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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Seismotectonics of thin- and thick-skinned deformation in the Andean foreland from local network data - Evidence for a seismogenic lower crust

Local network data from San Juan, Argentina, provides new information about crustal seismicity in the Andean foreland above a horizontal segment of the subducted Nazca Plate. Two areas of foreland seismicity are found, one associated with the Sierras Pampeanas basement uplifts, and the other beneath, but not within, the Precordillera foreland fold-thrust belt. The Precordillera seismicity provides direct evidence for basement deformation beneath the sediments of the thrust belt and supports the idea that its eastern part is significantly modified by underlying basement deformation. In both areas, events are concentrated between 15 and 35 km depth and have volumetric, rather than planar, faultlike distributions. The depth distribution is unusually deep for intraplate earthquakes and suggests a brittle-ductile transition near 30-35 km.

Smalley, Robert, Jr.↗
NASA NTRS1990

Present-day kinematics of the Rivera plate and implications for tectonics in southwestern Mexico

A model for the present-day motion of the Rivera plate relative to the North America, Cocos, and Pacific plates is derived using new data from the Pacific-Rivera rise and Rivera transform fault, together with new estimates of Pacific-Rivera motions. The results are combined with the closure-consistent NUVEL-1 global plate motion model of DeMets et al. (1990) to examine present-day deformation in southwestern Mexico. The analysis addresses several questions raised in previous studies of the Rivera plate. Namely, do plate motion data from the northern East Pacific rise require a distinct Rivera plate? Do plate kinematic data require the subduction of the Rivera plate along the seismically quiescent Acapulco trench? If so, what does the predicted subduction rate imply about the earthquake recurrence interval in the Jalisco region of southwestern Mexico?

Demets, Charles↗
DOE OSTI2023

A Fusion of Geothermal and InSAR Data with Machine Learning for Enhanced Deformation Forecasting at the Geysers

The Geysers geothermal field in California is experiencing land subsidence due to the seismic and geothermal activities taking place. This poses a risk not only to the underlying infrastructure but also to the groundwater level which would reduce the water availability for the local community. Because of this, it is crucial to monitor and assess the surface deformation occurring and adjust geothermal operations accordingly. In this study, we examine the correlation between the geothermal injection and production rates as well as the seismic activity in the area, and we show the high correlation between the injection rate and the number of earthquakes. This motivates the use of this data in a machine learning model that would predict future deformation maps. First, we build a model that uses interferometric synthetic aperture radar (InSAR) images that have been processed and turned into a deformation time series using LiCSBAS, an open-source InSAR time series package, and evaluate the performance against a linear baseline model. The model includes both convolutional neural network (CNN) layers as well as long short-term memory (LSTM) layers and is able to improve upon the baseline model based on a mean squared error metric. Then, after getting preprocessed, we incorporate the geothermal data by adding them as additional inputs to the model. This new model was able to outperform both the baseline and the previous version of the model that uses only InSAR data, motivating the use of machine learning models as well as geothermal data in assessing and predicting future deformation at The Geysers as part of hazard mitigation models which would then be used as fundamental tools for informed decision making when it comes to adjusting geothermal operations.

Yazbeck, Joe (ORCID:0000000302235260)↗
NASA NTRS1986

Mechanisms and depths of atlantic transform earthquakes

Mechanisms and depths of 40 earthquakes on major transforms along the Mid-Atlantic Ridge are studied in order to identify events that deviate from the transform-parallel strike-slip motion. Long and short period waves and Rayleigh wave spectral amplitudes are used to analyze focal mechanisms, depths, source time functions, and seismic moments of earthquakes. The relationship between centroid depths and transform thermal structures is examined. The data reveal that transform earthquake centroid depths occur above the predicted 400 C isotherms and the oceanic intraplate depths extend to the 750 C isotherm. Slip rates inferred from seismic moment releases are compared to those predicted by plate motions and good correlation is detected. The difference in the centroid depths of transform and interplate seismicity indicates transforms are either weaker or higher temperatures than expected.

