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At least 1,063 records · Page 59

Radiofrequency synthesiser with an intrinsic instability of 5 × 10{sup −15} at the averaging time of 1 s based on a femtosecond erbium-doped fibre laser

A radio-optical synthesiser intended for operation in a radio-frequency master oscillator with an optical He – Ne/CH{sub 4} frequency standard (λ = 3.39 μm) is developed on the basis of a femtosecond erbium-doped fibre laser. The synthesiser generates equidistant harmonics in the frequency range of 1 – 10 GHz with stability determined by the optical frequency standard. A stable supercontinuum spectrum is formed in the range around 1.06 μm, which provides stable 24-hour operation of the synthesiser and is important for practical applications in off-laboratory conditions. A direct comparison of the output frequencies of two synthesisers shows that the up-grade of the fibre laser and detection system of femtosecond pulses results in the synthesiser intrinsic instability of 5 × 10{sup −15} at the averaging time of 1 s. Such a value is by an order of magnitude less than that obtained in our earlier works. (laser frequency standards)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cross-correlating radial peculiar velocities and CMB lensing convergence

We study, for the first time, the cross correlation between the angular distribution of radial peculiar velocities (PV) and the lensing convergence of cosmic microwave background (CMB) photons. We derive theoretical expectations for the signal and its covariance and assess its detectability with existing and forthcoming surveys. We find that such cross-correlations are expected to improve constraints on different gravitational models by partially breaking degeneracies with the matter density. We identify in the distance-scaling dispersion of the peculiar velocities the most relevant source of noise in the cross correlation. For this reason, we also study how the above picture changes assuming a redshift-independent scatter for the PV, obtained for example using a reconstruction technique. Our results show that the cross correlation might be detected in the near future combining PV measurements from DESI and the convergence map from CMB-S4. Using realistic direct PV measurements we predict a cumulative signal-to-noise ratio of approximately 3.8σ using data on angular scales 3 ≤ ℓ ≤ 200. For an idealized reconstructed peculiar velocity map extending up to redshift z = 0.15 and a smoothing scale of 4 Mpc h -1 we predict a cumulative signal-to-noise ratio of approximately 27σ from angular scales 3 ≤ ℓ ≤ 200. We conclude that currently reconstructed peculiar velocities have more constraining power than directly observed ones, even though they are more cosmological-model dependent.

79 ASTRONOMY AND ASTROPHYSICS↗

Observation of collective modes of excitations in 59 Co, 59 Ni, and 61 Co and the influence of the $g_{9/2}$ orbital

High-spin states in 59 Co (Z = 27), 59 Ni (Z = 28), and 61 Co have been populated by the fusion evaporation reactions, 48 Ti( 14 C, p2n ) 59 Co, 48 Ti( 14 C, 3 n ) 59 Ni, and 50 Ti( 14 C, p2n ) 61 Co. The 9 MV tandem accelerator at the John D. Fox Laboratory, Florida State University (FSU) was used to accelerate the 14 C beam and the deexciting γ rays were detected by the FSU detector array consisting of six high-purity germanium (HPGe) clover detectors and three single crystals. Directional correlation of the $γ$ rays deexciting oriented states (DCO ratios) and polarization asymmetry measurements helped to establish spin and parities of the excited states whenever possible. The level scheme of 59 Co has been expanded with the inclusion of positive-parity states up to 31/2 + at around 11 MeV. The 59 Ni positive-parity states known from previous study were verified with modifications to some of the spins and parities. On the other hand, the negative-parity states were extended to 31/2 at an excitation energy of 12 MeV. No new transition was observed for 61 Co, but one of the major bands has been reassigned as consisting of positive-parity states by reason of this study. Importantly, excitations observed within the f 7/2 , p 3/2 , f 5/2 , and p 1/2 orbitals, and also across the N = 40 subshell closure into the g 9/2 orbital was established by comparison with large-scale shell-model calculations for the three nuclei studied.

