We present the results of a finite element analysis of the electro-optical non-equivalence of planar electrical substitution radiometers with vertically aligned carbon nanotube absorbers, operating at either room or cryogenic temperature. These detectors are the basis of the new room temperature standards of the Laboratory for Atmospheric and Space Physics' (LASP) Total solar irradiance Radiometer Facility and the Spectral solar irradiance Radiometer Facility, and the NIST Boulder open beam cryogenic radiometer facility. We show that the detector of our cryogenic electrical substitution radiometer has no significant electro-optical non-equivalence. Further, we also show that with careful detector design, the non-equivalence can be minimized at room temperature. It was found that in general the non-equivalence cannot be deduced from the temperature mismatch between the electrical and the optical states without considering the conductance mismatch and optical power input. The results are regarded as being precise rather than absolute to account for potentially unknown modeling errors. The numerical accuracy is typically less than 5 ppm.

We analyze the relationship between geothermal energy production and seismic hazards in the Salton Sea Geothermal Field (SSGF) between 1972 and 2022. A clear increase in seismic activity accompanies geothermal energy production and is greatest to the east of the Brawley fault, where the amount of injection exceeds the amount of production. We estimate that, whereas there was a 2% chance of a M6.07 earthquake nucleating inside the SSGF within a fifty-year period prior to energy production (pre-production), there is an equal probability that a M6.70 earthquake nucleates there in a fifty-year period during which historically average energy production conditions persist (syn-production). Similarly, we estimate a 2% chance of a M7.15 and M6.92 occurring in the broader Brawley Seismic Zone (excluding the SSGF) within a fifty-year period during the pre- and syn-production eras, respectively. We find that linear regression models fail to reliably forecast the background seismicity rate as a function of fluid production and injection.

We have developed a technique to determine the electrical substitution power of a cryogenic optical radiant power detector, that directly implements a frequency-programmable Josephson voltage standard (FPJVS), thus reducing the traceability chain. The optical power detector and the Josephson voltage reference are combined inside a common cryogenic environment. We demonstrate the practicality of the technique by using a FPJVS to apply a known voltage across the resistive heater of a standard NIST cryogenic planar radiometric detector. The power applied to the detector heater is calculated from a measurement of the heater resistance and the known applied voltage. The FPJVS dc bias current source supplies dc current to the resistive heater. In this demonstration, the standard uncertainty of the substituted electrical power is limited by the uncertainty of the electrical heater four-wire resistance measurement at 4 K. The uncertainty due to the resistance measurement is 1 part in 105 out of a total uncertainty of 1 part in 104 (k = 2) on the 1 mW optical power measurement. We aim to develop the technique, to provide traceability to the International System of Units for the picowatt power measurement of single-photon emitters such as quantum dot sources.

SUMMARY Enigmatically strong tube waves continue to exist long after the direct wave during repeat crosswell-monitoring surveys at the Nagaoka CO2 injection site in Japan. The tube waves, which have linear moveouts with velocities of 1.29 and 1.41 km s−1 at plastic and steel casings, respectively, are generated by double scattering on the shallow side of the wells. We characterize wavefields to confirm that these late coda waves are tube waves that are excited at the source well, propagate upward, then travel to a receiver well as a body wave, and finally propagate downward along the receiver well. Even though these tube waves result from second-order scattering, they have large amplitudes because of the relatively short distance between source and receiver wells. Because these waves propagate along both wells many times, we can extract detailed information of wave propagation by averaging them to increase the signal-to-noise ratio. We first use the tube waves to relocate sources and receivers between multiple monitoring surveys, demonstrating our ability to correct the severe noise caused by location errors that frequently degrades the repeatability of time-lapse surveys. Then, we apply an inversion based on the physics of tube waves to estimate the location and strength of the scatterers and find that they are predominantly located in the shallow segment of the wells, above the sources, and infer that they are related to local fractures and/or wellbore conditions because their locations do not correspond to the well geometry. Lastly, we use the tube waves to accurately estimate subsurface velocities along the wells. The estimation is stable and robust, and the velocities follow the general trend of subsurface structure seen in the well log data. Due to the receiver spacing, tube-wave analysis cannot resolve a thin, high-velocity layer at the CO2 reservoir. By combining tube waves observed during different stages of the monitoring survey, we can estimate the time-lapse changes of the subsurface velocities.