Engeln, J. F.↗
NASA NTRS2015

The Age of Lunar South Circumpolar Craters Haworth, Shoemaker, Faustini, and Shackleton: Implications for Regional Geology, Surface Processes, and Volatile Sequestration

The interiors of the lunar south circumpolar craters Haworth, Shoemaker, Faustini, and Shackleton contain permanently shadowed regions (PSRs) and have been interpreted to contain sequestered volatiles including water ice. Altimetry data from the Lunar Orbiter Laser Altimeter (LOLA) onboard the Lunar Reconnaissance Orbiter provide a new means of examining the permanently shadowed interiors of these craters in unprecedented detail. In this study, we used extremely high-resolution gridded LOLA data of Haworth, Shoemaker, Faustini, and Shackleton to determine the size-frequency distributions and the spatial density of craters superposing their rims, inner slopes, and floors. Based on their population of superposed D greater than or equal to 2 km craters, Haworth, Shoemaker, and Faustini have pre-Nectarian formation ages. Shackleton is interpreted as having a Late Imbrian age on the basis of craters with diameter D greater than or equal to 0.5 km superposed on its rim. The local density of craters with sub-km diameters across our study area is strongly dependent on slope; because of its steep interior slopes, the lifetime of craters on the interior of Shackleton is limited. The slope-dependence of the small crater population implies that the population in this size range is controlled primarily by the rate at which craters are destroyed. This is consistent with the hypothesis that crater removal and resurfacing is a result of slopedependent processes such as diffusive mass wasting and seismic shaking, linked to micrometeorite and meteorite bombardment. Epithermal neutron flux data and UV albedo data show that these circumpolar PSRs, particularly Shoemaker, may have approximately 1-2% water ice by mass in their highly porous surface regolith, and that Shoemaker may have approximately 5% or more water ice by mass in the near subsurface. The ancient formation ages of Shoemaker, Faustini and Haworth, and the Late Imbrian (approximately 3.5 Ga) crater retention ages of their floors suggests that any water ice that might have been deposited in their permanently shadowed areas was insufficient to modify the superposed crater population since that time.

Circumpolar↗
NASA NTRSDate not supplied

High-Temperature MEMS Based Venus Seismometer

Seismology is the method of choice for studying a planet’s interior and assessing current tectonic activity. With a single strategically placed seismometer, or preferably a network of seismometers, a variety of key aspects of a planet can be evaluated. The level and nature of seismicity observed provides a gauge of current geologic, especially tectonic, activity. Where tectonic activity is and is not occurring illuminates what regions and geologic features on the planet are currently active, thus, constraining global geodynamics. Larger distal earthquakes can be used to determine major compositional and structural boundaries within a planet’s interior, providing major constraints on planet formation and interior evolution. Seismometers have been deployed successfully on the Moon and Mars. Only small subsets of the scientific knowledge that can be gained from seismology can be obtained from alternative scientific approaches, such as global gravity solutions or repeat-pass interferometry. By virtue of its similar size to Earth, Venus is likely to be highly seismically active (Fig. 1). Even at Earth-like levels of seismology, returning meaningful data would require observation over a period that is at least 2–3 orders of magnitude longer than the 1–2 h lifetime of previous Soviet landers. Clever insulation could extend the lifetime of standard electronics in a modern lander to perhaps 24 h. While active cooling of electronics for a Venusian lander is plausible, this approach would require considerable technological advancement and will likely come at a high monetary and mass cost. The high density of the Venusian atmosphere at the surface should mean that there is good coupling of seismic energy into the atmosphere, such that seismology using infrasound from a balloon platform is currently being explored, and observations of the upper levels of the atmosphere from orbit has also been proposed [3]. Besides losing all shear wave information with these two methods, calibrating and interpreting seismic information that has been distorted by, and convolved with, atmospheric phenomena will be challenging without existing seismology data collected through surface seismometers (optimally, simultaneous surface seismological observations would be made).

silicon carbide↗
DOE OSTI2025

Improving the Transportability of a Deep Learning Denoising Model Using Transfer Learning Techniques

