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DOE OSTI2021

Randomized Sketching Algorithms for Low-Memory Dynamic Optimization

This paper develops a novel limited-memory method to solve dynamic optimization problems. The memory requirements for such problems often present a major obstacle, particularly for problems with PDE constraints such as optimal flow control, full waveform inversion, and optical tomography. In these problems, PDE constraints uniquely determine the state of a physical system for a given control; the goal is to find the value of the control that minimizes an objective. While the control is often low dimensional, the state is typically more expensive to store. This paper suggests using randomized matrix approximation to compress the state as it is generated and shows how to use the compressed state to reliably solve the original dynamic optimization problem. Concretely, the compressed state is used to compute approximate gradients and to apply the Hessian to vectors. The approximation error in these quantities is controlled by the target rank of the sketch. This approximate first- and second-order information can readily be used in any optimization algorithm. As an example, we develop a sketched trust-region method that adaptively chooses the target rank using a posteriori error information and provably converges to a stationary point of the original problem. Numerical experiments with the sketched trust-region method show promising performance on challenging problems such as the optimal control of an advection-reaction-diffusion equation and the optimal control of fluid flow past a cylinder.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Decoupled Fréchet kernels based on a fractional viscoacoustic wave equation

We formulate the Fréchet kernel computation using the adjoint-state method based on a fractional viscoacoustic wave equation. We first numerically prove that both the 1/2- and the 3/2-order fractional Laplacian operators are self-adjoint. Using this property, we show that the adjoint wave propagator preserves the dispersion and compensates the amplitude, while the time-reversed adjoint wave propagator behaves identically as the forward propagator with the same dispersion and dissipation characters. Without introducing rheological mechanisms, this formulation adopts an explicit Q parameterization, which avoids the implicit Q in the conventional viscoacoustic/viscoelastic full waveform inversion (Q-FWI). In addition, because of the decoupling of operators in the wave equation, the viscoacoustic Fréchet kernel is separated into three distinct contributions with clear physical meanings: lossless propagation, dispersion, and dissipation. Here, we find that the lossless propagation kernel dominates the velocity kernel, while the dissipation kernel dominates the attenuation kernel over the dispersion kernel.

58 GEOSCIENCES↗

DOE OSTI2023

SKS Polarization Anomalies Due to the Coriolis Force

The Earth’s Coriolis force has been well–known to impact surface waves and normal modes, which is essential to accurately interpret these waves. However, the Coriolis force on body waves has been assumed to be negligible and mostly ignored. It has been previously shown that the Coriolis force impacts polarizations of shear waves, whereas the wavefronts remain unaffected. We expand on the potential influences of Earth’s Coriolis force on shear–wave polarization measurements by conducting 3D numerical simulations for elastic waves generated by earthquake and explosive sources in a radially symmetric, and 3D mantle and crustal models. The Coriolis force can produce polarization anomalies of mantle shear waves up to 7° and core phases, such as SKS and SKKS, up to 4°. Uncorrected shear–wave polarizations due to the Coriolis force can cause an additional source of error (5°–10° in fast direction, and 0.2–0.3 s delay time depending on the method and seismic phase), inaccurate interpretation of station misalignments, and imprecise estimates of the core–mantle boundary topography. We show how to correct for the Coriolis force on teleseismic shear waves using 1D ray tracing for well–isolated phases. Here, we recommend the use of full waveform simulations to accurately account for earthquake sources parameters, poorly isolated phases that could include interfering phase arrivals within the measurement time window, and the effect of the Coriolis force on the polarizations of shear waves.

58 GEOSCIENCES↗

DOE OSTI2021

Development of Time Lapse VSP Integration Workflow: A Case Study at Farnsworth CO2-EOR Project

