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At least 1,153 records · Page 64

A Data-Driven Framework for Automated Detection of Aircraft-Generated Signals in Seismic Array Data Using Machine Learning

Abstract Ground motions associated with aircraft overflights can cover a significant portion of the seismic data collected by shallowly emplaced seismometers, such as new nodal and Distributed Acoustic Sensing systems. This article describes the first published framework for automated detection of aircraft on single channel and multichannel seismic data. The seismic data are converted to spectrograms in a sliding time window and classified as aircraft or nonaircraft in each window using a deep convolutional neural network trained with analyst-labeled data. A majority voting scheme is used to convert the output from the sequence of sliding time windows onto a decision time sequence for each channel and to combine the binary classifications on the decision time sequences across multiple channels. Precision, recall, and F-score are used to quantify the detection performance of the algorithm on nodal data using fourfold time-series cross validation. By applying our framework to data from the Sage Brush Flats nodal array in Southern California, we provide a benchmark performance and demonstrate the advantage of using an array of sensors.

Geochemistry & Geophysics↗

Narrow-Band Least-Squares Infrasound Array Processing

Infrasound data from arrays can be used to detect, locate, and quantify a variety of natural and anthropogenic sources from local to remote distances. However, many array processing methods use a single broad frequency range to process the data, which can lead to signals of interest being missed due to the choice of frequency limits or simultaneous clutter sources. In this work, we introduce a new open-source Python code that processes infrasound array data in multiple sequential narrow frequency bands using the least-squares approach. We test our algorithm on a few examples of natural sources (volcanic eruptions, mass movements, and bolides) for a variety of array configurations. Our method reduces the need to choose frequency limits for processing, which may result in missed signals, and it is parallelized to decrease the computational burden. Improvements of our narrow-band least-squares algorithm over broad-band least-squares processing include the ability to distinguish between multiple simultaneous sources if distinct in their frequency content (e.g., microbarom or surf vs. volcanic eruption), the ability to track changes in frequency content of a signal through time, and a decreased need to fine-tune frequency limits for processing. We incorporate a measure of planarity of the wavefield across the array (sigma tau, στ) as well as the ability to utilize the robust least trimmed squares algorithm to improve signal processing and insight into array performance. Our implementation allows for more detailed characterization of infrasound signals recorded at arrays that can improve monitoring and enhance research capabilities.

58 GEOSCIENCES↗

Distinguishing Unique Earthquakes with Overlapping Signals in Oklahoma

Abstract During routine operations monitoring Oklahoma earthquakes, we found that certain earthquakes occurred closely both in space and time and had overlapping phases at the recording stations. Through further scrutiny and analysis, we determined that rather than being distinctly different earthquakes, some of the earthquakes exhibited multiphase arrivals and longer than expected coda due to unique ray paths that encounter impedance contrasts such as at the sedimentary rock-basement. Of course, some of these events truly were distinct events, which we term overlapping earthquakes, for which perceived coda duration overlaps and obscures the phase arrivals of the second event due to the source proximity in both time and space. We detail our classification scheme to separate the local earthquakes in Oklahoma as single, overlapping earthquakes, or those associated with multiphase arrivals. We forward model seismic wave propagation in a 2D crustal model and develop a methodology that utilizes waveform correlation to distinguish phases from overlapping earthquakes to those from crustal reverberations. Duration analysis shows a more elongated duration, qualitatively similar to the duration produced by overlapping earthquakes, at the sites where multiphase arrivals are observed.

Geochemistry & Geophysics↗

Regional Characteristics of Observable Foreshocks

Abstract Measures of foreshock occurrence are systematically examined using earthquake catalogs for eight regions (Italy, southern California, northern California, Costa Rica, Onshore Japan, Alaska, Turkey, and Greece) after imposing a magnitude ≥3.0 completeness level. Foreshocks are identified using three approaches: a magnitude-dependent space + fixed-time windowing method, a nearest-neighbor clustering method, and a modified magnitude-dependent space + variable-time windowing method. The method with fixed-time windows systematically yields higher counts of foreshocks than the other two clustering methods. We find similar counts of foreshocks across the three methods when the magnitude aperture is equalized by including only earthquakes in the magnitude range M*−2≤ M< M*, in which M* is the mainshock magnitude. For most of the catalogs (excluding Italy and southern California), the measured b-values of the foreshocks of all region-specific mainshocks are lower by 0.1–0.2 than b-values of respective aftershocks. Allowing for variable-time windows results in relatively high probabilities of having at least one foreshock in Italy (∼43%–56%), compared to other regional catalogs. Foreshock probabilities decrease to 14%–41% for regions such as Turkey, Greece, and Costa Rica. Similar trends are found when requiring at least five foreshocks in a sequence to be considered. Estimates of foreshock probabilities for each mainshock are method dependent; however, consistent regional trends exist regardless of method, with regions such as Italy and southern California producing more observable foreshocks than Turkey and Greece. Some regions with relatively high background seismicity have comparatively low probabilities of detectable foreshock activity when using methods that account for variable background, possibly due to depletion of near-failure fault conditions by background activity.