59 ≤ A ≤ 89↗

Cybersecurity of Wide Area Monitoring, Protection and Control Systems for HVDC Applications

The flexibility provided by High Voltage Direct Current (HVDC) systems can be further extended by Wide Area Monitoring, Protection, and Control (WAMAPC) systems. WAMPAC systems enable many HVDC applications and, on the other hand, inevitably introduce cybersecurity concerns that need to be addressed. In this work, a security domain layer and decision framework is reported to detect and mitigate the impact of false data injection (FDI) attacks targeting HVDC stations. Specifically, a rule-based cyber-attack detection method is introduced and implemented on Raspberry Pi and tested on the real-time HVDC simulation facility on the real-time digital simulator (RTDS) platform at ABB U.S. Corporate Research Center.

cybersecurity↗

Effect of stress and temperature on zero group velocity Lamb modes

Zero group velocity (ZGV) Lamb wave resonances are highly localized and sensitive to changes in material properties, making them a viable option for probing residual stresses and elastic nonlinearity through acoustoelastic effects. Temperature changes also influence ZGV modes and need to be accounted for, particularly when measuring the small frequency shifts associated with acoustoelastic effects. We use a laser-based ultrasonic system to measure the third-order elastic constants of several materials. A temperature compensation scheme is devised to remove the effects of temperature fluctuations from the measurements. Furthermore, the measured third-order elastic constants are used to predict the temperature dependence of the ZGV resonances using thermo-acoustoelasticity theory, and these predictions are compared to experimental measurements. We find that thermo-acoustoelasticity theory was unable to reliably predict the shift in ZGV resonances with temperature. These results could have important implications in understanding the limitations of thermo-acoustoelasticity theory and in developing precision ZGV resonance-based systems to detect and quantify residual stress in parts, a particularly relevant problem in additive manufacturing techniques including powder bed fusion and directed energy deposition.

Engineering↗

Stabilization of the 81-channel coherent beam combination using machine learning

We develop a rapidly converging algorithm for stabilizing a large channel-count diffractive optical coherent beam combination. An 81-beam combiner is controlled by a novel, machine-learning based, iterative method to correct the optical phases, operating on an experimentally calibrated numerical model. A neural-network is trained to detect phase errors based on interference pattern recognition of uncombined beams adjacent to the combined one. Due to the non-uniqueness of solutions in the full space of possible phases, the network is trained within a limited phase perturbation/error range. This also reduces the number of samples needed for training. Simulations have proven that the network can converge in one step for small phase perturbations. When the trained neural-network is applied to a realistic case of 360 degree full range, an iterative scheme exploits random walking at the beginning, with the accuracy of prediction on phase feedback direction, to allow the neural-network to step into the training range for fast convergence. This neural-network-based iterative method of phase detection works tens of times faster than the commonly used stochastic parallel gradient descent approach (SPGD) using a single-detector and random dither when both are tested with random phase perturbations.

Wang, Dan↗

3D, Real-time Label-free Visualization of Cellular Health

This work directly addresses a key question raised in TA7, Topic L1 of HDTRA1-16-24-FRCWMDCall, “Can quantum level changes be detected, mapped, and understood in the biological environment to allow faster diagnostic responses?” This work will use the inherently sensitive quantum property of a molecular excited state lifetime to visualize and map discrete, subtle nanometer-scale changes (e.g. NADPH vs NADH) that are key indicators of cellular health in response to chemical and biological threats and MCMs. It will also develop and exploit new, fast imaging light-sheet methods to allow faster diagnostic responses. This new imaging system will exploit time-correlated single photon counting and new advances in single-objective light-sheet microscopy (oblique plane microscopy) for fast, quantitative analysis of cellular redox state. We will add an entirely new dimension (excited state fluorescence lifetime) to oblique plane microscopy—a method that even without this added dimension was labeled by Nature Methods in 2021 as a ‘Method to Watch.’ Following instrument development and validation, we will explore cellular response to Burkholderia infections and antibiotic treatment in immortal cell lines followed by expansion to more realistic cellular environments (such as neuro-muscular junctions, NMJs) to test nerve agent simulants and their MCMs. As a microscopy platform, these methods hold the promise of being able to visualize a single infected cell (or a cellular compartment) and MCM treatment well before a larger and later organ/organism response.