Abstract This study aims to develop a 4D Vertical Seismic Profile (VSP) integration workflow to improve the prediction of subsurface stress changes. The selected study site is a 5-spot pattern within the ongoing CO2-EOR operations at the Farnsworth Field Unit FWU in Ochiltree County, Texas. The specific pattern has undergone extensive geological and geomechanical characterization through the acquisition of 3D seismic data, geophysical well logs, and core. This workflow constrains a numerical hydromechanical model by applying a penalty function formed between "modeled" versus "observed" time-lapse compressional and shear seismic velocity changes. Analyses of geophysical logs and ultra-sonic measurements on core exhibit measurable sensitivities to changes in both fluid saturation and mean effective stress. These data are used to develop a site-specific rock physics model and stress-velocity relationship, which inform the numerical models used to generate the "modeled" portion of the penalty function. The "observed" portion of the penalty function is provided by a novel elastic full-waveform inversion of the available 3D baseline and three monitor surveys to produce high-quality estimates of time-lapse compressional and shear seismic velocity changes. The modeling workflow accounts sequentially for fluid substitution and stress impacts. Hydrodynamic and geomechanical properties of the 3D coupled numerical model are estimated through geostatistical integration of well log and core data with 3D seismic inversion products. Changes in seismic velocities due to fluid substitution are computed using the Biot-Gassmann workflow and site-specific rock physics. Stress impacts on time-lapse seismic velocity changes are modeled from the effective stress output of the hydromechanical model and are initially based on the velocity versus effective stress relationship extracted from core mechanical testing. Based on the principle of superposition of seismic wavefields, seismic velocity changes attributed to fluid substitution and that due to changes in mean effective stress are treated as linearly additive. The modeled results are upscaled using Backus averaging to reconcile scale discrepancies between the modeled and measured datasets to formulate the penalty function. This manuscript presents the forward modeling process and concludes that for the base case, the seismic velocity changes due to mean effective stress dominates over the seismic velocity changes attributed to fluid substitution because of the extensive range of the pressure perturbations. Successful minimization of this penalty function calibrates the coupled hydrodynamic geomechanical numerical model and affirms the suitability of acoustic time-lapse measurements such as 4D-VSP for geomechanical calibration.

02 PETROLEUM↗

DOE OSTI2021

Uncertainty Quantification of Geophysical Inversion Using Stochastic Partial Differential Equations (LDRD #218329)

This report summarizes work completed under the Laboratory Directed Research and Development (LDRD) project "Uncertainty Quantification of Geophysical Inversion Using Stochastic Differential Equations." Geophysical inversions often require computationally expensive algorithms to find even one solution, let alone propagating uncertainties through to the solution domain. The primary purpose of this project was to find more computationally efficient means to approximate solution uncertainty in geophysical inversions. We found multiple computationally efficient methods of propagating Earth model uncertainty into uncertainties in solutions of full waveform seismic moment tensor inversions. However, the optimum method of approximating the uncertainty in these seismic source solutions was to use the Karhunen-Love theorem with data misfit residuals. This method was orders of magnitude more computationally efficient than traditional Monte Carlo methods and yielded estimates of uncertainty that closely approximated those of Monte Carlo. We will summarize the various methods we evaluated for estimating uncertainty in seismic source inversions as well as work toward this goal in the realm of 3-D seismic tomographic inversion uncertainty.

58 GEOSCIENCES↗

DOE OSTI2023

Integration of seismic-pressure-petrophysics inversion of continuous active-seismic monitoring data for monitoring and quantifying CO 2 plume (Final Report)

The overall objective of this project is to develop and validate an integrated package of joint seismic-pressure-petrophysics inversion (jSPPI) of continuous active-source seismic monitoring dataset capable of providing real-time monitoring of CO 2 plume during geologic carbon sequestration (GCS). The three specific developments include: (a) the methodologies for fast seismic full waveform inversion of continuous active source seismic monitoring, (CASSM) datasets for simultaneously estimating velocity and attenuation, and with data assimilation; (b) joint Bayesian petrophysical inversion of seismic models and pressure data for providing and updating CO 2 saturation models; (c) the methods using multiple datasets including (Crainfield and Frio-II borehole) synthetic, laboratory, and field CASSM datasets. The outcomes of jSPPI include (a) a workflow for processing CASSM data, (b) Bayesian inversion algorithms using CASSM data and pressure response data, and (c) integration with data assimilation algorithms for continuously updating site-specific models used for prediction and reservoir management. The validation of joint FWI will be conducted using synthetic models based on the Cranfield and Frio experiments as well as field CASSM datasets collected as part of the Frio-II pilot injection. To quantify and map the mass and distribution of CO 2 (saturation), we will jointly invert velocity and attenuation measurements from the FWI with a Bayesian approach using a rock physics model for attenuation (e.g., White’s attenuation model with two selected patch sizes (White, 1976; Dutta and Seriff, 1979)). The Bayesian inversion will be applied to each time step in the CASSM survey in an updating scheme, which integrates with an ensemble of reservoir simulations at each step. A more complete experimental validation dataset will be collected as part of a mesoscale (2-3 m) gas-CO 2 injection experiment utilizing a higher frequency version of the CASSM system developed for laboratory studies; the integrated inversion will be demonstrated using this dataset which will provide both a dense geometry as well as more precise secondary confirmation measurements (e.g. saturation) typically not available in the field. The resulting real-time map of CO 2 saturation is able to provide a deeper scientific understanding of the complex, time-varying dynamics of subsurface fluid flow migration path as well as the rapid detection of CO 2 leakage hazards.