Geochemistry & Geophysics↗

Crustal Strain Rates in the Western United States and Their Relationship with Earthquake Rates

Abstract We present a suite of strain rate models for the western United States based on geologic and geodetic data. The geologic data consist of Quaternary fault-slip rates and the geodetic data consists of a new compilation of Global Positioning System (GPS) velocities derived from continuous, semicontinuous, and campaign measurements. We remove postseismic deformation from the GPS time series in order for our geodetic strain rate model to best capture the interseismic strain accumulation rate. We present models based on either geologic or geodetic data, but also create a hybrid model. Although there are some differences between the models, the large-scale features are the same, with the noticeable exception for the Pacific Northwest where interseismic strain is naturally more distributed than the long-term strain release. We also present a map of earthquake rate densities based on mainshocks, and the result has similar spatial features similar to the strain rate models (at least in the southwestern United States). We perform a general correlation analysis between strain rate and seismicity rate (south of Cascadia) and find a change in linearity between seismicity and strain rates from slow to faster deforming areas with seismicity rates relatively lower for the latter. The extent of that change depends a bit on assumptions made on the declustering and completeness of the catalog, but the finding of a change in slope is robust across the different strain rate models. Linearity for all areas is only expected when Gutenberg–Richter parameters and parameters involved in the conversion from strain to moment rate are uniform across the study area. We discuss these qualifications, but find no single satisfactory explanation for our observation. Moreover, when considering a rather short time and space, theoretical considerations of sampling from a power-law distribution actually predict there to be a power law instead of a linear relationship, generally consistent with our observation.

Geochemistry & Geophysics↗

Variable Daily Autocorrelation Functions of High-Frequency Seismic Data on Mars

Abstract High-frequency seismic data on Mars are dominated by wind-generated lander vibrations, which are radiated partially to the subsurface. Autocorrelation functions (ACFs) of seismic data on Mars filtered between 1 and 5 Hz show clear phases at ∼1.3, ∼2.6, and ∼3.9 s. Daily temporal changes of their arrival times (dt/t) correlate well with the daily changes of ground temperature, with ∼5% daily variation and ∼50 min apparent phase delay. The following two mechanisms could explain the observations: (1) the interference of two predominant spectral peaks at ∼3.3 and ∼4.1 Hz, assumed to be both lander resonance modes, generate the apparent arrivals in the ACFs; (2) the interference of the lander vibration and its reflection from an interface ∼200 m below the lander generate the 3.3 Hz spectral peak and ∼1.3 s arrival in the ACFs. The driving mechanism of the resolved dt/t that most likely explains the ∼50 min delay is thermoelastic strain at a near-surface layer, affecting the lander–ground coupling and subsurface structures. The two outlined mechanisms suggest, respectively, up to ∼10% changes in ground stiffness at 1–5 Hz and ∼15% velocity changes in the top ∼20 m layer. These are upper bound values considering also other possible contributions. The presented methodology and results contribute to analysis of ACFs with limited data and the understanding of subsurface materials on Mars.

Geochemistry & Geophysics↗

Global Characteristics of Observable Foreshocks for Large Earthquakes

Abstract Foreshocks are the only currently widely identified precursory seismic behavior, yet their utility and even identifiability are problematic, in part because of extreme variation in behavior. Here, we establish some global trends that help identify the expected frequency of foreshocks as well the type of earthquake most prone to foreshocks. We establish these tendencies using the global earthquake catalog of the U.S. Geological Survey National Earthquake Information Center with a completeness level of magnitude 5 and mainshocks with Mw≥7.0. Foreshocks are identified using three clustering algorithms to address the challenge of distinguishing foreshocks from background activity. The methods give a range of 15%–43% of large mainshocks having at least one foreshock but a narrower range of 13%–26% having at least one foreshock with magnitude within two units of the mainshock magnitude. These observed global foreshock rates are similar to regional values for a completeness level of magnitude 3 using the same detection conditions. The foreshock sequences have distinctive characteristics with the global composite population b-values being lower for foreshocks than for aftershocks, an attribute that is also manifested in synthetic catalogs computed by epidemic-type aftershock sequences, which intrinsically involves only cascading processes. Focal mechanism similarity of foreshocks relative to mainshocks is more pronounced than for aftershocks. Despite these distinguishing characteristics of foreshock sequences, the conditions that promote high foreshock productivity are similar to those that promote high aftershock productivity. For instance, a modestly higher percentage of interplate mainshocks have foreshocks than intraplate mainshocks, and reverse faulting events slightly more commonly have foreshocks than normal or strike-slip-faulting mainshocks. The western circum-Pacific is prone to having slightly more foreshock activity than the eastern circum-Pacific.