The adoption of machine learning techniques in the seismology community has led to great performance improvements in several areas, including signal processing. Specifically, the development of deep learning–based seismic waveform denoising models has the potential to yield improvements in signal detection capabilities for networks operating in particularly noisy environments. Recent advancements in the design of these deep learning denoising models have included the incorporation of continuous and discrete wavelet transform functions into the network architecture to improve the learning capabilities and efficiency of said models. These wavelet transform–based seismic denoising models have shown improved denoising capabilities in regions where there is good agreement between the data features present in the training and evaluation datasets. However, questions remain about the overall transportability of these models to other monitoring regions. Here, in this study, we will determine the baseline transportability of a newly developed multilevel wavelet‐transform convolutional neural network (MWCNN) seismic denoising model. We accomplish this by taking a version of the MWCNN denoising model trained on data collected from the Utah region and evaluating its denoising performance on datasets collected from the neighboring Nevada region, which differ with regard to monitoring sensor types and event histories. We find that there is a notable variability in denoising performance related to the degree of similarity between the initial and new target datasets. The most notable difference in denoising performance is the ability of the denoising model to preserve accurate amplitude information associated with the signal energy present in the waveform data. Finally, we evaluate the ability of transfer learning techniques to improve the transportability of the MWCNN denoising model. We find that although there is still a performance gap present in the denoising results of the MWCNN model, transfer learning did yield improved results.

Quinones, Louis [Sandia National Laboratories (SNL↗
DOE OSTI2020

Play Fairway Analysis: Structurally Controlled Geothermal Systems in the Eastern Great Basin Extensional Regime, Utah

A research team with membership from the University of Utah/Energy & Geoscience Institute, the University of Utah/Dept. of Geology & Geophysics, and the Utah Geological Survey, undertook a play fairway analysis (PFA) for geothermal resources in the Eastern Great Basin (EGB) extensional tectonic regime of western Utah. This is a high-priority region for geothermal exploration because active Basin and Range (B&R) extension with volcanism having a N-S strike is superimposed upon pre-existing E-W belts of plutonic rocks and large-scale structural lineaments. Cumulative heat flow along the N-S strike of the state totals approximately 5 GWt above background stable interior. Three electricity producing power plants currently exist with substantial potential for increase. Succinctly, our PFA approach aims to resolve potential sources of heat and permeability in the region, which are the two principal criteria for establishing a geothermal resource. An initial Phase 1 was carried out using only existing geoscientific data in the area. Criteria selected for focusing heat potential include direct heat flow measurements in boreholes, magnetotelluric (MT) low resistivity anomalies, fluid/gas geochemistry, and proximity to recent volcanic eruptions. Permeability is established through geological structures (fault density, critically stressed areas, seismicity, gravity), and MT low resistivity anomalies. In Phase II of this PFA project, additional geological, geophysical and geochemical data were acquired and analysis carried out primarily over promising composite common risk (CCR) areas initially identified in Phase I in order to focus prospectivity and prepare for drilling recommendations. These prospects are near the Twin Peaks rhyolite field, high heat flow areas north of the producing Cove Fort system, and geophysical structure beneath the Crater Knoll area off the northeast flank of the Mineral Mountains. Additional data included MT site fill-in, structural mapping and analysis using high-resolution imagery, gravity and on-ground mapping, Nodal 3C passive seismic collection, and passive 3He surveying. Heat source and permeability potential are again expressed in terms of their individual common risk segment (CRS) maps, with a color scheme using green for most favorable (low risk) and red for least favorable (high risk). Diverse data types are united through the technique of probability kriging, which establishes prospectivity thresholds for each data type and then computes probability of exceeding that threshold over the PFA area. Modified CRS and CCRS maps are compared to those of Phase I to highlight tighter prospectivity focus. In doing so, the prospectivity threshold for heat was increased significantly to narrow the targeting. In the final Phase III of this project where a recommended deep thermal gradient hole was sited, additional geophysical, geochemical and geological field collection and analysis was carried out to refine drill hole targeting. This includes prospect-scale MT, gravity, structure, passive seismic deployment (Cove Fort area), and detailed 3He isotope profiling. It was the recommendation of the DOE Technical Monitoring Team (TMT) that one or more holes be sited in the north-ern Cove Fort area where legacy TG gradient holes showed high cumulative heat flow. These were to be of moderate depth, 2000-3000 feet, to reach the geothermal fluid table expected to start in excess of 1000 feet depth. The drilling organization stipulated by the DOE/GTO was that of the USGS Research Drilling Program (RDP) centered in Las Vegas, NV. A detailed well plan, appended to this report, was developed principally by Dr. Ben Barker consulting to University of Utah, Dr. Steve Pye on the DOE TMT, Mr. Steven Crawford of the USGS-RDP, and the project PI Phil Wannamaker. However, temperature and possible H 2 S at the systems lead to cancellation of the drilling last-minute as this appeared outside the experience base of the USGS-RDP. We hope to have the opportunity to revisit the test drilling and expand the Play Fairway Analysis of this region at some point in the future.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Aquifer Monitoring Using Ambient Seismic Noise Recorded With Distributed Acoustic Sensing (DAS) Deployed on Dark Fiber