25 ENERGY STORAGE↗

DOE OSTI2024

ASIC Scoping Study Final Report

This report documents the results and findings of a one-year scoping study investigating multichannel readout application specific integrated circuits (ASICs) for interfacing to, and processing data from, silicon photomultiplier (SiPM) arrays. We document ASIC desired and required specifications for four applications supporting national security mission areas: neutron radiography, associated particle imaging, and two versions of kinematic neutron imaging cameras. While each application has a few unique requirements that stress capability, there is generally good agreement among most. Two recently developed ASIC devices were evaluated in a system-like configuration by interfacing these to scintillator crystals exposed to gamma and neutron sources. The 64-channel ORNL device delivered functional capability while meeting most mission requirements for neutron radiography. The Nalu Scientific device, a 32-channel full waveform digitizer, did not demonstrate reliable neutron / gamma separation but it is unclear if this was an ASIC issue or problems with test setup or firmware. A literature survey of other commercial and academic ASICs was undertaken to with the conclusion that existing devices do not meet all requirements.

42 ENGINEERING↗

DOE OSTI2025

Quantifying uncertainty in regional-scale seismic moment tensors

We examine the ability of three different inversion methods: 1) first motion (FM) inversions, 2) amplitude inversions, and 3) full waveform (FW) time variable moment tensor (TVMT) inversions, to recover an accurate source mechanism for simulated data for an earthquake as well as an explosion. The ability of inversion methods, such as the ones described above, to recover accurate models representative of the data depends on both a priori information as well as the quality of data being inverted. Therefore, we examine the effect that station geometry, geologic model, and noise level has on the inversion and estimated source mechanism. We find that FM data can provide more robust solutions than amplitude data and are not as sensitive to inaccurate earth models, especially in low-noise cases, and overall FW inversions are the most accurate out of the methods examined, but can still be biased by inaccurate earth models.

58 GEOSCIENCES↗

NASA NTRS2011

Polarimetric, Two-Color, Photon-Counting Laser Altimeter Measurements of Forest Canopy Structure

Laser altimeter measurements of forest stands with distinct structures and compositions have been acquired at 532 nm (green) and 1064 nm (near-infrared) wavelengths and parallel and perpendicular polarization states using the Slope Imaging Multi-polarization Photon Counting Lidar (SIMPL). The micropulse, single photon ranging measurement approach employed by SIMPL provides canopy structure measurements with high vertical and spatial resolution. Using a height distribution analysis method adapted from conventional, 1064 nm, full-waveform lidar remote sensing, the sensitivity of two parameters commonly used for above-ground biomass estimation are compared as a function of wavelength. The results for the height of median energy (HOME) and canopy cover are for the most part very similar, indicating biomass estimations using lidars operating at green and near-infrared wavelengths will yield comparable estimates. The expected detection of increasing depolarization with depth into the canopies due to volume multiple-scattering was not observed, possibly due to the small laser footprint and the small detector field of view used in the SIMPL instrument. The results of this work provide pathfinder information for NASA's ICESat-2 mission that will employ a 532 nm, micropulse, photon counting laser altimeter.

Harding, David J.↗

NASA NTRS2012

Forest Canopy Cover and Height from MISR in Topographically Complex Southwestern US Landscape Assessed with High Quality Reference Data

This study addresses the retrieval of spatially contiguous canopy cover and height estimates in southwestern USforests via inversion of a geometric-optical (GO) model against surface bidirectional reflectance factor (BRF) estimates from the Multi-angle Imaging SpectroRadiometer (MISR). Model inversion can provide such maps if good estimates of the background bidirectional reflectance distribution function (BRDF) are available. The study area is in the Sierra National Forest in the Sierra Nevada of California. Tree number density, mean crown radius, and fractional cover reference estimates were obtained via analysis of QuickBird 0.6 m spatial resolution panchromatic imagery usingthe CANopy Analysis with Panchromatic Imagery (CANAPI) algorithm, while RH50, RH75 and RH100 (50, 75, and 100 energy return) height data were obtained from the NASA Laser Vegetation Imaging Sensor (LVIS), a full waveform light detection and ranging (lidar) instrument. These canopy parameters were used to drive a modified version of the simple GO model (SGM), accurately reproducing patterns ofMISR 672 nm band surface reflectance (mean RMSE 0.011, mean R2 0.82, N 1048). Cover and height maps were obtained through model inversion against MISR 672 nm reflectance estimates on a 250 m grid.The free parameters were tree number density and mean crown radius. RMSE values with respect to reference data for the cover and height retrievals were 0.05 and 6.65 m, respectively, with of 0.54 and 0.49. MISR can thus provide maps of forest cover and height in areas of topographic variation although refinements are required to improve retrieval precision.