Geochemistry & Geophysics↗

Tracking Seismic Velocity Perturbations at Ridgecrest Using Ballistic Correlation Functions

Abstract We present results based on data of a dense nodal array composed of 147 stations, deployed in 2022 near the epicenter of the 2019 Mw 7.1 Ridgecrest earthquake to investigate characteristics of the seismic wavefields. Through array analyses, we identified two primary components. First, we observed far-field P waves dominating the 0.5–1.2 Hz frequency range, which are likely primarily generated by wind-driven oceanic swell activity. Second, we detected near-field body waves resulting from anthropogenic activities in the frequency range 2–8 Hz. We examined noise correlation functions derived from data of the dense deployment and regional stations to explore fault-zone seismic velocity changes using ballistic arrivals, with a focus on velocity perturbation shortly before and after the Ridgecrest earthquake sequence. Our findings exhibit distinct behavior compared to results obtained through standard coda-wave interferometry. Particularly, we observed a decrease in P-wave travel time on certain station pairs prior to the 2019 earthquake sequence. Supported by detailed investigation of the local seismic wavefields, we interpret the decreasing P-wave travel time as likely caused by a velocity increase away from the fault, possibly related to fluid migration. However, additional information is necessary to verify this hypothesis.

Geochemistry & Geophysics↗

Seismic Monitoring near Ithaca, New York, Reveals Nonuniform Distribution of Microseismicity in an Intraplate Region

Abstract Cornell University intends to use a deep direct-use geothermal system to heat its Ithaca, New York, campus. In preparation for this project, the Cornell Seismic Network has been monitoring the background seismicity in this intraplate region since 2019. From January 2020 to June 2023, 95 events were detected within 20 km of the proposed geothermal well site, with local magnitudes ranging from −1.02 to 0.56. None of these events appear in regional or national catalogs. Events locate in a narrow geographic band, with one-fourth exhibiting multimodal hypocentral probability peaks both near the surface and at 1–4 km depth. We relocate events with a joint hypocenter and 1D velocity model inversion, in addition to a fully nonlinear method, and then compare observations with synthetic waveforms. Together, these approaches provide strong evidence for >95% of events locating at the surface or within the 3-km-thick sedimentary sequence. We explore how anthropogenic activity and regional topographic stress may contribute to frequent surficial events. This information is critical for characterizing the background microseismicity for comparison during future geothermal operations. Ithaca’s geology of Paleozoic sediments overlying Precambrian crystalline basement is typical of many continental interiors, so these results also provide insight into intraplate microseismicity patterns.

Geochemistry & Geophysics↗

Cardinal: Seismic and Geoacoustic Array Processing

Data collected via seismic and infrasound array deployments are leveraged in the geosciences to detect and characterize a myriad of natural and anthropogenic sources. These deployments consist of numerous sensors placed in a predetermined configuration to amplify signal strength and improve the efficacy of array processing techniques used to measure signal directionality and waveform coherence. High‐fidelity feature extraction is often predicated on interstation distance as well as the frequency content and wavelength of an incident signal. Numerous array processing softwares analyze data in sequential frequency bands to obtain a more detailed characterization of a signal. However, current algorithms are limited in their ability to determine optimal array configuration for each band. We introduce an open‐source Python code, called Cardinal, to process seismic and infrasound array data in discretized time–frequency space with the option of applying an adaptive array design to determine optimal subarray configuration for each frequency band. To reduce computational time, the array processing step can be run in parallel using multithreading. Furthermore, the software has the capability to aggregate array processing results from different time–frequency pixels to produce separate sets of detections, or families, with added utility via the application of an adaptive semblance threshold, which aids in isolating signals‐of‐interest from coherent background noise. Upon appropriate configuration, Cardinal exhibits the potential to combine distinct seismic and infrasound phases into separate families.

Adaptive Array↗

FutureGen 2.0 Technical Data

This is a comprehensive collection of all original surface and subsurface technical data, as well as various derivative subsurface models, collected from the FutureGen 2.0 project. This collection of data has been vetted for confidential or sensitive documents.