Abstract Groundwater is a critical resource for human activities worldwide, and a vital component of many natural ecosystems. However, the state and dynamics of water‐bearing aquifers remain uncertain, mostly due to the paucity of subsurface data at high spatial and temporal resolution. Here, we show that analysis of infrastructure‐generated ambient seismic noise acquired on distributed acoustic sensing (DAS) arrays has potential as a tool to track variations in seismic velocities (d v / v ) caused by groundwater level fluctuations. We analyze 5 months of ambient noise acquired along an unused, 23 km‐long telecommunication fiber‐optic cable in the Sacramento Valley, CA, a so‐called “dark fiber." Three array subsections, ∼6 km apart, are processed and the stretching technique is applied to retrieve daily d v / v beneath each location. Near the Sacramento river, d v / v variations in the order of 2%–3% correlate with precipitation events and fluctuations in river stage of ∼1.5 m. In contrast, regions away (2.5 km) from the river do not experience large d v / v variations. These observations reveal short‐scale spatial variability in aquifer dynamics captured by this approach. Dispersion analysis and surface wave inversion of noise gathers reveal that seismic velocity perturbations occur at depths of 10–30 m. Rock physics modeling confirms that observed d v / v are linked to pore pressure changes at these depths, caused by groundwater table fluctuations. Our results suggest that DAS combined with ambient noise interferometry provides a means of tracking aquifer dynamics at high spatial and temporal resolutions at local to regional scales, relevant for effective groundwater resource management.

58 GEOSCIENCES↗
NASA NTRS1979

Velocity structure of the shallow lunar crust

Data from the thumper shots of the Apollo 14 and Apollo 16 active seismic experiments, testing whether the velocity variation in the shallow lunar crust (depths less than or equal to 10 m) can be represented by a self-compacting-power-layer or by a constant-velocity-layer model, are analyzed. Although filtering and stacking improved the S/N ratios, it was found that measuring the arrival times or amplitudes of arrivals beyond 32 m was not possible. The data quality precluded a definitive distinction between the power-law velocity variation and the layered-velocity model. Furthermore, it was found that the shallow lunar regolith is made up of fine particles, which supports the idea of a 1/6 power-velocity model. Analysis of the amplitudes of first arrivals revealed large errors in the data due to variations in the geophone sensitivities and shot strengths; a least-squares method, that uses data redundancy was employed to eliminate them.

Gangi, A. F.↗
DOE OSTI2024

Gulf of Mexico Miocene CO2 Site Characterization Mega Transect

The project Gulf of Mexico Miocene CO2 Site Characterization Mega Transect is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The University of Texas at Austin study focused on (1) collecting high-resolution, 3-D (HR3D) seismic datasets of the shallow geologic section to evaluate the capacity of potential reservoirs and the sealing capacity of the confining system, and (2) producing a regional CO2 atlas of Miocene age units of the upper Texas coast submerged lands (southeast Texas). The goal of the study was to evaluate the capability of the Miocene age geologic section of Texas submerged lands to permanently store large volumes of anthropogenic CO2. The geographic locations of three HR3D, “P-Cable” seismic surveys collected in the near-shore waters of southeast Texas offers a vertical and horizontal view (data “cube”) example from the second survey. The dataset's high quality allowed for defining recognizable geologic morphologies (shapes) and possible fluid content, which are important for determining an area’s prospects for geologic storage. The regional CO2 atlas of Miocene age units highlights several topics, including: (1) a regional analyses of petroleum systems as analogs for CO2 storage; (2) petrography, petrology, and extent of confining systems of the Miocene section; (3) static capacity estimate; and (4) examples of characterization methodologies of prospect areas. The HR3D datasets and regional analyses within the CO2 atlas of the offshore Texas Miocene provide a sound basis for a future generation of specific CO2 prospects in the study area.

