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408 records · Page 4Linked to original sources

Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity

Since the vast majority of carbon dioxide (CO 2 ) storage resources in the United States are in deep saline aquifers, optimizing the use of these saline storage resources could be crucial for efficient development of geologic CO 2 storage (GCS) resources and basin- or larger-scale deployment of GCS in the country. Maximum CO 2 injection rates can be enhanced by extracting brine from the CO 2 storage unit. However, disposal of the extracted brine is both a technological and economic challenge. The lowest-cost option would likely be reinjection of the extracted brine into another formation above or below the CO 2 storage unit. Therefore, it is important to estimate brine injectivity as it will constrain the potential to increase CO 2 injectivity at an injection site that has access to multiple geologic storage units where either CO 2 or brine can be injected. Using a simulation-optimization framework, coupled with a non-isothermal, multiphase CO 2 -water-salt equation-of-state module, we developed a computationally efficient method for evaluating optimization of simultaneous CO 2 injection, brine extraction, and brine (re)injection at hypothetical injection sites deployed across a geologic basin. The Illinois basin is ideal for testing our methodology because it contains multiple geologic storage units with seals in between them to isolate injection of CO 2 in one unit from interfering with the injection of either brine or CO 2 in another unit above or below it. In addition, we investigated the relative effects of variation in key geologic parameters as well as two reservoir structures (hydrogeologic heterogeneity/anisotropy and homogeneity/isotropy) on CO 2 injectivities and enhancement of CO 2 injectivity through extracting brine. Results suggest that permeability, depth, and especially thickness of the storage unit could be the most influential parameters determining CO 2 injectivity. They also suggest that only injecting CO 2 into the storage unit with the greatest injectivity, enhancing that unit’s injectivity by extracting brine, and disposing of the produced brine in other suitable units could maximize total CO 2 injectivity in limited regions of the basin. At the majority of simulated injection sites, however, we found that injecting CO 2 into all of the accessible and suitable storage units was more likely to maximize the CO 2 storage resource.

Illinois, Kentucky, Indiana

Detecting snow avalanche activity using infrasound: Hooker Valley, New Zealand

Snow avalanches pose considerable hazards to people and infrastructure in alpine environments. Traditional avalanche monitoring relies on meteorological data and visual observations, which can be limited in scope and timeliness. Infrasound offers a promising complementary monitoring tool by detecting the low-frequency sound waves generated by avalanches. Here, we present infrasound and camera observations during a 50-day field campaign in the Hooker Valley of Aoraki/Mount Cook National Park, New Zealand. Our study detected seven avalanches with the cameras, whereas the infrasound system identified only one of these events, which was the largest and occurred under conditions that likely favoured infrasound propagation. The infrasound system recorded numerous other events not captured by the cameras, indicating the benefit of further investigation to determine their sources. These findings highlight the potential of infrasound technology for detecting avalanches and providing broad spatial coverage, capturing events in areas not monitored by cameras, while also showcasing limitations in infrasound capabilities. The limited detection of smaller avalanches underscores the opportunity for further research to enhance detection capabilities and understand environmental influences such as snow cover and wind noise. Overall, this study emphasises the utility of multidisciplinary monitoring techniques to improve avalanche detection in alpine environments.