CCUS↗

Fiber Optic Distributed Acoustic Sensing in DFPS East Well

Fiber optic files in *.hdf format, acquired in the Devine Fracture Pilot Site East well, using Fotech interrogator. There was no change in channel spacing or acquisition settings during the project. Channel spacing is 0.68 m.

Electrically active proppant,Electromagnetic,Fiber↗

Petrographic and spectral study of hydrothermal mineralization in drill core from Hawaii: A potential analog to alteration in the martian subsurface

Abstract Continuous rock core was collected for 1764 m (5786’) on the Pohakuloa Army Training base near the center of the big island of Hawaii. The core traverses basaltic lava flows from the volcano's shield-building phase, and perched aquifers and higher temperature groundwaters were encountered. The collected samples record water-rock interactions of basaltic materials in a setting that may be a model for groundwater interactions on Mars. We collected visible and infrared point spectra of materials in the lowest portion of the core, where alteration was noted to become more prominent. We identified three types of phyllosilicate spectral signatures and three types of zeolites. The phyllosilicates show similarity to those identified on Mars using data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). Based on the field survey, 25 depths were selected for sampling and petrographic analysis of thin sections. The spectral data and thin section work have a strong agreement in the types of materials identified by the two different techniques. Both the spectral and petrographic data indicate low to moderate temperature geothermal alteration occurred in the lower half of the core. The field spectra are a useful reconnaissance tool for selecting mineralogic diversity for subsequent higher resolution and more time-consuming laboratory analysis.

Geochemistry & Geophysics↗

The new K, Pb-bearing uranyl-oxide mineral kroupaite: Crystal-chemical implications for the structures of uranyl-oxide hydroxy-hydrates

Abstract Kroupaite (IMA 2017-031), ideally KPb0.5[(UO2)8O4(OH)10]·10H2O, is a new uranyl-oxide hydroxylhydrate mineral found underground in the Svornost mine, Jáchymov, Czechia. Electron-probe micro-analysis (WDS) provided the empirical formula (K1.28Na0.07)Σ1.35(Pb0.23Cu0.14Ca0.05Bi0.03Co0.02Al0.01)Σ0.48 [(UO2)7.90(SO4)0.04O4.04(OH)10.00]·10H2O, on the basis of 40 O atoms apfu. Sheets in the crystal structure of kroupaite adopt the fourmarierite anion topology, and therefore kroupaite belongs to the schoepite-family of minerals with related structures differing in the interlayer composition and arrangement, and charge of the sheets. Uptake of dangerous radionuclides (90Sr or 135Cs) into the structure of kroupaite and other uranyl-oxide hydroxy-hydrate is evaluated based on crystal-chemical considerations and Voronoi-Dirichlet polyhedra measures. These calculations show the importance of these phases for the safe disposal of nuclear waste.

Geochemistry & Geophysics↗

Precipitation of low-temperature disordered dolomite induced by extracellular polymeric substances of methanogenic Archaea Methanosarcina barkeri : Implications for sedimentary dolomite formation

Abstract A correlation between methanogenesis and dolomite formation has been reported; however, the mechanism underlying this association is not fully understood. In this study, we conducted forced carbonate precipitation experiments at room temperature in calcite-seeded Ca/Mg carbonate solutions containing either purified non-living biomass or bound extracellular polymeric substances (EPS) of the methanogen Methanosarcina barkeri. Purified non-living biomass and bound EPS was used so as to avoid the possible influence of the complex components of the growing microbial culture on carbonate crystallization. Our results demonstrated that non-living biomass of M. Barkeri can enhance the Mg incorporation into calcitic structure and induce the crystallization of disordered dolomite. In the presence of ~113 mg L–1 of non-living biomass, disordered dolomite with ~41 and 45 mol% of MgCO3 was precipitated in solutions with initial Mg:Ca ratios of 5:1 and 8:1, respectively. A systematic increase in the MgCO3 contents of the precipitated Ca-Mg carbonates was also observed with the increased non-living biomass concentration. Bound EPS was shown to be the component of non-living biomass that catalyzed the precipitation of disordered dolomite. At only ~25 mg L–1 of bound EPS, disordered dolomite with ~47 and 48 mol% of MgCO3 was precipitated in solutions with initial Mg:Ca ratios of 5:1 and 8:1, respectively. We propose that adsorption of bound EPS to growing carbonate surfaces through hydrogen bonding is the key to catalyzing disordered dolomite crystallization, and that this mechanism is also applicable to natural EPS-induced dolomite formation. This study provides significant insight into the formation mechanism of microbial-induced dolomite with high δ13C values.