Chopping, Mark↗

NASA NTRS2020

Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels

We introduce a multiscale superpixel approach that leverages repeat-pass interferometric coherence and sparse AGB estimates from a simulated spaceborne lidar in order to extend the NISAR mission’s applicable range of aboveground biomass (AGB) in tropical forests. Airborne and spaceborne L-band radar and full-waveform airborne lidar data are used to simulate the NISAR and GEDI mission, respectively. In addition to UAVSAR data, we use spaceborneALOS-2/PALSAR-2 imagery with 14-day temporal baseline, which is comparable to NISAR’s 12-daybaseline. Our reference AGB maps are derived from the airborne LVIS data during the AfriSAR campaign for three sites (Mondah, Ogooue, and Lope). Each tropical site has mean AGB of at least 125 Mg/ha in addition to areas with AGB exceeding 700 Mg/ha. Spatially sampling from these LVIS-derived AGB reference maps, we approximate GEDI AGB estimates. To evaluate our methodology, we perform several different analyses. First, we partition each study site into low(≤100 Mg/ha) and high (>100 Mg/ha) AGB areas, in conformity with the NISAR mission requirement to provide AGB estimates for forests between 0 and 100 Mg/ha with a RMSE below 20 Mg/ha. In the low AGB areas, this RMSE requirement is satisfied in Lope and Mondah and it fell short of the requirement in Ogooue by less 3 Mg/ha with UAVSAR and 6 Mg/ha with PALSAR-2. We note that our maps have finer spatial resolution (50 m) than NISAR requires (1 hectare). In the high AGB areas, the normalized RMSE increases to 51% (i.e.,<90 Mg/ha), but with negligible bias for all three sites. Second, we train a single model to estimate AGB across both high and low AGB regimes simultaneously and obtain a normalized RMSE that is<60% (or<100 Mg/ha). Lastly, we show the use of both (a) multiscale superpixels and (b) interferometric coherence significantly improves the accuracy of the AGB estimates. The InSAR coherence improved the RMSE by approximately 8% at Mondah with both sensors, lowering the RMSE from 59 Mg/ha to 47.4 Mg/h with UAVSAR and from 57.1 Mg/ha to 46 Mg/ha. This work illustrates one of the numerous synergistic relationships between the spaceborne lidars, such as GEDI, with L-band SAR, such as PALSAR-2 and NISAR, in order to produce robust regional AGB in high biomass tropical regions.

NISAR↗

NASA NTRS2022

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Laura Duncanson↗

DOE OSTI2022

Methods and systems for obtaining reconstructed low-frequency seismic data for determining a subsurface feature

A computer-implemented method for obtaining reconstructed seismic data for determining a subsurface feature, includes: determining an initial training velocity model, training a machine learning model based on first training seismic data and second training seismic data generated from the training velocity model, the first training seismic data corresponding to one or more first frequencies, the second training seismic data corresponding to one or more second frequencies lower than the one or more first frequencies, obtaining, based on measured seismic data and the machine learning model, reconstructed seismic data corresponding to the one or more second frequencies, generating a velocity model based on the measured seismic data, the reconstructed seismic data, and a full waveform inversion (FWI), and when the generated velocity model does not satisfy a preset condition, updating the training velocity model based on the generated velocity model, to obtain updated reconstructed seismic data for determining a subsurface feature.

58 GEOSCIENCES↗

DOE OSTI2022

Tsunami Early Warning From Global Navigation Satellite System Data Using Convolutional Neural Networks

Abstract We investigate the potential of using Global Navigation Satellite System (GNSS) observations to directly forecast full tsunami waveforms in real time. We train convolutional neural networks to use less than 9 min of GNSS data to forecast the full tsunami waveforms over 6 hr at select locations, and obtain accurate forecasts on a test data set. Our training and test data consists of synthetic earthquakes and associated GNSS data generated for the Cascadia Subduction Zone using the MudPy software, and corresponding tsunami waveforms in Puget Sound computed using GeoClaw. We use the same suite of synthetic earthquakes and waveforms as in earlier work where tsunami waveforms were used for forecasting, and provide a comparison. We also explore varying the number of GNSS stations, their locations, and their observation durations.