Fluids injected during hydraulic fracturing (fracking) in unconventional shale oil and gas reservoirs, geothermal system enhancement, wastewater disposal, and carbon capture and storage can induce microearthquakes. The spatiotemporal distribution of induced earthquakes is often used to trace the growth of fractures in target layers and guides production. We analyze microseismicity behavior induced by fracking in the Montney Formation, one of the largest unconventional oil and gas reservoirs in North America. An optical fiber deployed in a horizontal well provides extensive spatial sampling and data coverage for microseismic imaging. We design median and F-k filters to predict instrumental and random noise and further suppress them by adaptive noise subtraction. An elliptical vertical transverse isotropic (VTI) velocity model is derived from the Backus-averaged well-log sonic data and is modified to match the microseismic wavefronts by a grid search. We image 41 previously cataloged microearthquakes recorded by distributed acoustic sensing (DAS) using geometric-mean reverse time migration. We find that the fiber geometry’s lack of 2-D/3-D variations increases the nonuniqueness of the image point location, and the $P$ -wave particle motions derived from three-component (3C) geophones data can effectively eliminate the location ambiguity. The spatiotemporal distribution of our updated locations agrees with the fracking schedule. Predicted $P$ - and $S$ -wave travel times from the updated locations also match with the observed waveforms. Analyzing data sensitivity to source locations confirms the potential limitations imposed on source imaging by the geometry of borehole observations and shows that relocation accuracy is directionally dependent. We also investigate the feasibility of estimating source focal mechanisms using realistic DAS and geophone observations. Our study provides guidance for characterizing microearthquake sources and optimizing observation geometry for unconventional reservoirs.

Most conceptual models for how fluids and sediment influence slip behavior and uplift along subduction margins are poorly constrained by geophysical observations. Given the complexity of subduction systems, overcoming this gap in knowledge will require a systems-level approach which uses high quality geophysical constraints. We present wide-angle, onshore-offshore seismic data collected along the northern Hikurangi margin, New Zealand, from which P-wave velocities were calculated using active- and passive-sources. A gravity model and reflection profiles were also assembled to create a complete, ~400 km long transect which images the incoming plate, down going slab, overthrusting forearc, and backarc rift. Velocities and gravity modelling help to constrain the lithology of the forearc basement to ~20 km depth. Upper plate lower crustal velocities and reflectivity point to the presence of underplated sediments immediately above the lithospheric mantle nose, suggesting that underplated sediments are driving uplift of the forearc. Comparing these results to geophysical images from the southern Hikurangi margin, we suggest that the backarc rift influences along-strike changes in the compressional stresses experienced by the forearc, driving changes in bending stresses within the subducting slab.

FastMapSVM is a recently developed Machine Learning framework that combines the complementary strengths of FastMap and SVMs for classification tasks. It is particularly useful when it is easier to measure the dissimilarity between pairs of objects in the domain via a well-defined distance function on them than it is to identify and reason about complex characteristic features of individual objects. The success of FastMapSVM has also been recently demonstrated in the Earthquake Science domain, where the objects are seismograms that need to be classified as earthquake signals or noise signals. In this paper, we first define various distance functions on seismograms. We then study the effects of these different distance functions on the performance characteristics of FastMapSVM. We also evaluate the different distance functions on their ability to provide perspicuous visualizations of the seismograms, their spread, and the classification boundaries between them.

Modern high-performance computing (HPC) tasks overwhelm conventional geophysical data formats. We describe a new data schema called HDF5eis (read H-D-F-size) for handling big multidimensional time series data from environmental sensors in HPC applications and implement a freely available Python application programming interface (API) for building and processing HDF5eis files. HDF5eis augments the popular Hierarchical Data Format 5 with a minimal set of additional conventions that facilitate fast and flexible data input and output protocols for regularly sampled (in time) data with any number of dimensions. HDF5eis supports arbitrary ancillary data (e.g., metadata) storage in columnar format or as UTF-8 encoded byte streams alongside time series data. Our HDF5eis API enables simple and efficient access to big data sets distributed across a potentially large number of small heterogeneous files through a single point of access. HDF5eis outperforms conventional seismic data formats by up to two orders of magnitude in terms of random read access times. We contribute HDF5eis as an operational tool and an experimental draft proposal that will help establish the next generation of data standards in the earth sciences.

Neural networks and related deep learning methods are currently at the leading edge of technologies used for classifying complex objects such as seismograms. However they generally demand large amounts of time and data for model training and their learned models can sometimes be difficult to interpret. FastMapSVM is an interpretable machine learning framework for classifying complex objects, combining the complementary strengths of FastMap with support vector machines (SVMs) and extending the applicability of SVMs to domains with complex objects. FastMap is an efficient linear-time algorithm that maps complex objects to points in a Euclidean space while preserving pairwise domain-specific distances between them. Here we invoke FastMapSVM as a lightweight alternative to neural networks for classifying seismograms. We demonstrate that FastMapSVM outperforms other state-of-the-art methods for classifying seismograms when train data or time is limited. We also show that FastMapSVM can provide an insightful visualization of seismogram clustering behaviour and thus earthquake classification boundaries. We expect FastMapSVM to be viable for classification tasks in many other real-world domains.