Geochemistry & Geophysics↗

Thermodynamic characterization of synthetic lead-arsenate apatites with different halogen substitutions

Abstract Thermodynamic parameters have been measured for synthetic analogs of the mimetite-group minerals Pb5(AsO4)3X (X = OH, Cl, Br, I) belonging to the apatite supergroup. Phases precipitated from aqueous solutions under ambient conditions with well characterized structures and compositions were studied. For each phase, dissolution enthalpy was experimentally determined by oxide melt drop solution calorimetry in a molten solvent of sodium molybdate (3Na2O·4MoO3) at 976 K. The enthalpy of formation from the elements ΔHf,elo was calculated using thermochemical cycles and was −3030.6 ± 11.5, −3026.6 ± 15.8, −2967.6 ± 25.0, and −2993.1 ± 12.2 kJ/mol for Pb5.00(AsO4)3.00OH0.86(CO3)0.07, Pb5.00(AsO4)3.00Cl0.80(CO3)0.10, Pb5.00(AsO4)3.00Br0.80(CO3)0.10, and Pb5.00(AsO4)3.00I0.45OH0.35(CO3)0.10, respectively. These ΔHf,elo values exhibit typical trends for apatites: they increased (were less negative) with the increasing molar mass and ionic radius of X and decreased with the electronegativity and ionization energy of X. The compilation and comparison of data for Ca-, Pb-, P-, and As-apatites revealed correlations indicating that thermodynamic enthalpic stability is largely influenced by chemical factors (e.g., differences in electronegativities of the elements, ionization energy, or ionic characteristics of the bonds) and to a lesser extent by physical and geometric parameters in the crystal structure related to the mass and size of the X anion. Using the correlations, it was possible to estimate the value of hitherto unknown ΔHf,elo for Pb5(AsO4)3F, −3144.3 ± 66.5 kJ/mol. The observed relationships apply to the entire apatite supergroup and can be used to predict the values of ΔHf,elo for phases that have not been studied experimentally. The new data on environmentally significant phases will contribute to the modeling of mineral-water interactions, particularly for potential use in the remediation of soils and wastes contaminated with Pb and As and in the immobilization of radioactive waste containing I-129.

Geochemistry & Geophysics↗

Seaborgite, LiNa6K2(UO2)(SO4)5(SO3OH)(H2O), the First Uranyl Mineral Containing Lithium

Abstract Seaborgite (IMA2019-087), LiNa6K2(UO2)(SO4)5(SO3OH)(H2O), is a new mineral species from the Blue Lizard mine, Red Canyon, San Juan County, Utah, U.S.A. It is a secondary phase found on gypsum in association with copiapite, ferrinatrite, ivsite, metavoltine, and römerite. Seaborgite occurs in sprays of light-yellow, long flattened prisms or blades, up to about 0.2 mm in length. Crystals are elongated on [100], flattened on {010}, and exhibit the forms {100}, {010}, {001}, and {101}. The mineral is transparent with vitreous luster and very pale-yellow streak. It exhibits bright lime-green fluorescence under a 405 nm laser. The Mohs hardness is ~2½. The mineral has brittle tenacity, curved or conchoidal fracture, and one good cleavage on {100}. The measured density is 2.97(2) g/cm3. The mineral is immediately soluble in H2O at room temperature. The mineral is optically biaxial (–), α = 1.505(2), β = 1.522(2), γ = 1.536(2) (white light); 2Vmeas = 85(1)°; moderate r < ν dispersion; orientation X ^ a ≈ 10°; pleochroic X colorless, Y and Z light green-yellow; X < Y ≈ Z. EPMA and LA-ICP-MS analyses of seaborgite undermeasured its Li, K, and Na. The empirical formula using Li, Na, and K based on the structure refinement is Li1.00Na5.81K2.19(UO2)(SO4)5(SO3OH)(H2O). Seaborgite is triclinic, P1, a = 5.4511(4), b = 14.4870(12), c = 15.8735(15) Å, α = 76.295(5), β = 81.439(6), γ = 85.511(6)°, V = 1203.07(18) Å3, and Z = 2. The structure (R1 = 0.0377 for 1935 I = 2σI) contains [(UO2)2(SO4)8]4– uranyl-sulfate clusters that are linked into a band by bridging LiO4 tetrahedra. The bands are linked through peripheral SO4 tetrahedra forming a thick heteropolyhedral layer. Channels within the layers contain a K site, while an additional K site, six Na sites, and an SO3OH group occupy the space between the heteropolyhedral layers.

Geochemistry & Geophysics↗