured microseismic activity, and it can be used to make predictions regarding the timing, location, and amplitude of events in the subsurface.

58 GEOSCIENCES↗

Magnetotelluric Data from Mountain Home, ID

This dataset includes magnetotelluric transfer functions in the form of EDI files for 16 stations collected by the USGS and 40 stations collected by Quantec Geoscience for Lawerence Berkeley National Lab around the Mountain Home area in Idaho. A 3D electrical resistivity model is included that images resistive and conductive bodies in the subsurface that maybe important for geothermal characterization. The model was created using ModEM using the high performance computer Yeti at the USGS.

15 GEOTHERMAL ENERGY↗

Predicting Cement-Sheath Integrity with Consideration of Initial State of Stress and Thermoporoelastic Effects

In conventional wellbore-integrity analysis, the cement sheath’s initial state of stress and transient thermoporoelastic effects are often neglected. However, the initial state of stress is prerequisite information for accurately predicting the safe operating conditions that prevent a cemented well from being damaged. In addition, transient thermoporoelastic effects can have a profound effect on when damage will occur. Here in this paper, we propose a model that includes these effects to predict the safe operating pressures and temperatures that will prevent cement-sheath failure. For the initial state of stress, we proposed an empirical model using measurements. Subsequent stress changes are evaluated by a fully coupled transient thermoporoelastic model to analyze the mechanical behavior of the cement sheath. We predict the safe operating envelope (SOE) for shear, tensile, and debonding cement-sheath failures caused by pressure and temperature perturbations after the cement sets. Our model predicts that pore pressure is a key factor for cement failure, especially for rapid temperature changes. If the formation is low permeability, the transient pore pressures are amplified, causing the risk of damage to increase. Compared with conventional thermoelastic models, the thermoporoelastic model predicts a smaller SOE when heating the internal casing fluid and a larger envelope when cooling the internal casing fluid. Finally, the heating rate was considered with respect to field applications. The heating rate was also considered, and slower heating/cooling rates can prevent damage to the cement sheath. Finally, the thermoporoelastic model was applied to explain several laboratory and field experiments and achieved good matches.

02 PETROLEUM↗

Heart Shape to Fracture Distance: Characterizing Hydraulic Fracture Propagation before Hits

Estimating the distance from the hydraulic fracture tip to the monitor well can be useful for fracture characterization, well spacing optimization, and preventing parent-child well interference. A heart-shaped signal is referred to as the extensional precursor of a fracture hit recorded by crosswell strain measurements and can serve as a vital tool for such estimation. This study incorporates the 3D displacement discontinuity method (DDM) to understand the impact of fracture geometry and monitor well offset on the heart-shaped signal’s characteristics. Results from numerical simulation and analytical solutions reveal a strong linear correlation between the spatial extent of the heart-shaped signal and the fracture tip distance. This relationship was further developed to predict tip distance using field data from the Hydraulic Fracture Test Site 2 (HFTS2). A reasonable approximation result from field data further validates the methodology. In addition, it is worth noting that the estimation accuracy depends on the ratio between fracture dimension and tip distance. The findings of this study offer a novel approach for real-time monitoring and characterizing hydraulic fracture propagation, which can be further used for well spacing optimization in unconventional and enhanced geothermal system reservoir development, as well as caprock integrity monitoring for carbon sequestration projects.

58 GEOSCIENCES↗

3D Moment Tensor Inversion of Underground Chemical Explosions from the Source Physics Experiments

Several physical mechanisms have been proposed to explain the generation of S-waves from underground explosions, such as asymmetries in the source, release of tectonic pre-stress, interactions with the free-surface, spall, and heterogeneities in the Earth. An accurate description of the explosion source processes is an important step towards understanding which of these plausible mechanisms are actively contributing to the generation of S-waves and under what conditions. In this study we explore the application of the seismic moment tensor source to model far-field, low frequency (up to 6 Hz) waveform data of over-buried chemical explosions from the Source Physics Experiment, with a focus on S-wave generation and amplitude predictions. We use an inverse waveform modeling approach to estimate the source properties of the chemical explosions, and compare solutions using different velocity models. 1D and 3D subsurface velocity models are used to characterize wave propagation between the source and receiver. We also performed analysis on wavefield simulations from physic-based explosion source modeling. The analyses show scattering and phase conversion from 3D heterogonies dominate the generation of far-field, S-wave energy observed in data, and that the variability in the recovered deviatoric component of the moment tensor source model are largely a result of inadequately accounting for 3D wave propagation effects in the inversion process.