Hooker Valley

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi

Guidelines for producing integrated 210Pb and 14C age-models

Accurate reconstructions of past environmental changes are crucial in paleoecological research and require reliable chronologies of sedimentary archives. Establishing robust age-models and obtaining the most appropriate proxies for analysis is a complex scientific endeavor, requiring extensive resources and collaboration among specialists, including radiochronologists. Radiometric dating methods, such as 210 Pb and radiocarbon ( 14 C), are frequently employed to establish chronologies in aquatic sedimentary deposits and peat bogs. In this study, we review key aspects of sampling, analysis, and the principles underlying 210 Pb and 14 C age-models, focusing on methods for developing robust joint chronologies for paleoenvironmental research. Drawing largely from the authors' experiences and group discussions during and after a scientific workshop in 2022, we discuss important considerations for site selection, sampling strategies, and radiometric dating to construct integrated 210 Pb and 14 C age-models. Using expert consensus, this group – called Paleostats – aims to provide a set of best practices for other geochronologists with this methods paper. Among our conclusions, we emphasize the importance of accounting for site-specific factors such as prior information on sedimentation rates to establish appropriate sampling and analytical strategies. The use of appropriate coring devices can minimize disturbance to sediments and ensure the core surface remains intact and preserved until sectioning. Where excess 210 Pb is expected, sectioning at intervals of ≤1 cm provides an adequate sampling resolution for 210 Pb dating. Exceptions are possible, allowing for ~2–3 cm sections in areas with confirmed high sedimentation rates (e.g., > 1 cm yr −1 ). Recovering deeper core sections for 14 C dating with sufficient overlap allows for accounting errors in depth estimates made in the field. Special attention is advised during time intervals where validation proxies, such as the human-made radionuclides 137 Cs or post-bomb 14 C, are expected, and to determine the depth of secular equilibrium between 210 Pb and 226 Ra. Radiocarbon analyses are commonly performed by accelerator mass spectrometry, and age models are constructed mainly using Bayesian statistics with Markov Chain Monte Carlo techniques (e.g., Bacon ). A Bayesian approach ( Plum ) is now available for producing 210 Pb age-models, which infers the 210 Pb ex flux, eliminates the need for selecting an equilibrium depth, and allows dating cores with incomplete 210 Pb ex inventory. Plum offers improved chronologies by integrating raw 210 Pb and 14 C data, and these age-models can be enriched with other dating methodologies, such as identifying tephras and other well-recorded historical events. Harmonized reporting would contribute to making radiometric age-models reproducible, which would benefit from an international effort. Using 210 Pb and 14 C to produce integrated age-models may yield better insights into the interplay between natural and recent anthropogenic forcings on ecosystems. This can enhance our understanding of environmental processes and their impacts on climate change, ultimately supporting science-based assessments and decisions.

Earth-Science Reviews

Lunar grid systems, coordinate systems, and map projections for the Artemis missions and lunar surface navigation

Foreward This document contains design specifications of a navigational standard for the Moon, including a Lunar Transverse Mercator system, a Lunar Polar Stereographic system, a Lunar Grid Reference System, and a unique coordinate structure, Artemis Condensed Coordinates, for Artemis mission navigation and lunar surface science. The National Aeronautics and Space Administration (NASA) Artemis campaign seeks to place humans on the Moon for the first time since the Apollo missions. Early Artemis missions are heavily focused on the lunar south pole, which promises to return valuable data on the Moon’s geologic record, amongst other mission objectives. Coordinate systems in use today for the lunar south pole provides crew members on the surface neither an efficient nor intuitive means to communicate their position and orientation. A novel grid coordinate system, the Lunar Grid Reference System, is proposed to address these concerns for use in real-time extravehicular activity operations on the lunar surface. The many stakeholders involved in the Artemis missions will need a common system to communicate position and orientation while astronauts are operating on the lunar surface. To that end, Artemis crew members will need that system to be efficient and intuitive to promote efficient extravehicular activity timelines and reduce confusion. In the context of this document, these characteristics are addressed on the design of lunar coordinate systems: Efficient.—The number of characters required to communicate a location within a desired precision level in both local and global contexts, and how many steps are required for a recipient or sender to interpret a location. Intuitive.—How well the system aligns with human perceptual abilities, and whether the system yields distances that have the same relationship to actual lunar surface distance in all directions from the point where a person is located. Technological systems are currently being investigated to supplement the crew members’ ability to locate and orient themselves and other assets on the lunar surface; however, it is unlikely that those systems will be fully operational for the first few landed missions. Even with future positional aids, crew members will still need an efficient and intuitive means to communicate position and orientation. In addition, if technological systems fail, the crews will require land navigation skills and have maps available, thus providing further motivation for a crew-centric coordinate system. The contents of this U.S. Geological Survey (USGS) document detail a comprehensive framework for standardizing lunar crewed surface navigation within NASA and outlines the protocols, methods, and designs necessary for achieving consistency and interoperability across relevant space mission teams and lunar surface navigators. Key components of this document include designs of map projections, projected coordinate reference systems (Lunar Transverse Mercator and Lunar Polar Stereographic systems), and a grid system (Lunar Grid Reference System and Artemis Condensed Coordinates) for the Moon. The work proposed in this document seeks to accomplish something similar to the National Geospatial-Intelligence Agency (NGA) document SIG 0012 (NGA, 2014a), but for using grid systems for the Moon. This report incorporates initial feedback and input from NASA’s Artemis Geospatial Data Team, NASA’s Flight Operations Directorate, National Geodetic Survey, USGS Astrogeology Science Center, and NGA and is intended to serve as a resource for all involved with the Artemis missions, as well as for engineers designing and operating lunar infrastructure.

