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DOE OSTI2025

Entropy of the Quantum–Classical Interface: A Potential Metric for Security

Hybrid quantum–classical systems are emerging as key platforms in quantum computing, sensing, and communication technologies, but the quantum–classical interface (QCI)—the boundary enabling these systems—introduces unique and largely unexplored security vulnerabilities. This position paper proposes using entropy-based metrics to monitor and enhance security, specifically at the QCI. We present a theoretical security outline that leverages well-established information-theoretic entropy measures, such as Shannon entropy, von Neumann entropy, and quantum relative entropy, to detect anomalous behaviors and potential breaches at the QCI. By linking entropy fluctuations to scenarios of practical relevance—including quantum key distribution, quantum sensing, and hybrid control systems—we promote the potential value and applicability of entropy-based security monitoring. While explicitly acknowledging practical limitations and theoretical assumptions, we argue that entropy-based metrics provide a complementary approach to existing security methods, inviting further empirical studies and theoretical refinements that can strengthen future quantum technologies.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2001

Application of a Fiber Optic Distributed Strain Sensor System to Woven E-Glass Composite

A distributed strain sensing system utilizing a series of identically written Bragg gratings along an optical fiber is examined for potential application to Composite Armored Vehicle health monitoring. A vacuum assisted resin transfer molding process was used to fabricate a woven fabric E-glass/composite panel with an embedded fiber optic strain sensor. Test samples machined from the panel were mechanically tested in 4-point bending. Experimental results are presented that show the mechanical strain from foil strain gages comparing well to optical strain from the embedded sensors. Also, it was found that the distributed strain along the sample length was consistent with the loading configuration.

Anastasi, Robert F.↗

DOE OSTI2026

Computing an Optimal Entanglement Path with Throughput and Fidelity Considerations

Entanglement distribution is a core function of quantum networks essential for operations including teleportation, distributed quantum sensing, and multisite computation. Entanglement throughput and fidelity are two critical performance measures that depend on the quantum transmission along the links and swapping operations at the repeaters along the path. We study the problem of computing a end-to-end entanglement path that satisfies both fidelity and throughput requirements, leveraging qubit buffers at the nodes and considering the sequential swapping order. We show that the general problem of simultaneously satisfying both metrics to be NP-hard, and develop an algorithm to maximize throughput subject to a given fidelity threshold. We introduce the concepts of entanglement probability distribution and path domination and exploit them in the design of our algorithm. Extensive numerical results show that our algorithm can find optimal solutions in networks with thousands of nodes in less than a second. We also describe practical and possible implementation aspects of this algorithm in terms of devices and architecture support.

Xue, Guoliang [Arizona State University]↗

DOE OSTI2023

Cascaded Sapphire Fiber Bragg Gratings Inscribed by Femtosecond Laser for Molten Steel Studies

This research reports a distributed fiber optic high-temperature sensing system tailored for applications in the steel industry and various other sectors. Recent advancements in optical sensor technology have led to the exploration of sapphire crystal fibers as a solution for sensing in harsh environments. Utilizing a femtosecond (fs) laser, cascaded fiber Bragg gratings (FBGs) were meticulously fabricated within a multimode sapphire optical fiber. These FBGs endowed the system with distributed sensing capabilities and underwent rigorous testing under extreme temperatures, reaching up to 1800 °C. Here, the study delves into the investigation of the FBG reflection spectrum, facilitated by the development of a sophisticated multimode demodulation system, which contributed to the attainment of precise temperature measurements with a performance accuracy of 99.9%. Demonstrating exceptional thermal stability, the sapphire FBGs endured temperatures of 1600 °C for a sustained duration of 22 h. Furthermore, this article explores the application of distributed temperature sensing employing multiple sapphire FBGs, showcasing their utility in temperature measurements related to molten steel studies.