47 OTHER INSTRUMENTATION↗

Probing Intra-Halo Light with Galaxy Stacking in CIBER Images

We study the stellar halos of 0.2 ≲ $z$ ≲ 0.5 galaxies with stellar masses spanning $M$* ~ 10 10.5 to 10 12 $M$ ⊙ (approximately $L$* galaxies at this redshift) using imaging data from the Cosmic Infrared Background Experiment (CIBER). A previous CIBER fluctuation analysis suggested that intra-halo light (IHL) contributes a significant portion of the near-infrared extragalactic background light (EBL), the integrated emission from all sources throughout cosmic history. In this work, we carry out a stacking analysis with a sample of ~30,000 Sloan Digital Sky Survey (SDSS) photometric galaxies from CIBER images in two near-infrared bands (1.1 and 1.8 $μ$m) to directly probe the IHL associated with these galaxies. We stack galaxies in five sub-samples split by brightness and detect an extended galaxy profile beyond the instrument point-spread function (PSF) derived by stacking stars. We jointly fit a model for the inherent galaxy light profile plus large-scale one- and two-halo clustering to measure the extended galaxy IHL. We detect nonlinear one-halo clustering in the 1.8 $μ$m band at a level consistent with numerical simulations. Furthermore, by extrapolating the fraction of extended galaxy light, we measure to all galaxy mass scales, we find ~30%/15% of the total galaxy light budget from galaxies is at radius $r$ > 10/20 kpc, respectively. These results are new at near-infrared wavelengths at the $L$* mass scale and suggest that the IHL emission and one-halo clustering could have appreciable contributions to the amplitude of large-scale EBL background fluctuations.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantitative stable isotope probing (qSIP) and cross-domain networks reveal bacterial-fungal interactions in the hyphosphere

Interactions between fungi and bacteria have the potential to substantially influence soil carbon dynamics in soil, but we have yet to fully identify these interactions and partners in their natural environment. In this study, we stacked two powerful methods, 13 C quantitative stable isotope probing (qSIP) and cross-domain co-occurrence network, to identify interacting fungi and bacteria in a California grassland soil. We used in-field whole plant 13 CO 2 labeling along with sand-filled ingrowth bags (that trap fungi and hyphae-associated bacteria) to amplify the signal of fungal-bacterial interactions, separate from the bulk soil background. We found a total of 54 bacterial ASVs and 9 fungal OTUs that were significantly 13 C-enriched. These were saprotrophic and biotrophic fungi, and motile, sometimes predatory bacteria. Among these, 70% of all 13 C-enriched bacteria identified were motile. Notably, we detected fungal-bacterial network links between a fungal OTU of the genus Alternaria and several bacterial ASVs of the genera Bacteriovorax, Mucilaginibacter, and Flavobacterium, providing empirical evidence of their direct interactions through C exchange. We observed a strong positive co-occurrence pattern between predatory bacteria of the phylum Bdellovibrionota and fungal OTUs, suggesting the transfer of C across the soil food web. To date, our ability to associate microbial co-occurrence network patterns with biological interactions is limited, but the incorporation of qSIP allowed us to more precisely detect interacting partners by narrowing in on the taxa that were actively incorporating plant-fixed, fungal-transported labeled substrates. Together, these approaches can help build a mechanistic understanding of the complex nature of fungal-bacterial interactions in soil.

59 BASIC BIOLOGICAL SCIENCES↗

The Variable Continuous Bimaterial Interface in the San Jacinto Fault Zone Revealed by Dense Seismic Array Analysis of Fault Zone Head Waves

Key factors controlling earthquake ruptures include fault geometry, continuity, and seismic velocity structure around the fault. We present a novel tool that better informs deep bimaterial fault geometry embedded in distributed damage and seismicity, associated velocity contrasts across the fault, and their correlations with surface complexities. The method employs fault zone head and direct body waves and is applied to recordings from five spatiotemporally different seismic arrays along the complex San Jacinto fault zone (SJFZ) in southern California. We detect and distinguish these signals based on instantaneous phase coherence and relative energy in a cascading manner from one scale array to another. The analysis reveals a >70-km long continuous bimaterial interface within the SJFZ with several deep northeast dipping fault segments. The northern SJFZ, for instance, locates ~7 km northeast of its surface expression at 18-km depth. P-wave velocity contrasts range from near 0% to >15%, consistent with other bimaterial faults, and differ by a few % depending on fault-array azimuth, implying directional-dependent velocity contrasts. S-wave head waves and velocity contrasts are also imaged for the first time at the southern SJFZ, averaging to 2.9% in agreement with tomography results. The imaged geometry and continuity suggest the SJFZ initiated along remnant tectonic structures and translates to a rupture potential of M > 7.2, i.e., the sizes of its largest paleo-earthquakes. The P and S contrasts, and their ratios, have important implications for earthquake rupture speed, mode, directivity, and frictional heating along the SJFZ and other major faults globally.