Techniques and Methods

Do bighorn sheep use desert tortoise burrow spoil piles as mineral licks in southern California?

In a previous study, bighorn sheep ( Ovis canadensis ) were periodically photographed by trail cameras when they visited desert tortoise ( Gopherus agassizii ) burrows in the San Bernardino Mountains near Palm Springs, California, USA. The authors suggested that bighorn sheep may utilize the excavated spoil material from burrows as a mineral lick. To test that supposition, we collected soil samples from the spoil piles and undisturbed surface soil up to 1 m away at two desert tortoise study sites with bighorn sheep at the aforementioned site and another nearby site. We hypothesized that sodium concentrations would be greater in spoil than in nearby surface soil samples. Common major cations were quantified in soil samples using inductively coupled plasma-mass spectrometry following microwave-assisted digestion to solubilize the fraction of elements that could become biologically or environmentally available. Mean sodium concentrations were greater in burrow spoil samples than in undisturbed soil samples at both sites, likely due to aqueous leaching of sodium from surface to subsurface soil horizons. Although we did not collect evidence of geophagy by bighorn sheep, the behavior is well known. However, trail camera photographs of bighorn sheep with their head next to the entrance of tortoise burrows suggests that they may periodically utilize sodium and other elements brought to the surface by desert tortoises that are otherwise unavailable to bighorn sheep on the surface.

California

End-user needs for remote sensing wetlands of the Prairie Pothole Region of North America

The Prairie Pothole Region (PPR) of North America comprises globally important grassland and wetland ecosystems critical for numerous populations of migratory birds. Due to the importance of this region for migratory birds, and particularly waterfowl, and the threats of habitat loss due to intensifying agriculture, there is a mature and diverse system of conservation organizations, agencies, and partnerships that spends hundreds of millions of dollars annually on habitat conservation to support migratory bird populations. Remote sensing can be a powerful tool for observing and evaluating global change at large scales as well as expanding inferences from field studies to the broader landscape with statistical models. However, development and utilization of these tools has lagged behind their demand for several reasons, including concerns over spatial and temporal resolution and accuracy of products; perception of a misalignment with decision-maker needs; technological barriers such as skill sets of conservation professionals, computing resources, data access, and usability. In this report, we summarize the needs of conservation professionals and scientists who use or want to use remote sensing data products to inform science about wetland change and conservation of wetlands in the PPR. We assembled this information through several methods leading up to, during, and following a January 2026 PPR Wetland Remote Sensing Workshop. The workshop included United States and Canadian scientists, conservation professionals, and policy experts. Our goal was to bring together end-users and remote sensing product developers jointly to explore reducing the lag between product development and utilization of products to inform science and conservation. Specifically, we aimed to identify gaps in wetland remote sensing that limit effective monitoring, management, and conservation in the PPR, and to develop a framework that outlines pathways to address these gaps by fostering collaboration, improving communication networks, encouraging discussion, and building on existing and ongoing efforts. This report summarizes our participants’ descriptions of end-user needs and the outcomes of the workshop.

Prairie Pothole region

Dendroseismological investigation of redwood trees along the North Coast section of the San Andreas Fault

Sequoia sempervirens (coast redwood) tree rings have the potential to annually resolve late-Holocene earthquakes on the northern San Andreas Fault based on direct (e.g., physical damage) and indirect (e.g., co-seismic environmental change) impacts, but scarcity of suitable samples and challenges crossdating this long-lived species have limited progress. More precise dating of the pre-1906 (penultimate) earthquake can improve hazard assessment and understanding of rupture segmentation. We target old trees (maximum >815 yr) along the North Coast section of the fault (increment cores via rope-climbing, 11 living trees; plunge cuts, 23 stumps) and employ complementary disturbance detection methods including radial-growth averaging (tree- and series-level), cataloging anatomical indicators (e.g., traumatic resin ducts, TRD), and dating structural components (e.g., reiterated trunks, leans). Multi-centennial ring-width chronologies at Fort Ross (1569−2023) and Gualala (1397−2023) promote continued study with incomplete crossdating limiting utilization of some series. Growth pulses (reductions, releases) and TRD dispersed across the record reflect dynamic environments that obfuscate detection of earthquake signals. The 1906 earthquake did not leave strong signatures on most trees, and when it did, within-tree response varied from normal presentation to discoloration, TRD, and missing rings. Synchrony of indicators at both locations identified 1678−1680 (6 of 15 trees) and 1698−1700 (8 of 16 trees) as the strongest disturbances among dated rings in the time range of the penultimate earthquake, peaking at 1698 (15.7 % of possible growth and anatomical indicators), but the triggering mechanisms for these events are unknown.