47 OTHER INSTRUMENTATION↗

NASA NTRS2007

A Contrast in Use of Metrics in Earth Science Data Systems

In recent years there has been a surge in the number of systems for processing, archiving and distributing remotely sensed data. Such systems, working independently as well as in collaboration, have been contributing greatly to the advances in the scientific understanding of the Earth system, as well as utilization of the data for nationally and internationally important applications. Among such systems, we consider those that are developed by or under the sponsorship of NASA to fulfill one of its strategic objectives: "Study Earth from space to advance scientific understanding and meet societal needs." NASA's Earth science data systems are of varying size and complexity depending on the requirements they are intended to meet. Some data systems are regarded as NASA's "Core Capabilities" that provide the basic infrastructure for processing, archiving and distributing a set of data products to a large and diverse user community in a robust and reliable manner. Other data systems constitute "Community Capabilities". These provide specialized and innovative services to data users and/or research products offering new scientific insight. Such data systems are generally supported by NASA through peer reviewed competition. Examples of Core Capabilities are 1. Earth Observing Data and Information System (EOSDIS) with its Distributed Active Archive Centers (DAACs), Science Investigator-led Processing Systems (SIPSs), and the EOS Clearing House (ECHO); 2. Tropical Rainfall Measurement Mission (TRMM) Science Data and Information System (TSDIS); 3. Ocean Data Processing System (ODPS); and 4. CloudSat Data Processing Center. Examples of Community Capabilities are projects under the Research, Education and Applications Solutions Network (REASON), and Advancing Collaborative Connections for Earth System Science (ACCESS) Programs. In managing these data system capabilities, it is necessary to have well-established goals and to measure progress relative to them. Progress is measured through "metrics", which can be a combination of quantitative as well as qualitative assessments. The specific metrics of interest depend on the user of the metrics as well as the type of data system. The users of metrics can be data system managers, program managers, funding agency or the public. Data system managers need metrics for assessing and improving the performance of the system and for future planning. Program managers need metrics to assess progress and the value of the data systems sponsored by them. Also, there is a difference in the metrics needed for core capabilities that tend to be more complex, larger and longer-term compared to community capabilities and the community capabilities that tend to be simpler, smaller and shorter-term. Even among community capabilities there are differences; hence the same set of metrics does not apply to all. Some provide data products to users, some provide services that enable better utilization of data or interoperability among other systems, and some are a part of a larger project where provision of data or services is only a minor activity. There is also a contrast between metrics used for internal and external purposes. Examples of internal purposes are: ensuring that the system meets its requirements, and planning for evolution and growth. Examples of external purposes are: providing to sponsors indicators of success of the systems, demonstrating the contributions of the system to overall program success, etc. This paper will consider EOSDIS, REASON and ACCESS programs to show the various types of metrics needed and how they need to be tailored to the types of data systems while maintaining the overall management goals of measuring progress and contributions made by the data systems.

Ramapriyan, Hampapuram↗

DOE OSTI2021

An Integrated View of Hydraulic Induced Fracture Geometry in Hydraulic Fracture Test Site 2

Until relatively recently, most of our understanding about the geometry of hydraulically induced fractures in unconventional reservoirs has been inferred by patterns observed via microseismic monitoring. Important information, such as fracture-azimuth, fracture-length, height-growth and other geometric data has been determined from microseismic “event clouds”, which in turn has been used to interpret a stimulated reservoir volume (SRV). It is important to note that relatively limited microseismic results have been acquired in conjunction with other diagnostics and validated in a consistent manner. The Hydraulic Fracture Test Site 2 (HFTS2) in the Permian Delaware Basin provides a unique opportunity to compare the frac geometry interpretations derived from multiple frac diagnostic tools and at multiple scales. The integrated view that emerges from all the frac diagnostic tools is that in HFTS2 the geometries of hydraulically induced fractures are not random and with a highly complex branching architecture. In fact, the fracs are mostly vertical, parallel plana domains, and both vertically and horizontally asymmetrical. The hydraulically induced fractures have a very consistent azimuth with a strike that matches SHmax. At the distance corresponding to the spacing between nearby wells in HFTS2, ~ 660 ft, the pattern of strain interceptions observed from Low Frequency Distributed Acoustic Sensing (LF-DAS) shows far-field dimensions that are consistent with the stage length dimensions at the stimulated well. In general, larger stages with higher number of clusters create larger number of interceptions and wider stimulated intervals than that of shorter stages with the same cluster to cluster spacing and fewer clusters. The hydraulically induced fractures also show a clear tendency to preferentially grow upwards as shown by the microseismic data, by the relative lower number of LF-DAS interceptions in nearby deeper wells and finally by the observed LF-DAS strain patterns in the vertical observation well. In the near field, the geometries of the fracture domains are also consistent. As shown by the distributed strain measurements obtained during production via the monitoring of Rayleigh Frequency Shift (RFS), each cluster has a separate, non-overlapping, frac-zone-domain that are generally centered around the locations of each perforation cluster. Overall, the hydraulically induced fractures in HFTS2 are interpreted as occurring in swarms associated with individual clusters, each with its own unique geometry but with similar predictable geometric and propagation tendencies. The comprehensive frac diagnostic program in HFTS2, the well-pad layout that permits the investigation of the Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S018R003/2477511/urtec-2021-5396-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5396 2 impact that nearby producing wells has on frac geometry, together with an innovative Design of Experiment (DofE) that includes sequential-fracing, consistent cluster-to-cluster distances and few single-perforation cluster stages, has allowed us to gain a unique perspective about the geometry of the induced hydraulic fractures on this pad. Finally, the HFTS2 dataset has also provided us with a better understanding of the applicability and limitations of the different diagnostic tools.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Simulated Vision-based Approach and Landing System for Advanced Air Mobility