.las↗
DOE OSTI2025

MTUQ: a framework for estimating moment tensors, point forces, and their uncertainties

SUMMARY We introduce MTUQ, an open-source Python package for seismic source estimation and uncertainty quantification, emphasizing flexibility and operational scalability. MTUQ provides MPI-parallelized grid search and global optimization capabilities, compatibility with 1-D and 3-D Green’s function database formats, customizable data processing, C-accelerated waveform and first-motion polarity misfit functions, and utilities for plotting seismic waveforms and visualizing misfit and likelihood surfaces. Applicability to a range of full- and constrained-moment tensor, point force, and centroid inversion problems is possible via a documented application programming interface, accompanied by example scripts and integration tests. We demonstrate the software using three different types of seismic events: (1) a 2009 intraslab earthquake near Anchorage, Alaska; (2) an episode of the 2021 Barry Arm landslide in Alaska; and (3) the 2017 Democratic People’s Republic of Korea underground nuclear test. With these events, we illustrate the well-known complementary character of body waves, surface waves, and polarities for constraining source parameters. We also convey the distinct misfit patterns that arise from each individual data type, the importance of uncertainty quantification for detecting multimodal or otherwise poorly constrained solutions, and the software’s flexible, modular design.

58 GEOSCIENCES↗
DOE OSTI2022

Optimizing Earthquake Nowcasting With Machine Learning: The Role of Strain Hardening in the Earthquake Cycle

Abstract Nowcasting is a term originating from economics, finance, and meteorology. It refers to the process of determining the uncertain state of the economy, markets or the weather at the current time by indirect means. In this paper, we describe a simple two‐parameter data analysis that reveals hidden order in otherwise seemingly chaotic earthquake seismicity. One of these parameters relates to a mechanism of seismic quiescence arising from the physics of strain‐hardening of the crust prior to major events. We observe an earthquake cycle associated with major earthquakes in California, similar to what has long been postulated. An estimate of the earthquake hazard revealed by this state variable time series can be optimized by the use of machine learning in the form of the Receiver Operating Characteristic skill score. The ROC skill is used here as a loss function in a supervised learning mode. Our analysis is conducted in the region of 5° × 5° in latitude‐longitude centered on Los Angeles, a region which we used in previous papers to build similar time series using more involved methods (Rundle & Donnellan, 2020, https://doi.org/10.1029/2020EA001097 ; Rundle, Donnellan et al., 2021, https://doi.org/10.1029/2021EA001757 ; Rundle, Stein et al., 2021, https://doi.org/10.1088/1361-6633/abf893 ). Here we show that not only does the state variable time series have forecast skill, the associated spatial probability densities have skill as well. In addition, use of the standard ROC and Precision (PPV) metrics allow probabilities of current earthquake hazard to be defined in a simple, straightforward, and rigorous way.

58 GEOSCIENCES↗
DOE OSTI2024

Enhancing Regional Seismic Velocity Models With Higher‐Resolution Local Results Using Sparse Dictionary Learning

Abstract We use sparse dictionary learning to develop transformations between seismic velocity models of different resolution and spatial extent. Starting with data in the common region of both models, the method can enhance a regional lower‐resolution model to match the style and resolution of local higher‐resolution results while preserving its regional coverage. The method is demonstrated by applying it to two‐dimensional V S and three‐dimensional V P and V S regional and local velocity models in southern California. The enhanced reconstructed regional results exhibit clear visual improvements, especially in the reconstructed V P / V S ratios, and better correlations with geological features. Moreover, the reconstructed regional V P , V S models outperform the original ones in comparison of simulated earthquake waveforms to observations. The improved fitting to observed waveforms extends beyond the domain of the overlapping region. The developed dictionary learning approach provides physically interpretable results and offers a powerful tool for additional applications of data enhancement in earth sciences.

