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At least 1,045 records · Page 58

Analysis of Selected Publicly Available Geothermal Exploration Data Gaps

As part of a United States Department of Energy (DOE) supported retrospective analysis of DOE's Play Fairway Analysis (PFA) projects, the National Renewable Energy Laboratory (NREL) compiled and analyzed publicly available geothermal exploration datasets to identify and highlight data gaps in areas prospective for hosting geothermal resources. The analysis was intended to understand the existing geographic coverage of selected datasets commonly utilized both by the PFA projects and geothermal developers during resource assessments including geologic mapping, temperature gradient drilling, and aeromagnetic, gravimetric, and lidar surveys. Results indicate that broad areas of the western United States estimated to have geothermal potential lack sufficient geologic and geophysical coverage necessary for even regional resource exploration. The study directly informed the recent Geoscience Data Acquisition for Western Nevada, or GeoDAWN - which united DOE's Geothermal Technologies Office (GTO) with the U.S. Geological Survey (USGS) of the U.S. Department of the Interior to assist U.S. needs for energy and critical minerals. The study also has the potential to inform public investment in further data acquisition for characterization of the Earth both for geothermal and other natural resource assessments.

data↗

Quality Assessment of Landsat Surface Reflectance Products Using MODIS Data

Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat images for the 2000 epoch. As surface reflectance likely will be a standard product for future Landsat missions, the approach developed in this study can be adapted as an operational quality assessment system for those missions.

Landsat↗

Production and Distribution of NASA MODIS Remote Sensing Products

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the MODIS Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original MODIS science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to MODIS, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.

Wolfe, Robert↗

Long-Term Evaluation of Landsat 9 Oli Data Product Uniformity at Focal Plane Module-Boundaries Using Earth Scenes

The uniformity performance characteristic in remote sensing data products is a metric that helps evaluate how an image accurately represents radiometric responses to geophysical variability at the Earth’s surface or within the atmosphere. These uniformity attributes are used in Earth remote sensing science applications such as investigating water quality, land-cover/land-use classifications, and crop health assessments. To ensure these applications perform effectively, it is crucial to maintain and regularly assess the uniformity of calibrated remote sensing data products. In the Landsat missions, data from the onboard radiometric reference Solar diffuser device are used as the standard approach to derive the calibration parameters, ensuring the maintenance of both absolute radiance and radiometric uniformity through quarterly updates. This publication presents an alternative approach that leverages Earth scene data to assess the on-orbit uniformity performance of the Landsat 9 (L9) mission. The analysis characterizes uniformity at a specific set of spatial positions (the focal-plane boundary zones) that are intrinsic to the Operational Land Imager (OLI) focal plane design. By employing these Earth data statistics, the article further explores the temporal trends in the radiometric uniformity results. The results shown in this article demonstrate that for pushbroom imaging design systems with staggered sensor chip focal plane architectures, the co-registered pixels, i.e., overlapping measurements of the same ground target viewed by different detectors, offer a self-contained mechanism for assessing product uniformity. Remarkably, this alternative approach achieves a level of radiometric quality comparable to that delivered by a stable, well-characterized onboard Solar diffuser calibration device. The findings demonstrate the potential and capability of such Earth scene statistics in maintaining radiometric uniformity in calibrated data products to better than 1% (1-sigma) throughout the mission’s operational lifetime.

trend↗

Industrial use of land observation satellite systems

The principal industrial users of land observation satellite systems are the geological industries; oil/gas, mining, and engineering/environmental companies. The primary system used is LANDSAT/MSS. Currently, use is also being made of the limited amounts of SKYLAB photography, SEASAT and SIR-A radar, and the new LANDSAT/TM data available. Although considered experimental, LANDSAT data is now used operationally by several hundred exploration and engineering companies worldwide as a vastly improved geological mapping tool to help direct more expensive geophysical and drilling phases, leading to more efficient decision-making and results. Future needs include global LANDSAT/TM; higher spatial resolution; stereo and radar; improved data handling, processing distribution and archiving systems, and integrated geographical information systems (GIS). For a promising future, governments must provide overall continuity (government and/or private sector) of such systems, insure continued government R and D, and commit to operating internationally under the civil Open Skies policy.