Advanced Air Mobility (AAM) aircraft require precision approach and landing systems (PALS) in several environments, such as urban, suburban, and rural. It is challenging to implement current state-of-the-art methods approved for automated approach and landing for AAM operations with challenges such as GPS degradation in urban environments and visual navigation aids like the glideslope and localizer being narrow and not allowing alternative incoming landing angles at vertiports. However, existing technology and systems, i.e., the instrument landing system (ILS) with glideslope and localizer indicators that use vision, IR, radar, or GPS methods, provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL and computer vision feature correspondence methods to demonstrate a baseline navigation system while adhering to the Federal Aviation Administration requirements and regulations about heliport design (FAA AC 150/5390-2C), which is one of the closest references for vertiport requirements and regulations. The coplanar pose from orthography and scaling with iterations (COPOSIT) algorithm determines pose estimation, which feeds into an Extended Kalman filter that combines IMU with vision to create a vision-based approach and landing (VAL) sensor fusion navigation solution for GPS-denied environments. The VAL navigation solution provides promising simulation results for AAM PALS with Hough circle detection and feature correspondence, which demonstrate robustness to false positives. This paper incorporates moderately high- fidelity simulations with computer graphics rendering to show a distributed sensor network to track an AAM aircraft during approach and landing to compare with the aircraft’s onboard vision-based navigation solution.

distributed sensing↗

DOE OSTI2021

Distributed Thermal Response Multi-Source Modeling to Evaluate Heterogeneous Subsurface Properties

A thorough assessment of thermal properties in heterogeneous subsurface is necessary in design of low-temperature borehole heat exchangers (BHEs). For this study, a distributed thermal response test (DTRT), which combines distributed temperature sensing (DTS) with a conventional thermal response test (TRT), was conducted in a U-bend geothermal loop installed in an open borehole at the University of Illinois at Urbana-Champaign to estimate thermal properties by analyzing the thermal response of different geologic materials while applying a constant heat input rate. Fiber-optic cables in the DTRT were deployed both inside the U-bend geothermal loop and in the center of the borehole to improve the accuracy of calculated heat-loss rates and borehole temperature profile measurements. To assess the subsurface thermal conductivity during the heating phase of the DTRT, a single-source model and a multi-source model, both based on the infinite line source method, were developed using the borehole temperature data and temperatures inside and along the outside of the loop, separately. The two models returned similar thermal conductivity values. The multi-source modeling has the advantage of predicting the thermal conductivity of heterogeneous geologic materials from borehole temperature profiles during the DTRT heating phase. Additionally, based on the distributed thermal conductivity measured in the borehole, estimates were made for both radial thermal impacts and the rate of heat loss in the BHE.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Assessing Carbon Properties in Coastal Waters with a New Observing System Testbed