58 GEOSCIENCES↗

Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

Anomaly detection is a widely studied task for a broad variety of data types; among them, multiple time series appear frequently in applications, including for example, power grids and traffic networks. Detecting anomalies for multiple time series, however, is a challenging subject, owing to the intricate interdependencies among the constituent series. We hypothesize that anomalies occur in low density regions of a distribution and explore the use of normalizing flows for unsupervised anomaly detection, because of their superior quality in density estimation. Moreover, we propose a novel flow model by imposing a Bayesian network among constituent series. A Bayesian network is a directed acyclic graph (DAG) that models causal relationships; it factorizes the joint probability of the series into the product of easy-to-evaluate conditional probabilities. We call such a graph-augmented normalizing flow approach GANF and propose joint estimation of the DAG with flow parameters. We conduct extensive experiments on real-world datasets and demonstrate the effectiveness of GANF for density estimation, anomaly detection, and identification of time series distribution drift.

Dai, Enyan↗

All-aerosol-jet-printed highly sensitive and selective polyaniline-based ammonia sensors: a route toward low-cost, low-power gas detection

In this work, we report the design and scalable fabrication of a low-cost and low-power polyaniline-based (PANI) ammonia (NH3) gas sensor on polyimide (PI) substrates using additive manufacturing techniques. The silver interdigitated electrode (IDE) arrays and conducting polymer films are printed onto PI using a direct-write technology of aerosol-jet printing. Morphological characteristics are examined by scanning electron microscopy and energy-dispersive X-ray analysis which reveal homogeneously printed PANI film on the IDE platform. The gas sensing performance is evaluated in the analytical early leak detection range of 5–1000 ppm NH3 in air as a function of both thermal (23 °C, 50 °C, 80 °C) and relative humidity (RH = 0%, 30%, 50%) exposures. The sensor exhibits sensitivity down to 5 ppm NH3 with a sub-ppm detection limit and good repeatability. We observe rapid NH3 detection at 0% RH with very extended times for equilibration and recovery. However, at both 30 and 50% RH, the room temperature response and recovery times are reduced to only about 1 min and 5 min, respectively. Experiments also reveal good sensitivity toward the analyte even at higher operating temperatures. Present results merit the practical application of aerosol-jet-printed, low-power sensors for industrial applications where low-level hazardous gas detection is essential.

36 MATERIALS SCIENCE↗

Signal Decomposition for Intrusion Detection in Reliability Assessment in Cyber Resilience (Summary Report)

The complexity of assuring cyber resilience for physical process interactions in connected systems such as energy grids increases dramatically as the coupling between processes becomes more direct and responsive. An example of this growing complexity is provided by Integrated Energy Systems (IES), in which various processes such as nuclear heat generation and commodity production are being directly coupled for increased responsiveness to highly variable signals such as market pricing or electricity demand. As such, the potential attack surface of the coupled processes is larger than the two processes independently. Securing these complex systems requires two-fold monitoring: cybersecure monitoring for potential malicious incursion, and physics monitoring for system tampering. Physics monitoring includes analyzing the behavior of the signals within the system for anomalous behavior. This analysis has been shown to be insufficient if approached by only data-driven machine learning and artificial intelligence (MLAI) techniques or only low-level model comparison. Previous efforts at Purdue University suggested combining high-fidelity models with MLAI algorithms as a basis for a software tool for detecting anomalies in physical processes. This work built on that suggestion, developing an advanced library for signal decomposition and analysis using both MLAI and high-fidelity physics algorithms for greatly improved anomaly detection, especially false data injection. This software can be used as part of a secure imbedded intelligence (SEI) system designed under Consequence-driven Cyber-informed Engineering (CCE) for complex coupled systems. This library established a foundation for online and posteriori analysis of digital signals for the purpose of detecting potential malicious tampering in digital signals representing physical processes. Demonstrations carried out throughout the development highlight the effective use of characterization algorithms to detect signal perturbations, particularly triangle attack-style perturbations, in three wide-ranging applications: seismic monitoring, nuclear thermal hydraulics system simulation, and custom manufacturing.