Henderson, F. B., III↗

Inversion of data from diffraction-limited multiwavelength remote sensors. I - Linear case

The remote sensing inverse problem is considered in which the sensor does not necessarily view the same area on the earth at each wavelength, and spatial correlations of the geophysical parameters may be present. Under the conditions of linearity and stationary statistics, the minimum mean-square error solution to the problem of inverting such data is a spatial filter of the Wiener-Kolmogorov class. The resulting remote-sensing system can be characterized by an impulse response matrix in ordinary space or by a transfer matrix in frequency space. A signal-to-noise matrix for the geophysical parameters to be sensed is also defined; this matrix depends on the postulated a priori statistics and on the characteristics of the remote-sensing instrument. The system transfer matrix and the signal-to-noise matrix are simultaneously diagonalizable. The optimum transfer matrix filters out of the estimate vector those eigenparameters for which eigenvalues of the signal-to-noise matrix are less than unity.

Rosenkranz, P. W.↗

Utah FORGE: Fiber Optic Cumulative Strain Change and Strain Change Rate Data From Well 16A Stimulation at Well 16B

This dataset includes Rayleigh Frequency Shift (RFS) Distributed Strain Sensing (DSS) cumulative strain change and change rate data. The data was acquired during the stimulation of Utah FORGE Well 16A(78)-32 in April 2024 via fiber installed in Well 16B(78)-32. The fiber optic data was acquired using Neubrex SR7000 RFS DSS Distributed Strain sensing instruments and is saved here in the format of HDF5 files (.h5 extension). The spatial sampling on the full wellbore profiles is 0.20 centimeters. The data is the far field strain change response from a baseline profile made down the 16B well on April 3, 2024, so each strain value represents the strain change or strain change rate at each depth relative to the baseline reference profile. The data arrays for each type share the same dimensions (number of channels and time stamps).

15 GEOTHERMAL ENERGY↗

The Kimberlina synthetic multiphysics dataset for CO 2 monitoring investigations

Abstract We present a synthetic multi‐scale, multi‐physics dataset constructed from the Kimberlina 1.2 CO 2 reservoir model based on a potential CO 2 storage site in the Southern San Joaquin Basin of California. Among 300 models, one selected reservoir‐simulation scenario produces hydrologic‐state models at the onset and after 20 years of CO 2 injection. Subsequently, these models were transformed into geophysical properties, including P‐ and S‐wave seismic velocities, saturated density where the saturating fluid can be a combination of brine and supercritical CO 2 , and electrical resistivity using established empirical petrophysical relationships. From these 3D distributions of geophysical properties, we have generated synthetic time‐lapse seismic, gravity and electromagnetic responses with acquisition geometries that mimic realistic monitoring surveys and are achievable in actual field situations. We have also created a series of synthetic well logs of CO 2 saturation, acoustic velocity, density and induction resistivity in the injection well and three monitoring wells. These were constructed by combining the low‐frequency trend of the geophysical models with the high‐frequency variations of actual well logs collected at the potential storage site. In addition, to better calibrate our datasets, measurements of permeability and pore connectivity have been made on cores of Vedder Sandstone, which forms the primary reservoir unit. These measurements provide the range of scales in the otherwise synthetic dataset to be as close to a real‐world situation as possible. This dataset consisting of the reservoir models, geophysical models, simulated time‐lapse geophysical responses and well logs forms a multi‐scale, multi‐physics testbed for designing and testing geophysical CO 2 monitoring systems as well as for imaging and characterization algorithms. The suite of numerical models and data have been made publicly available for downloading on the National Energy Technology Laboratory's (NETL) Energy Data Exchange (EDX) website.

58 GEOSCIENCES↗

Utah FORGE: Pump and Probe Test on a Mated Fracture Westerly Granite Sample

This dataset contains results from a pump and probe experiment conducted on a mated fracture Westerly Granite sample with a diameter of 1 inch and a height of 2 7/8 inches. The experiment was performed within an aluminum triaxial pressure vessel (TEMCO) to investigate the non-linear acoustic parameters of the sample under varying axial pressures. The confining pressure was maintained at 4 MPa, while the axial pressure was incrementally reduced from 17 MPa to 1 MPa in 1 MPa steps. 5 dynamic pressure oscillations of 0.5 MPa were applied over a 10 minute interval. The dataset includes pump controller data, linear variable differential transformer (LVDT) measurements, and acoustic data. The pump controller data tracks the confining and axial pressures, flow rates, and pump volumes. LVDT measurements provide detailed records of the axial displacement of the cell piston. Additionally, acoustic data captured by s-wave transducers is archived in a compressed file.