Large rainfall events over land can lead to a substantial flux of carbon and nutrients to estuaries and the coastal ocean. In the mid-Atlantic on the east coast of North America (35° - 42° N), these events often happen due to tropical storm activity as well as less predictable anomalously large midlatitude storms or abrupt spring snow melt runoff. Storms can directly impact the coastal carbon cycle via export of carbon from land to sea, while also stimulating phytoplankton production due to the influx of nutrients to the coastal ocean. To assess the impact of high precipitation and river flow events on the coastal carbon cycle, we have integrated multiple observing platforms in an analytical framework to dynamically observe carbon-related properties. The new observing system testbed (NOS-T) allows for an estimate of phytoplankton and organic carbon stocks in the surface ocean, with a goal of providing near real time analytical capability. A case study of high river discharge in the mid-Atlantic in the summer and fall of 2018 and 2021 were used to examine how riverine carbon manifests along the land-estuary-ocean continuum particularly in Chesapeake Bay. Chesapeake Bay was chosen as the study site because of long term monitoring by the Chesapeake Bay Program and a robust and well-developed regional biogeochemical modeling system, the Chesapeake Bay Environmental Forecast System (CBEFS), that is publicly available. There is also new capability in Chesapeake Bay to combine hyperspectral radiometric data from the Aerosol Robotic Network site that is online in 2022 with in-water observations of optical properties. Precipitation data from the Global Precipitation Measurement IMERG data set was used to establish triggering criteria for storm carbon flux observation. USGS and in-water carbon data were used to establish statistical models to estimate the mass flux of organic carbon into Chesapeake Bay using measured river discharge. The year 2018 was examined as there was record rainfall and near record river flow in the late summer. The CBEFS modeling was compared with in-water estimates of dissolved organic carbon (DOC) to assess the model’s ability to capture storm fluxes of carbon to the ecosystem. Multiple satellite platforms were also used to assess how remote sensing using passive Earth orbiting sensors can be used to observe carbon in this complex coastal region. A set of recommendations have been established to improve sensing capability to measure aquatic carbon during storm events. A unique challenge in these dynamic inland waters is how rapidly carbon fluxes can evolve in space and time, with many sources contributing to the water leaving reflectance that satellites can observe. To improve our ability to quantify carbon stocks and fluxes in near real time, a suite of satellite sensors and high-resolution modeling capability is needed, all supplemented by in situ monitoring. Future inclusion of in-water observations that would be deployed when the system reaches triggering criteria, as well as taskable orbital instruments, will improve estimates of ocean carbon properties and provide the ability to calculate major carbon stocks and fluxes in near real time following episodic storm events.

land-ocean continuum↗

DOE OSTI2022

Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

02 PETROLEUM↗

NASA NTRS2026

Multi-Agent Swarm State of the Art Report

The Next-Generation Multi-Agent Swarm (NGS) Study conducted by NASA’s Ames Research Center for NASA’s Space Technology Mission Directorate (STMD) will develop a comprehensive understanding of emerging multi-agent swarm capabilities. The study aims to identify existing swarm capabilities and asses their potential for persistent lunar space situational awareness, surface monitoring, and distributed autonomy demonstrations. A key objective is to inform the design of a next-generation multi-agent swarm that can perform autonomous distributed remote sensing, position, navigation, and timing (PNT) services, automated deployment that leverages autonomy, edge computing, and interoperable networking to enable cooperative operations without the need for immediate human operation. This study will address specific shortfalls identified by STMD, including intelligent multi-agent constellations, autonomy, edge computation, position, navigation, and timing for small spacecraft, small spacecraft propulsion, and space situational awareness (1625, 1438, 1433, 1557, 1431, 1430, 1589). The NASA Ames Mission Design Center (MDC) will provide subject matter expertise to support systems engineering trades, while experts in autonomy and spacecraft swarms in NASA’s Intelligent Systems Division will lead the study and focus on identifying emerging next-generation swarm capabilities. The study objectives include: capturing the current state-of-the-art for multi-agent swarm capabilities, evaluating technologies and creating technology roadmaps, and developing at least one new technology demonstration mission concept. This initial NGS study report surveys the current state of the art in technology areas relevant for the next-generation multi-agent swarm design. Our primary focus is on surveying relevant deployed space systems1, supplemented with selective analysis of relevant proposed missions and technology developments that have yet to fly.

agent↗

DOE OSTI2022

Probing eddy size and its effective mixing length in stably stratified roughness sublayer flows