California

Mechanics and statistics of postseismic shaking

Analysis of two weeks of continuous post-seismic shaking after the 2019 M7.1 Ridgecrest, CA earthquake sequence using 4 nearby borehole seismometers reveals that continuous ground motions decay as Omori’s law in time and follow the Gutenberg-Richter distribution in logarithmic amplitude. The measured temporal decay in amplitudes agrees with predictions of the rate-and-state framework and indicates shaking amplitudes are proportional to the velocity of afterslip. Our ground motion-based statistical framework provides a basis to forecast shaking intensity in the minutes to hours after a large earthquake.

California

Distinguishing natural sources from anthropogenic events in seismic data

As seismic data are increasingly used to investigate a diverse range of subsurface phenomena beyond regular fast-rupturing earthquakes (Peng and Gomberg, 2010; Beroza and Ide, 2011), it is important to acknowledge that human-generated ground vibrations may be mistaken for naturally generated subsurface processes (Larose et al., 2015; Li et al., 2018). Correct discrimination of natural processes from anthropogenic noise is especially pressing given the trend in seismic detection research toward automated algorithms and machine learning methods (Yoon et al., 2015; Kong et al., 2019;Mousavi and Beroza, 2022) and the growth in seismic data collection in new environments such as urban and industry settings (e.g., Díaz et al.,2017).

Seismological Research Letters

pySATSI: A Python package for computing focal mechanism stress inversions

We introduce pySATSI, a Python package for computing earthquake focal mechanism stress inversions. This algorithm can handle a wide variety of types of stress inversion problems with a single script and can duplicate many capabilities of preceding methodologies. We also add new capabilities that include spatiotemporally variable inversion grids, damped stress estimates for clusters with few or no focal mechanisms, and variable fault‐plane ambiguities that the user can assign to individual events. In addition, we added the ability to use damped stress inversions with fault‐plane ambiguity probabilities that are weighted by fault instabilities. Our algorithm is computationally efficient with faster runtimes than previous algorithms, scales well for large datasets, and can be easily parallelized.

Seismological Research Letters

Preface to the focus section on earthquake-induced ground deformation

Ground failure due to earthquake-induced liquefaction, surface fault rupture, and landsliding has caused substantial damage in the past and continues to pose risks to critical infrastructure in the future. The consideration of ground failure is central to engineering analysis and design, ranging from site-specific engineering assessments of ground failure potential to broader regional-scale ground failure assessments of near-real-time earthquake impacts or longer-term portfolio risk. Uncertainties in all aspects of the problem complicate the prediction of earthquake-induced ground failure, including the identification of hazard-susceptible geomaterials, characterizing their spatial extent and physical properties, spatio-temporal variability in groundwater conditions, characterization of earthquake ground motions, assessing ground failure severity, and linking ground failure severity to infrastructure damage and loss.

Seismological Research Letters

Velocity-independent dry friction on mica: A realization of ideal Amontons-Coulomb friction

The Amontons-Coulomb friction law assumes that the frictional force between materials is independent of sliding velocity. However, as Coulomb noted, this is a rough approximation, and a second-order dependence of friction on the logarithm of sliding velocity is incorporated in a commonly used ‘rate- and state-dependent’ friction representation. Here we conduct shear experiments on mica, a layer-structured mineral, at temperatures ranging from 25 to 200ºC and under normal stress of 100 MPa. The friction coefficient clearly depends on the logarithmic sliding velocity at 25ºC, but rate sensitivity decreases with increasing temperature until at 200ºC, the friction coefficient is independent of sliding velocity. Our findings could initiate the development of velocity-independent frictional materials, realizing the ideal Amontons-Coulomb friction.