The tectonic setting of Timor–Leste and Eastern Indonesia comprises of a complex transition from oceanic lithosphere subduction to arc-continental collision. To better understand the deformation and convergent-zone structure of the region, we derive a new catalog of earthquake hypocenters and magnitudes from a temporary deployment of five years of continuous seismic data using an automated processing procedure. This includes a machine-learning phase picker, EQTransformer, and a sequential earthquake association and location workflow. We detect and locate ∼19,000 events during 2014–2018, which demonstrates that it is possible to characterize earthquake sequences from raw seismic data using a well-trained machine-learning picker for a complex convergent plate setting. This study provides the most complete catalog available for the region for the duration of the temporary deployment, which includes a complex pattern of crustal events across the collision zone and into the back-arc, as well as abundant deep slab seismicity.

We present the results of a recent, extensive measurement campaign validating the traceability of the solar irradiance record and Earth radiation budget data. The campaign also established future traceability, thus ensuring confidence in the continuing climate-data record. The total solar irradiance radiometer facility (TRF) at the Laboratory for Atmospheric and Space Physics (LASP) Boulder, uses a liquid helium cooled cryogenic radiometer as the reference standard for the validation of spaceflight total solar irradiance (TSI) instrumentation. In 2008 the radiometer was directly compared to the National Institute of Standards and Technology (NIST) Primary Optical Watt Radiometer (POWR) at a wavelength of 532.12 nm. At TSI power levels, a correction factor of 1.000 306 with an associated standard uncertainty (u) of 0.000 098, was reported for the TRF radiometer scale when using external voltage measurement electronics, and not correcting for cavity heating non-equivalence or cavity absorptance. The TRF radiometer has recently been revalidated at LASP using a POWR calibrated silicon photodiode trap transfer standard named TT4. We report a correction factor of 0.999 787, u = 0.000 285 to align the TRF radiometer scale with the current NIST POWR scale. A new room temperature reference standard radiometer was established. It measured 133 parts per million (ppm) higher than POWR using the same silicon transfer standard as above, and in a separate direct measurement, 168 ppm lower than the TRF radiometer shuttered at 400 s full shutter cycle. The difference agrees within stated uncertainties. A correction of 0.999 867, u = 0.000 247 will align the new radiometer scale with the NIST radiant power scale of POWR.

Regional seismic networks typically monitor and locate seismic sources using only kinematic (i.e., traveltime) observations. We propose an automated “sliding box” procedure to improve source locations by leveraging dynamic (e.g., full waveform) information via Geometric-mean Reverse-Time Migration (GmRTM). We demonstrate the proposed method’s efficacy by selecting and relocating some of the cataloged tectonic earthquakes recorded by a network of ∼250 three-component seismic sensors deployed across 8,000 km2 of mountainous terrain in Central Asia. Each event is recorded with sufficient signal-to-noise ratio (≥4) by at least 8 sensors inside a 20 km × 20 km box centered on the cataloged location. For each event, we extract a local 3-D velocity model, multiply the waveform data by their corresponding STA/LTA ratios to suppress coda waves and other coherent noise, and apply GmRTM to reconstruct high-resolution source images. The automatic procedure reasonably relocates 280 earthquakes.

We have developed generalized methods for electrical substitution optical measurements, as well as cryogenic detectors which can be used to implement them. The new methods detailed here enable measurement of arbitrary periodic waveforms by an electrical substitution radiometer (ESR), which means that spectral and dynamic optical power can be absolutely calibrated directly by a primary standard detector. Cryogenic ESRs are not often used directly by researchers for optical calibrations due to their slow response times and cumbersome operation. We describe two types of ESRs with fast response times, including newly developed cryogenic bolometers with carbon nanotube absorbers, which are manufacturable by standard microfabrication techniques. These detectors have response times near 10 ms, spectral coverage from the ultraviolet to far-infrared, and are ideal for use with generalized electrical substitution. In our first tests of the generalized electrical substitution method with FTS, we have achieved uncertainty in detector response of 0.13% (k = 1) and total measurement uncertainty of 1.1% (k = 1) in the mid-infrared for spectral detector responsivity calibrations. The generalized method and fast detectors greatly expand the range of optical power calibrations which can be made using a wideband primary standard detector, which can shorten calibration chains and improve uncertainties.