58 GEOSCIENCES↗

Exploring Geologic Hydrogen: A New Frontier for Affordable, Reliable Energy Security

Recent successes in the exploration, drilling, and discovery of geologic hydrogen have generated notable excitement. This new energy resource has the potential to make an important contribution to our nation’s energy supply, resiliency, and security. Contemporary studies of geologic hydrogen have a common theme of suggesting places where it might be found or even more specifically, what rocks in what geologic formations may contribute to its formation — either naturally or via artificially induced means. This vital ongoing body of work sets the stage for imagining what may be possible with vast available quantities of naturally occurring hydrogen in the subsurface. While acknowledging current approaches to characterizing geologic hydrogen, this report advances the discussion by suggesting next steps, including the critical science and engineering necessary to make geologic hydrogen an affordable and reliable part of the U.S. energy portfolio.

08 HYDROGEN↗

Characterization of natural titanomagnetites (Fe3-xTixO4) for studying heterogeneous electron transfer to Tc(VII) in the Hanford subsurface

Sediments with basaltic provenance, such as those at the Hanford nuclear reservation, Washington, USA, are rich in Fe-bearing minerals of mixed valence. These minerals are redox reactive with aqueous O2 or Fe(II), and have the potential to react with important environmental contaminants including Tc. Here we isolate, identify and characterize natural Fe(II)/Fe(III)-bearing microparticles from Hanford sediments, develop synthetic analogues and investigate their batch redox reactivity with aqueous Tc(VII). Natural Fe-rich mineral samples were isolated by magnetic separation from sediments collected at several locations on Hanford’s central plateau. This magnetic mineral fraction was found to represent up to 1 wt% of the total sediment, and be composed of 90% magnetite with minor ilmenite and hematite, as determined by X-ray diffraction. The magnetite contained variable amounts of transition metalsconsistent with alio- and isovalent metal substitutions for Fe. X-ray microprobe analysis showed that Ti was the most significant substituent, and that these grains could be described with the titanomagnetite formula Fe3_xTixO4, which falls between endmember magnetite (x = 0) and ulvo¨ spinel (x = 1). The dominant composition was determined to be x = 0.15 by chemical analysis and electron probe microanalysis in the bulk, and by L-edge X-ray absorption spectroscopy and X-ray photoelectron spectroscopy at the surface. Site-level characterization of the titanomagnetites by X-ray magnetic circular dichroism showed that despite native oxidation, octahedral Fe(II) was detectable within 5 nm of the mineral surface. By testing the effect of contact with oxic Hanford and Ringold groundwaters to reduced Ringold groundwater, it was found that the concentration of this near-surface structural Fe(II) was strongly dependent on aqueous redox condition. This highlights the potential for restoring reducing equivalents and thus reduction capacity to oxidized Fe-mineral surfaces through redox cycling in the natural environment. Reaction of these magnetically-separated natural phases from Hanford sediments with a solution containing 10 lmol L_1 Tc(VII) showed that they were able to reductively immobilize Tc(VII) with concurrent oxidation of Fe(II) to Fe(III) at the mineral surface, as were synthetic x = 0.15 microparticle and nanoparticle analogue phases. When differences in the particle surface area to solution volume ratio were taken into consideration, measured Tc(VII) reduction rates for Fe3_xTixO4(x = 0.15) natural material, synthetic bulk powder and nanoparticles scaled systematically, suggesting possible utility for comprehensive batch and flow reactivity studies.