Physical Review Letters

S/P amplitude ratios with Distributed Acoustic Sensing and application to earthquake focal mechanisms

Distributed acoustic sensing (DAS), which transforms a fiber optic cable into an array of high frequency strainmeters, has the potential to help us characterize earthquakes with a dense sampling of measurements. While earthquake focal mechanisms are frequently determined using P -wave polarities and S / P amplitude ratios with inertial seismometers, the dense sampling of DAS over potentially large portions of the focal sphere can aid our solutions. Here, we consider ∼200 regional earthquakes and thousands of S / P measurements on a DAS cable colocated with a network of inertial seismometers near Arcata, California. We demonstrate the S / P ratio measurements made on DAS are similar to those made on the inertial seismometers and can be used to constrain focal mechanism solutions.

California

GRAPES: Earthquake early warning by passing seismic vectors through the grapevine

Estimating an earthquake's magnitude and location may not be necessary to predict shaking in real time; instead, wavefield-based approaches predict shaking with few assumptions about the seismic source. Here, we introduce GRAph Prediction of Earthquake Shaking (GRAPES), a deep learning model trained to characterize and propagate earthquake shaking across a seismic network. We show that GRAPES’ internal activations, which we call “seismic vectors”, correspond to the arrival of distinct seismic phases. GRAPES builds upon recent deep learning models applied to earthquake early warning by allowing for continuous ground motion prediction with seismic networks of all sizes. While trained on earthquakes recorded in Japan, we show that GRAPES, without modification, outperforms the ShakeAlert earthquake early warning system on the 2019 M7.1 Ridgecrest, CA earthquake.

Shimane/HiroshimaPrefectures

U.S. Geological Survey geomagnetic variometer data: Capitalizing on seismic infrastructure

The U.S. Geological Survey’s Geomagnetism Program is collaborating with the Earthquake Hazards Program and Global Seismographic Network Program to densify magnetic field observations. This collaboration focuses on the installation of magnetometers, or magnetic variometers, at existing seismic stations. Along with improving the density of space weather observations for hazard monitoring, these data can be used to correct colocated magnetic field induced noise in seismic data. Such corrections are especially useful during time periods of large magnetic storms where the magnetic field‐induced instrument noise can be of similar amplitude to earthquake ground‐motion records.

contiguous United States

A probabilistic assessment methodology for the evaluation of geologic energy storage capacity—Natural gas storage in depleted hydrocarbon reservoirs

The need for energy storage, particularly underground, where capacity and duration may far exceed battery storage technologies, is especially relevant given the increasing demands for reliable power alongside the development of intermittent renewable electricity sources. Geologic energy storage facilities already exist, and expanded use would enable storing gases such as methane and hydrogen. In 2018, a National Academies of Sciences, Engineering, and Medicine report, “Future Directions for the U.S. Geological Survey's Energy Resources Program,” recommended that the U.S. Geological Survey (USGS) prioritize assessing underground energy storage in geologic formations in the United States. The U.S. Geological Survey has since developed a methodology for assessing natural gas storage capacities in depleted hydrocarbon reservoirs on a national scale. The methodology introduced in this report prescribes three approaches for calculating gas storage capacity. This methodology relies on the availability of input data, including cumulative hydrocarbon production records, reservoir petrophysical properties, and reservoir pressure data. Assessment inputs can be obtained from public, State-level databases and propriety national-scale databases, although the use of analogs could be warranted for estimating input parameters. Probabilistic assessment results are aggregated to play, petroleum province, regional, and national scales. The steps defined in this report are demonstrated on the Michigan Basin Province, which includes the Mississippian Sandstone Gas Play and the Clinton Structural Play. This methodology could be used to systematically and consistently assess hydrocarbon plays and provinces for natural gas storage capacity across the United States.

Michigan

Anomalous shear stress variation in wet granular medium: Implications for landslide lateral faults

Landslide assessments typically focus on the mechanical properties of the basal shear zone, but lateral faults are frequently overlooked, possibly due to their lower normal stresses and variably saturated conditions. Using double-cylinder shear experiments on wet granular systems as analogs for landslide lateral faults, we observe anomalous shear stress variations with fluid volume fractions, defying an expected unimodal relationship associated with capillary cohesion. At low fluid volume fractions, shear strength weakens as the wet grain assembly experiences reduced lateral pressure and increased boundary slip. This boundary slip subsequently vanishes, with an abrupt strengthening due to the dilation of the grain assembly against fluid surface tension as saturation approaches. Strike-slip motion and confinement in this system explain the strength anomaly, highlighting a critical role of lateral faults in landslide stability, particularly in cases where dynamics cannot be adequately explained by monitored pore-water pressure or basal friction.

Geophysical Research Letters