Stably stratified roughness sublayer flows are ubiquitous yet remain difficult to represent in models and to interpret using field experiments. Here, continuous high-frequency potential temperature profiles from the forest floor up to 6.5 times the canopy height observed with distributed temperature sensing (DTS) are used to link eddy topology to roughness sublayer stability correction functions and coupling between air layers within and above the canopy. The experiments are conducted at two forest stands classified as hydrodynamically sparse and dense. Near-continuous profiles of eddy sizes (length scales) and effective mixing lengths for heat are derived from the observed profiles using a novel conditional sampling approach. The approach utilizes potential temperature isoline fluctuations from a statically stable background state. The transport of potential temperature by an observed eddy is assumed to be conserved (adiabatic movement) and we assume that irreversible heat exchange between the eddy and the surrounding background occurs along the (vertical) periphery of the eddy. This assumption is analogous to Prandtl's mixing-length concept, where momentum is transported rapidly vertically and then equilibrated with the local mean velocity gradient. A distinct dependence of the derived length scales on background stratification, height above ground, and canopy characteristics emerges from the observed profiles. Implications of these findings for (1) the failure of Monin–Obukhov similarity in the roughness sublayer and (2) above-canopy flow coupling to the forest floor are examined. The findings have practical applications in terms of analysing similar DTS data sets with the proposed approach, modelling roughness sublayer flows, and interpreting nocturnal eddy covariance measurements above tall forested canopies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Seismic monitoring of CO 2 geosequestration using multi-well 4D DAS VSP: Stage 3 of the CO2CRC Otway project

An important part of any CO 2 geosequestration project is to ensure CO 2 containment and conformance in the subsurface. This is generally done by implementing a comprehensive, risk-based Measurement, Monitoring and Verification plan, a key element of which is active time-lapse seismic monitoring. However, high cost and environmental impact of the standard surface seismic monitoring dictate the need for a cost-effective and environmentally friendly alternative. An opportunity to develop such method emerges with advances in distributed acoustic sensing (DAS) technology, which turns an optical fibre into a seismic sensor with dense spatial sampling. DAS can be permanently deployed in multiple wells across the geosequestration site providing a robust and non-intrusive network of seismic receivers. This approach was developed and tested in the CO2CRC Otway project, where injection of 15 kt of CO 2 at 1.5 km depth was monitored with a 4D vertical seismic profiling (VSP) using five borehole DAS arrays and mobile vibroseis sources. The 4D DAS VSP in each of the five wells provides broadly consistent images of the CO 2 plume with some differences due to different illumination of the target horizon, lateral variation of velocities, and seismic anisotropy. When the newly injected CO 2 reaches a CO 2 plume created as a result of an earlier injection into the same formation ~600 m updip, 4D DAS VSP shows a change in reflectivity in that area and beyond. Furthermore, this shows a potential of 4D DAS VSP for monitoring gas injection into gas-saturated reservoirs.

58 GEOSCIENCES↗

DOE OSTI2020

Urban Seismic Site Characterization by Fiber-Optic Seismology

ccurate ground motion prediction requires detailed site effect assessment, but in urban areas where such assessments are most important, geotechnical surveys are difficult to perform, limiting their availability. Distributed acoustic sensing (DAS) offers an appealing alternative by repurposing existing fiber-optic cables, normally employed for telecommunication, as an array of seismic sensors. We present a proof-of-concept demonstration by using DAS to produce high-resolution maps of the shallow subsurface with the Stanford DAS array, California. We describe new methods and their assumptions to assess H/V spectral ratio—a technique widely used to estimate the natural frequency of the soil—and to extract Rayleigh wave dispersion curves from ambient seismic field. These measurements are jointly inverted to provide models of shallow seismic velocities and sediment thicknesses above bedrock in central campus. The good agreement with an independent survey validates the methodology and demonstrates the power of DAS for microzonation.

Geochemistry & Geophysics↗

DOE OSTI2020

High-Resolution Measurement of Soil Thermal Properties and Moisture Content Using a Novel Heated Fiber Optics Approach

Hydrological parameters are scale dependent. Efficient monitoring techniques capable of measuring hydrological parameters, such as soil moisture content (θ), over a wide range of spatial scales are essential for understanding the complexity of water and energy movement across the landscape. Techniques to measure θ over spatial scales in the range from centimeters to thousands of meters, however, are sorely lacking. Recent improvements in the distributed temperature sensing (DTS) technology supported the development of novel techniques to fill that gap. However, improvements in the accuracy and applicability of DTS techniques are still needed. This study investigates the possibility of improving the accuracy of the fiber optics dual-probe heat-pulse (FO-DPHP) DTS technique by using a new design to maintain the spacing between the FO-DPHP probes and by introducing a novel data interpretation approach. The accuracy of the novel FO-DPHP design was tested at different θ in a sand column experiment. The FO-DPHP measurements obtained using traditional and novel data interpretation approaches were compared against independent measurements from several calibrated soil water content (EC5) sensors. Monte-Carlo analyses were also performed to assess the impact of DTS measurement errors on the accuracy achieved using the data interpretation approaches. The novel design and data interpretation approach allowed for accurate measurements of soil thermal properties and θ without the need to perform a hard-to-achieve soil-specific calibration. Measured θ had mean errors and standard deviations <0.03 and <0.01 m 3 m -3 , respectively, for moisture conditions ranging from dry to near saturation. The standard deviation in the measured heat capacity was <0.01 MJ m -3 K -1 .