Rim, Donsub↗

NASA NTRS2012

Beat-to-Beat Blood Pressure Monitor

This device provides non-invasive beat-to-beat blood pressure measurements and can be worn over the upper arm for prolonged durations. Phase and waveform analyses are performed on filtered proximal and distal photoplethysmographic (PPG) waveforms obtained from the brachial artery. The phase analysis is used primarily for the computation of the mean arterial pressure, while the waveform analysis is used primarily to obtain the pulse pressure. Real-time compliance estimate is used to refine both the mean arterial and pulse pressures to provide the beat-to-beat blood pressure measurement. This wearable physiological monitor can be used to continuously observe the beat-to-beat blood pressure (B3P). It can be used to monitor the effect of prolonged exposures to reduced gravitational environments and the effectiveness of various countermeasures. A number of researchers have used pulse wave velocity (PWV) of blood in the arteries to infer the beat-to-beat blood pressure. There has been documentation of relative success, but a device that is able to provide the required accuracy and repeatability has not yet been developed. It has been demonstrated that an accurate and repeatable blood pressure measurement can be obtained by measuring the phase change (e.g., phase velocity), amplitude change, and distortion of the PPG waveforms along the brachial artery. The approach is based on comparing the full PPG waveform between two points along the artery rather than measuring the time-of-flight. Minimizing the measurement separation and confining the measurement area to a single, well-defined artery allows the waveform to retain the general shape between the two measurement points. This allows signal processing of waveforms to determine the phase and amplitude changes. Photoplethysmography, which measures changes in arterial blood volume, is commonly used to obtain heart rate and blood oxygen saturation. The digitized PPG signals are used as inputs into the beat-to-beat blood pressure measurement algorithm.

Lee, Yong Jin↗

NASA NTRS2012

Beat-to-Beat Blood Pressure Monitor

Lee, Yong Jin↗

DOE OSTI2025

PhotonIDs: ML-Powered Photon Identification System for Dark Count Elimination

Reliable single photon detection is the foundation for practical quantum communication and networking. However, today's superconducting nanowire single photon detector(SNSPD) inherently fails to distinguish between genuine photon events and dark counts, leading to degraded fidelity in long-distance quantum communication. In this work, we introduce PhotonIDs, a machine learning-powered photon identification system that is the first end-to-end solution for real-time discrimination between photons and dark count based on full SNSPD readout signal waveform analysis. PhotonIDs ~demonstrates: 1) an FPGA-based high-speed data acquisition platform that selectively captures the full waveform of signal only while filtering out the background data in real time; 2) an efficient signal preprocessing pipeline, and a novel pseudo-position metric that is derived from the physical temporal-spatial features of each detected event; 3) a hybrid machine learning model with near 98% accuracy achieved on photon/dark count classification. Additionally, proposed PhotonIDs ~ is evaluated on the dark count elimination performance with two real-world case studies: (1) 20 km quantum link, and (2) Erbium ion-based photon emission system. Our result demonstrates that PhotonIDs ~could improve more than 31.2 times of signal-noise-ratio~(SNR) on dark count elimination. PhotonIDs ~ marks a step forward in noise-resilient quantum communication infrastructure.

Linne, Karl C. [Chicago U.] (ORCID:000900091870358↗

NASA NTRS2008

Simple Waveforms, Simply Described

Since the first Lazarus Project calculations, it has been frequently noted that binary black hole merger waveforms are 'simple.' In this talk we examine some of the simple features of coalescence and merger waveforms from a variety of binary configurations. We suggest an interpretation of the waveforms in terms of an implicit rotating source. This allows a coherent description, of both the inspiral waveforms, derivable from post-Newtonian(PN) calculations, and the numerically determined merger-ringdown. We focus particularly on similarities in the features of various Multipolar waveform components Generated by various systems. The late-time phase evolution of most L these waveform components are accurately described with a si~nple analytic fit. We also discuss apparent relationships among phase and amplitude evolution. Taken together with PN information, the features we describe can provide an approximate analytic description full coalescence wavefoRms. complementary to other analytic waveforn~s approaches.

Baker, John G.↗