97 MATHEMATICS AND COMPUTING↗

Evaluation of a frequency-dependent phase shift in chirped Raman lasers for atom gravimeters

Light-pulse atom gravimetry has emerged as a powerful technique for precisely measuring absolute gravitational acceleration. Raman lasers are commonly used in this technique to coherently manipulate the atomic wave packet, of which the effective frequency is chirped continuously to compensate for the Doppler shift. In this study we investigate an additional phase shift in the Raman lasers that arises due to the frequency chirp. Here, we directly measure this phase shift by recording the beat signal of the Raman lasers with a high-speed oscilloscope, providing an independent evaluation of the resultant error in atom gravimeters caused by this phase shift. Concurrently, we detect the influence of the additional phase shift on gravity measurements using our atom gravimeter, and the results are in good agreement with the independent evaluation. Notably, there may still be a residual error at the microgal level when performing differential measurements by reversing the direction of the effective wave vector of the Raman lasers. We propose that this residual error can in principle be eliminated by selecting the same chirp frequency range for both directions in the differential measurement.

Xu, Yaoyao [Huazhong Univ. of Science and Technolo↗

Examining Nuisance Aerosol Detections in Light of the Origin of the Screening Process (November 2021)

The evolution of philosophy and computations in the International Data Center (IDC) related to aerosol samples have had profound impacts on the number of recorded detections in the network since routine operations began in 2000. Key decisions from policymakers have been the list of triggering radionuclides, the scheme for categorizing these into interest levels 1-5, and an algorithm for determining when an anthropogenic isotope is seen so often that it is no longer interesting, known as the Exponential Weighted Moving Average (EWMA). These are described in the Operations Manual of the IDC. Key parameters that are controlled by the IDC but for which the IDC receives occasional input from policymakers include the constants in EWMA and the peak significance threshold for individual gamma rays, the latter of which directly leads to determination of the presence or absence of a radionuclide in a sample. There are also changes in computations which the IDC makes and informs policy makers about, such as changes in how background is computed, which could also affect the ease of detecting a peak – real or false. Rather than focus on the quantitative changes due to computation changes, this work records some thinking on how isotopes and peak significance levels were chosen, and the resulting detections seen over 18 years during the buildup of the International Monitoring System (IMS). These detections are considered on a global scale to try to determine the relative impact on monitoring, and in some cases, the nature of their existence. Repeated detections of 131I and 133I are the most troublesome, but they are not so frequent to be a major problem for the Verification Regime. These detections could probably be handled adequately using scientific methods currently under development for xenon backgrounds. It is also somewhat problematic that top-level analysis of aerosol backgrounds has not been reported previous to this. The steep increase in the rate of detections after 2016 are a concern, either in the actual backgrounds or from changes in the calculations methods used to generate the Reviewed Radionuclide Report (RRR.) Final conclusions of the authors are that the computational stability of the RRR is very important. With computational stability, changes can be usefully analyzed as being due to changes in radioactivity in Earth’s atmosphere This report is a distillation into text of a talk given in the Radionuclide Experts Group (RNEG) in Vienna during Working Group B (WGB) in February of 2019. This report does not directly contain any IDC data, only summaries by year, or by isotope, or by location. No specific IDC detection by time, location, or isotope is included.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Single-Molecule Chemical Reactions Unveiled in Molecular Junctions

Understanding chemical processes at the single-molecule scale represents the ultimate limit of analytical chemistry. Single-molecule detection techniques allow one to reveal the detailed dynamics and kinetics of a chemical reaction with unprecedented accuracy. It has also enabled the discoveries of new reaction pathways or intermediates/transition states that are inaccessible in conventional ensemble experiments, which is critical to elucidating their intrinsic mechanisms. Thanks to the rapid development of single-molecule junction (SMJ) techniques, detecting chemical reactions via monitoring the electrical current through single molecules has received an increasing amount of attention and has witnessed tremendous advances in recent years. Research efforts in this direction have opened a new route for probing chemical and physical processes with single-molecule precision. This review presents detailed advancements in probing single-molecule chemical reactions using SMJ techniques. We specifically highlight recent progress in investigating electric-field-driven reactions, reaction dynamics and kinetics, host–guest interactions, and redox reactions of different molecular systems. Finally, we discuss the potential of single-molecule detection using SMJs across various future applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning

Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barcoding strategy with nanopore sequencing to rapidly generate sequence-function data for entire protein-coding genes. LevSeq integrates into existing protein engineering workflows and comes with open-source software for data analysis and visualization. The pipeline facilitates data-driven protein engineering by consolidating sequence-function data to inform directed evolution and provide the requisite data for machine learning-guided protein engineering (MLPE). LevSeq enables quality control of mutagenesis libraries prior to screening, which reduces time and resource costs. Simulation studies demonstrate LevSeq’s ability to accurately detect variants under various experimental conditions. Lastly, we show LevSeq’s utility in engineering protoglobins for new-to-nature chemistry. Widespread adoption of LevSeq and sharing of the data will enhance our understanding of protein sequence-function landscapes and empower data-driven directed evolution.

59 BASIC BIOLOGICAL SCIENCES↗

Results from an Aeromagnetic Survey to Detect Steel-Cased Wells at a Marcellus Shale Well Site in Washington County, Pennsylvania

Pennsylvania has a 150-year history of oil and gas production—the longest of any state—and this enduring activity has resulted in the drilling of more than 300,000 recorded wells. However, unknown wells likely exist because innumerable wells were drilled during Pennsylvania’s intense early oil and gas history when incomplete records were kept of well locations. There is concern that early wells are likely to be ineffectively sealed because there were no laws that required plugging when the wells were abandoned. Today, many undocumented and unplugged wells are thought to be in areas of emerging shale gas and shale oil development where open wellbores can provide a pathway for undesired upward migration of fluids and gas from hydraulically fractured reservoirs. Due to this concern, Pennsylvania regulators have asked operators to locate orphaned and abandoned wells within a 1,000-ft buffer of proposed new wells. The objective of this report is to demonstrate that high-resolution aeromagnetic surveys, historic air photos, and Light Detection and Ranging (LiDAR) imagery can be rapid and effective methods to reconnoiter large, forested areas of moderate terrain for the presence of abandoned wells. These well-finding methods were evaluated at a proposed Marcellus Shale gas drilling site in Washington County, Pennsylvania, where the methods collectively located 18 confirmed wells: 15 wells were identified from aeromagnetic surveys, two wells were identified from inspection of historical air photos, and one well was identified by evaluation of state-wide LiDAR imagery. Only six wells were previously known, and their locations, as recorded in Pennsylvania’s statewide oil and gas wells database (PA/IRIS/WIS), were often too inaccurate for the wells to be found in the dense underbrush. Twelve wells identified in this study were abandoned, unmarked, and undocumented. Aeromagnetic surveys locate wells by detecting the unique magnetic signature of vertical, steel well casing, which is depicted on magnetic maps as a “bull’s eye” type anomaly that is centered directly over the well. However, when wells were drilled and found to be sub-economic, their casing was sometimes pulled and salvaged for reuse. Such wellbores provide no magnetic response and go undetected if all casing was removed. Oftentimes attempts to retrieve well casing were not 100% successful. For example, historical records for one well in the study area indicate that the well was completed in 1902 as a dry hole and that, to the extent possible, the casing was pulled for reuse. However, a section of 10-in. diameter steel casing was not recovered and remains at an unknown depth in the wellbore. This well was easily detected by the aeromagnetic survey although only deep casing remained in the well. To mitigate for the likelihood that wellbores exist where most or all casing has been removed, this study augmented aeromagnetic data with historic air photos and digital terrain models generated from LiDAR datasets—both databases are publicly available at no cost for areas within Pennsylvania. These complementary methods located three wells where the aeromagnetic anomaly, although present, was subtle and overlooked. Together, these methods determined accurate locations for six known wells within the study area and located 12 previously unknown wells. Although it is not certain that these methods successfully located all wells in the study area, the application of these methods does represent a significant improvement over relying on existing databases for well locations. For the Appendix to the report, see: https://www.netl.doe.gov/energy-analysis/details?id=b46c417a-7c9e-4d25-b810-e6248b0217f4</p>

04 OIL SHALES AND TAR SANDS↗