Geochemistry & Geophysics↗
DOE OSTI2023

PubDAS: A PUBlic Distributed Acoustic Sensing Datasets Repository for Geosciences

During the past few years, distributed acoustic sensing (DAS) has become an invaluable tool for recording high-fidelity seismic wavefields with great spatiotemporal resolutions. However, the considerable amount of data generated during DAS experiments limits their distribution with the broader scientific community. Such a bottleneck inherently slows down the pursuit of new scientific discoveries in geosciences. Here, we introduce PubDAS—the first large-scale open-source repository where several DAS datasets from multiple experiments are publicly shared. PubDAS currently hosts eight datasets covering a variety of geological settings (e.g., urban centers, underground mines, and seafloor), spanning from several days to several years, offering both continuous and triggered active source recordings, and totaling up to ~90 TB of data. Here this article describes these datasets, their metadata, and how to access and download them. Some of these datasets have only been shallowly explored, leaving the door open for new discoveries in Earth sciences and beyond.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Internal structure and properties of Mars

Theoretical physical models of the Martian interior are presented in the light of recent and revised data and constraints. These models include thermal evolution, densities, and seismic-wave velocities. The interior of Mars appears to be earthlike in many respects. Although thermal models indicate that Mars has passed its peak of evolution, it may still have an asthenosphere and may be moderately active tectonically. Mars has an Fe-FeS core with a radius of 1500-2000 km. The mantle is enriched in FeO with an olivine composition of about Fo75. Theoretically determined seismic-wave velocities are relatively well constrained in the mantle, with upper-mantle P-wave velocities ranging from 7.64 to 7.80 km/sec. However, there are wide variations in P-wave velocity in the core, dependent on composition. The shadow zone due to the core is larger than earth's.

Johnston, D. H.↗
NASA NTRS1987

Compression of oceanic lithosphere - An analysis of intraplate deformation in the Central Indian Basin

The development of intraplate structure in the Central Indian Basin is examined using models in which deformation is due to flexural buckling and the hydrodynamic growth of instabilities. Comparison of the models reveal that in a strong viscous lithosphere, deformation of the layer occurs by flexural folding at a wavelength which corresponds to the flexural buckling theory; in a lithosphere of intermediate strength, the layer deforms by folding characterized by thickening which localizes beneath topographic heights; and in a relatively weak lithosphere, the layer incurs an even greater amount of localized thickening and deforms in the symmetric or pinch-and-swell mode by inverse boudinage. It is noted that the models in which the layer folds either flexurally or with periodic thickening correspond with observed depth distribution of seismicity in the Central Indian Basin and with experimental rock rheological data.

Zuber, Maria T.↗
NASA NTRS2015

Water in the Lithospheric Mantle Beneath a Phanerozoic Continental Belt: FTIR Analyses of Alligator Lake Xenoliths (Yukon, Canada)

Water in the mantle influences melting, metasomatism, viscosity and electrical conductivity. The Alligator Lake mantle xenolith suite is one of three bimodal peridotite suites from the northern Canadian Cordillera brought to the surface by alkali basalts, i.e., it consists of chemically distinct lherzolites and harzburgites. The lherzolites have equilibration temperatures about 50 C lower than the harzburgites and are thought to represent the fertile upper mantle of the region. The harzburgites might have come from slightly deeper in the mantle and/or be the result of a melting event above an asthenospheric upwelling detected as a seismic anomaly at 400-500 km depth. Major and trace element data are best interpreted as the lherzolite mantle having simultaneously experienced 20-25% partial melting and a metasomatic event to create the harzburgites. Well-characterized xenoliths are being analyzed for water by FTIR. Harzburgites contain 29-52 ppm H2O in orthopyroxene (opx) and (is) approximately140 ppm H2O in clinopyroxene (cpx). The lherzolites have H2O contents of 27-150 ppm in opx and 46-361 ppm in cpx. Despite correlating with enrichments in LREE, the water contents of the harzburgite pyroxenes are low relative to those of typical peridotite xenoliths, suggesting that the metasomatic agents were water-poor, contrarily to what has been suggested before. The water content of cpx is about double that of opx indicating equilibrium. Olivine water contents are low ((is) less than 5 ppm H2O) and out of equilibrium with those of opx and cpx, which may be due to H loss during xenolith ascent. This is consistent with olivines containing more water in their cores than their rims. Olivines exclusively exhibit water bands in the 3400-3000 cm-1 range, which may be indicative of a reduced environment.

Gelber, McKensie↗