Environmental Molecular Sciences Laboratory↗

Produced Water DNA Database (PW-DNA): Utilizing KBase to generate an environmental specific curated molecular database

The deep subsurface is estimated to host the majority of Earth’s microbial biomass yet remains one of the most challenging environments to access and study. One common approach to investigate these microbial communities is through the analysis of produced water from subsurface reservoirs, where researchers can assess water and gas chemistry along with molecular (DNA/RNA) sequence data. Advances in high-throughput sequencing have greatly expanded our understanding of these environments and their biotechnological potential. However, further progress requires large-scale, integrative meta-analyses across diverse datasets. To address this need, we developed the Produced Water-DNA (PW-DNA) Database, a curated, publicly available resource that consolidates microbial DNA/RNA sequences, geochemical data, and relevant metadata from in situ hydrocarbon environments such as coal beds, oil reservoirs, and natural gas systems. The PW-DNA database delivers three core benefits to the research community: (1) it improves data sharing by linking environmental microbial datasets with corresponding geochemical parameters, enabling more robust filtering and analysis; (2) it connects with complementary research databases to promote broader dissemination and interoperability; and (3) it supports technological innovation by serving as a resource for identifying microbial trends and exploring genetic potential. While individual studies have highlighted basin-specific microbial communities and functional redundancy in biogeochemical cycling, a comprehensive, system-wide perspective is needed to better understand connectivity and novelty across subsurface ecosystems. By designing the PW-DNA in the KBase platform, we provide a reproducible, visual framework for integrating large-scale genomic and geochemical data, enabling researchers to perform more informed analyses and experimental design. Ultimately, this resource enhances the ability to identify, characterize, and interpret microbial functions across diverse subsurface environments, thereby accelerating discovery in subsurface microbiology and biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗

Integrating Electrical Resistivity Tomography with Vadose Zone Characterization - 20246

The environmental management mission at the U.S. Department of Energy Hanford Site includes addressing subsurface contaminants that are present in the vadose zone because of historical waste discharges. Characterization is needed to support evaluation of whether contaminants at specific disposal sites will migrate to and contaminate the groundwater in the future. Drilling of boreholes and analysis of retrieved sediment samples is a standard approach to evaluating contaminant distribution in the vadose zone for the types of inorganic and radionuclide contaminants at the Hanford Site. However, borehole sampling has limitations for understanding the volumetric distribution of contaminants. The Hanford Site is now applying electrical resistivity tomography to characterize the path and volumetric extent of contaminant migration in the vadose zone. This information aids selection of appropriate locations for obtaining borehole samples and provides three-dimensional contaminant distribution information for incorporation into conceptual site models and to help configure fate and transport models. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Efficient Data-Driven Geologic Feature Characterization from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm

Conventional seismic techniques for detecting the subsurface geologic features are challenged by limited data coverage, computational inefficiency and subjective human factors. We developed a novel data-driven geological feature characterization approach based on pre-stack seismic measurements. Our characterization method employs an efficient and accurate machine learning method to extract useful subsurface geologic features automatically. Specifically, we use kernel ridge regression to account for the nonlinear relationship between seismic data and geological features. We moreover employ kernel tricks to avoid the explicit nonlinear mapping and infinite dimension of feature space. Yet, the conventional kernel ridge regression can be computationally prohibitive because of the large volume of seismic measurements. We employ a data reduction technique in combination with the conventional kernel ridge regression method to improve the computational efficiency and reduce memory usage. In particular, we utilize a randomized numerical linear algebra technique, named Nyström method, to effectively reduce the dimensionality of the feature space without compromising the information content required for accurate characterization. We provide thorough computational cost analysis to show the efficiency of our new geological feature characterization methods. We validate the performance of our method in characterizing geologic fault zones because faults play an important role in various subsurface applications. Our numerical examples demonstrate that our new characterization method significantly improves the computational efficiency while maintaining comparable accuracy. Interestingly, we demonstrate that our approach yields a speedup ratio on the order of ~102 to ~103 in a multicore computational environment.

58 GEOSCIENCES↗

Time-reversed nonlinear acoustics for wellbore integrity characterization

A pulsed sinusoidal acoustic signal transmitted through a subsurface volume of a wellbore may be detected. A time-reversed acoustic signal of the pulsed sinusoidal acoustic signal may be transmitted through the subsurface volume of the wellbore. Transmission of the time-reversed acoustic signal through the subsurface volume of the wellbore may result in generation of focused acoustic signal in the subsurface volume of the wellbore. The focused acoustic signal in the subsurface volume of the wellbore may be detected, and the integrity of the wellbore may be determined based on the focused acoustic signal in the subsurface volume of the wellbore.