We derive new, 3D, isotropic models of seismic compressional and shear wavespeeds, Vp and Vs, respectively, their ratio, Vp/Vs, and a catalog of relocated earthquakes for Southern California from more than 10 million P‐ and S‐wave arrivals associated with over 0.3 million earthquakes that occurred between 2000 and 2020. We augment high‐quality analyst‐reviewed phase arrival picks from the Southern California Earthquake Data Center with S‐wave arrival picks obtained with an automated algorithm, and we derive new wavespeed models via traveltime tomography formulated using Poisson‐Voronoi cells (Fang et al., 2020, https://doi.org/10.1785/0220190141 ). The results contribute to improved regional wavespeed models, particularly the Vp/Vs model, and absolute event locations. The obtained models correlate well with regional geological features and yield more accurate synthetic waveforms than other regional models do for waves with periods shorter than 5 s in much of the modeled region. The derived event catalog exhibits tighter spatial clustering than the standard regional catalog, thereby helping to characterize subsurface features of major faults. The regional 1D averaged Vp/Vs ratio shows high values at shallow depths, decreases to a minimum at about 10 km, then increases again at greater depths below 15 km. Deep seismicity correlates well with regions of Vp/Vs ratio lower than 1.75, which may indicate an increased brittle‐to‐ductile transition depth with an important influence on crustal mechanics. The new wavespeed models and seismic catalog can be useful for various studies including analyses of seismicity patterns and simulations of crustal deformation and ground motion.

Neural Networks and related Deep Learning methods are currently at the leading edge of technologies used for classifying objects. However, they generally demand large amounts of time and data for model training; and their learned models can sometimes be difficult to interpret. In this paper, we advance FastMapSVM—an interpretable Machine Learning framework for classifying complex objects—as an advantageous alternative to Neural Networks for general classification tasks. FastMapSVM extends the applicability of Support-Vector Machines (SVMs) to domains with complex objects by combining the complementary strengths of FastMap and SVMs. FastMap is an efficient linear-time algorithm that maps complex objects to points in a Euclidean space while preserving pairwise domain-specific distances between them. We demonstrate the efficiency and effectiveness of FastMapSVM in the context of classifying seismograms. We show that its performance, in terms of precision, recall, and accuracy, is comparable to that of other state-of-the-art methods. However, compared to other methods, FastMapSVM uses significantly smaller amounts of time and data for model training. It also provides a perspicuous visualization of the objects and the classification boundaries between them. We expect FastMapSVM to be viable for classification tasks in many other real-world domains.

Emerging applications require a calibration at 1 W with greater accuracy than is currently available. Conventional free beam absolute electrical substitution radiometers (ESRs) operate at cryogenic conditions have historically provided the highest accuracy but operate at optical power levels < 2 mW. To improve the accuracy of calibrations at 1 W, we compare possible approaches to realize a primary standard for 1 W optical power measurements. We describe and evaluate two diverse concepts based on bolometer detectors: The first design is an adapted cryogenic approach while the second system is operating at room temperature (RT). With the proposed uncertainty budgets, we estimate an expanded uncertainty for the RT layout to be < 0.06 % (k = 2) while the cryogenic design approaches 0.02 % (k = 2).

We derive a detailed earthquake catalogue and V-p,V-s and V-p/V-s models for the region around the 2019 M-w 6.4 and M-w 7.1 Ridgecrest, California, earthquake sequence using data recorded by rapid-response, densely deployed sensors following the Ridgecrest main shock and the regional network. The new catalogue spans a 4-month period, starting on 1 June 2019, and it includes nearly 95 000 events detected and located with iterative updates to our velocity models. The final V-p and V-s models correlate well with surface geology in the top 4 km of the crust and spatial seismicity patterns at depth. Joint interpretation of the derived catalogue, velocity models, and surface geology suggests that (i) a compliant low-velocity zone near the Garlock Fault arrested the M-w 7.1 rupture at the southeast end; (ii) a stiff high-velocity zone beneath the Coso Mountains acted as a strong barrier that arrested the rupture at the northwest end and (iii) isolated seismicity on the Garlock Fault accommodated transtensional-stepover strain triggered by the main events. The derived catalogue and velocity models can be useful for multiple future studies, including further analysis of seismicity patterns, derivations of accurate source properties (e.g. focal mechanisms) and simulations of earthquake processes and radiated seismic wavefields.

The design and performance of a room temperature electrical substitution radiometer for use as an absolute standard for measuring continuous-wave laser power over a wide range of wavelengths, beam diameters, and powers are described. The standard achieves an accuracy of 0.46% (k = 2) for powers from 10 mW to 100 mW and 0.83% (k = 2) for powers from 1 mW to 10 mW and can accommodate laser beam diameters (1/e2) up to 11 mm and wavelengths from 300 nm to 2 μm. At low power levels, the uncertainty is dominated by sensitivity to fluctuations in the thermal environment. The core of the instrument is a planar, silicon microfabricated bolometer with vertically aligned carbon nanotube absorbers, commercial surface mount thermistors, and an integrated heater. Where possible, commercial electronics and components were used. The performance was validated by comparing it to a National Institute of Standards and Technology primary standard through a transfer standard silicon trap detector and by comparing it to the legacy "C-series" standards in operation at the U.S. Air Force Metrology and Calibration Division (AFMETCAL).