42 ENGINEERING↗

DOE OSTI2023

Observations of Ocean Surface Wave Attenuation in Sea Ice Using Seafloor Cables

Abstract The attenuation of ocean surface waves during seasonal ice cover is an important control on the evolution of Arctic coastlines. The spatial and temporal variations in this process have been challenging to resolve with conventional sampling using sparse arrays of moorings or buoys. We demonstrate a novel method for persistent observation of wave‐ice interactions using distributed acoustic sensing (DAS) along existing seafloor fiber optic telecommunications cables. DAS measurements span a 36‐km cross‐shore cable on the Beaufort Shelf from Oliktok Point, Alaska. DAS optical sensing of fiber strain‐rate provides a proxy for seafloor pressure, which we calibrate with wave buoy measurements during the ice‐free season (August 2022). We apply this calibration during the ice formation season (November 2021) to obtain unprecedented resolution of variable wave attenuation rates in new, partial ice cover. The location and strength of wave attenuation serve as proxies for ice coverage and thickness, especially during rapidly evolving events.

Smith, Madison M.↗

DOE OSTI2023

Joint Geophysical and Numerical Insights of the Coupled Thermal‐Hydro‐Mechanical Processes During Heating in Salt

Abstract Salt offers an optimal medium for the permanent isolation of heat‐producing radioactive waste due to its impermeability, high thermal conductivity, and ability to close fractures through creep. A thorough understanding of the thermal‐hydrological‐mechanical (THM) processes, encompassing brine migration, is fundamental for secure radioactive waste disposal within salt formations. At the Waste Isolation Pilot Plant (WIPP), we conducted joint in situ geophysical monitoring experiments during active heating to investigate brine migration near excavations. This experiment incorporated electrical resistivity tomography (ERT) alongside high‐resolution fiber‐optic‐based distributed temperature sensing within a controlled heating experiment. Additionally, discrete element model (DEM) based numerical simulations were conducted to simulate THM processes during heating, providing a more mechanistic understanding of the coupled processes leading to the observed changes in geophysical measurements. During heating, resistivity shifts near the heater were reasonably explained by temperature effects. However, in more distant, cooler regions, the resistivity decrease exceeded predictions based solely on temperature. DEM simulations highlighted brine migration, propelled by pore pressure gradients, as the likely primary factor contributing to the additional resistivity decline beyond temperature effects. The comparison between the predicted ERT responses and observations was much improved when considering the effects of brine migration based on the DEM simulations. These geophysical and simulation findings shed light on brine migration in response to salt heating, enhancing our understanding of the coupled THM processes in salt for safe radioactive waste disposal.

58 GEOSCIENCES↗

DOE OSTI2025

Seismic Tremors From Sea‐Landfast Ice Interactions Near Utqiaġvik, Alaska

The mechanical state of Arctic landfast sea ice remains poorly constrained due to limited observations. This study investigates interactions between drifting sea ice and the coastal landfast ice near Utqiaġvik, Alaska by integrating data from broadband seismometer, Distributed Acoustic Sensing, and marine radar. We find that decreases in sea ice velocity, marking transitions from drift to compressive contact, coincide with increased seismic energy. Tremor characteristics vary seasonally with ice conditions. In January, dense ice packs produced sustained harmonic tremors with gliding and U-shaped spectral features, consistent with repetitive stick-slip motion at the ice–ice or ice–ground interface under velocity-weakening friction. In April, smaller fragmented floes generated short-lived, chaotic tremors linked to brittle failure and spatially dispersed impacts. These findings demonstrate that seismic tremors encode the mechanical properties of interacting ice, offering a new tool to distinguish ice regimes and monitor evolving Arctic coastal dynamics under climate change.

58 GEOSCIENCES↗