Ulrich, II, Timothy James↗

Helium effects on the surface and subsurface evolutions in single-crystalline tungsten

Tungsten (W) has been perceived as one of the most promising plasma facing materials (PFMs) for future fusion reactors. In the past decade, its behavior under irradiation and helium (He) plasma interaction has been extensively studied. However, some key knowledge gaps still exist, such as the influence of crystallographic orientation on the surface and subsurface evolutions. In this work, we focus on the He ion-beam irradiation damage effects in mirror-polished single-crystalline W samples with three different surface planes of {100}, {110} and {111}. Irradiation was performed at room temperature using 40 keV He+ to a fluence of 1 × 10 16 /cm 2 , followed by thermal desorption spectroscopy (TDS) up to ~1920 K. The microstructures of He-irradiated W before and after TDS heat treatment were characterized by scanning and transmission electron microscopy. Subsurface He bubbles were imaged in all irradiated samples, but newly formed <111>-oriented surface grains and surface blisters were only observed in W {100} and {110} starting orientations. These results reveal that radiation damage, He thermal desorption, and surface/subsurface evolution are all strongly dependent on crystallographic orientation. Underlying physical mechanisms are discussed based on ion channeling effects, He-vacancy interactions, and surface diffusion. In conclusion, these findings provide new insights into He effects in W.

36 MATERIALS SCIENCE↗

Small Penetrator Instrument Concept for the Advancement of Lunar Surface Science

Fundamental scientific objectives concerning the surface and subsurface material and dynamics of the Moon are the drivers for the use and advancement of penetrators, which emplace a suite of scientific instruments by impact into a planetary surface, typically at velocities of dozens to hundreds of meters per second. Small lunar penetrators are poised to become a valuable new tool for lunar science and exploration during the next decade. These low-cost ballistic probes can be deployed in large numbers from orbit, or from descending robotic or crewed vehicles, in order to explore and characterize the diversity of extreme lunar shallow subsurface environments. In this paper, we describe the general overview of penetrator objectives, potential instrumentation, and how these would benefit the advancement of lunar science at various extreme environments.

47 OTHER INSTRUMENTATION↗

Approaching a universal scaling relationship between fracture stiffness and fluid flow

A goal of subsurface geophysical monitoring is the detection and characterization of fracture alterations that affect the hydraulic integrity of a site. Achievement of this goal requires a link between the mechanical and hydraulic properties of a fracture. Here we present a scaling relationship between fluid flow and fracture-specific stiffness that approaches universality. Fracture-specific stiffness is a mechanical property dependent on fracture geometry that can be monitored remotely using seismic techniques. A Monte Carlo numerical approach demonstrates that a scaling relationship exists between flow and stiffness for fractures with strongly correlated aperture distributions, and continues to hold for fractures deformed by applied stress and by chemical erosion as well. This new scaling relationship provides a foundation for simulating changes in fracture behaviour as a function of stress or depth in the Earth and will aid risk assessment of the hydraulic integrity of subsurface sites.

42 ENGINEERING↗

Anisotropic seismic-waveform inversion: Application to a seismic velocity model from Eleven-Mile Canyon in Nevada

Accurate imaging and characterization of fracture zones is crucial for geothermal energy exploration. Aligned fractures within fracture zones behave as anisotropic media for seismic-wave propagation. The anisotropic properties in fracture zones introduce extra difficulties for seismic imaging and waveform inversion. We have recently developed a new anisotropic elastic-waveform inversion method using a modified total-variation regularization scheme and a wave-energy-base preconditioning technique. Our new inversion method uses the parameterization of elasticity constants to describe anisotropic media, and hence it can properly handle arbitrary anisotropy. We apply our new inversion method to a seismic velocity model along a 2D-line seismic data acquired at Eleven-Mile Canyon located at the Southern Dixie Valley in Nevada for geothermal energy exploration. Our inversion results show that anisotropic elastic-waveform inversion has potential to reconstruct subsurface anisotropic elastic parameters for imaging and characterization of fracture zones.

15 GEOTHERMAL ENERGY↗

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