15 GEOTHERMAL ENERGY↗

Satellite magnetic modeling of north African hot spots

The primary objectives of the MAGSAT mission was to measure the intensity and direction of magnetization of the Earth's crust. A significant effort was directed to the large crustal anomalies first delineated by the POGO mission. The MAGSAT data are capable of spatial resolution of the crustal field to 250 km wavelength with reliability limits to less than 1 nT in the mean. The difficulties of dealing with less than the most robust of the MAGSAT anomalies is that often there is no more than the magnetic fields themselves to constrain geophysical models of the interior, and no independent means of assessing the quality of the crustal anomaly data in interpreting the subsurface are available.

Phillips, R. J.↗

Nixon B #1-7 Well Data

Data from the Nixon #1-7 Well described in "Computed Tomography Scanning and Geophysical Measurements of the Fayetteville Shale Formation from the Nixon B #1- 7 Well" TRS

Black shales↗

Physics-Reinforced Machine Learning Algorithms for Multiscale Closure Model Discovery

The central objective of this project was to address the challenge of modeling and simulating complex multiscale turbulence phenomena by leveraging physics-guided machine learning (PGML) and hybrid modeling approaches. By integrating physics-based methods with data-driven models, the research focused on achieving robust and scalable solutions for geophysical turbulence, enhancing numerical weather prediction and climate research tools. The project resulted in significant advancements in computational modeling paradigms, predictive tools for reduced-order modeling, and innovative algorithms for fluid dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Tables of thermospheric temperature, density and composition derived from satellite and ground based measurements. Volume 1: Ap=4

The tables contain the neutral temperature, neutral densities for N2, O2, O, Ar, He and H, mean molecular weight, and total mass density as predicted by the Mass Spectrometer and Incoherent Scatter empirical thermosphere model for selected altitudes, latitudes, local times, days and other geophysical conditions. The model is based on a least squares fit to density data from mass spectrometers on five satellites and temperature data from four incoherent scatter stations, providing coverage for most of solar sunspot cycle 20. Included in the model data base are longitudinally average N3, He, and O densities from the OGO-6 mass spectrometer longitudinally average N2, He, O and Ar densities from the AEROS-A (NATE) mass spectrometer the N2, He, O, and Ar densities from the San Marco 3 mass spectrometer the N2 densities from the AE-B mass spectrometer and the N2, He, O, and Ar densities from the AE-C (OSS, NACE, NATE) mass spectrometers. The O2 and H densities are inferred using ion mass spectrometer data from AE-C (BIMS). Neutral exospheric temperature data are included from Arecibo, St. Santin, Millstone Hill and Jicamarca.

Hedin, A. E.↗

Tables of thermospheric temperature, density and composition derived from satellite and ground based measurements. Volume 3: Ap=100

The neutral temperature, neutral densities for N2, O2, O, Ar, He and H, mean molecular weight, and total mass density as predicted by the Mass Spectrometer and Incoherent Scatter empirical thermosphere model are presented in tabular form. The predictions are based on selected altitudes, latitudes, local times, days and other geophysical conditions. The model is dependent on a least squares fit to density data from mass spectrometers on five satellites and temperature data from four incoherent scatter stations, providing coverage for most of solar sunspot cycle 20.

Hedin, A. E.↗

M2, S2, K1 models of the global ocean tide

Ocean tidal signals appear in many geophysical measurements. Geophysicists need realistic tidal models to aid in interpretation of their data. Because of the closeness to resonance of dissipationless ocean tides, it is difficult for numerical models to correctly represent the actual open ocean tide. As an approximate solution to this problem, test functions derived by solving Laplace's Tidal Equations with ocean loading and self gravitation are used as a basis for least squares dynamic interpolation of coastal and island tidal data for the constituents M2, S2, and Kl. The resulting representations of the global tide are stable over at least a ?5% variation in the mean depth of the model basin, and they conserve mass. Maps of the geocentric tide, the induced free space potential, the induced vertical component of the solid earth tide, and the induced vertical component of the gravitational field for each contituent are presented.

Parke, M. E.↗

The detection of long-term changes in stratospheric ozone Scientific requirements and current results from satellite-based measurement systems

The ability to detect subtle trends in upper stratospheric ozone places strict requirements on satellite-based Solar Backscatter Ultraviolet (SBUV) sensors intended for this purpose. Simulation of the long-term change in backscattered radiance indicates trends in the range 1.0-1.6 percent per decade depending on wavelength for an ozone depletion scenario based on chlorofluorocarbon (CFC) chemistry. The maximum percentage change in the measured quantity, as would be sensed by the Nimbus-7 SBUV experiment and future similar instruments, is roughly a factor of two less than the maximum percentage change in ozone, the quantity of geophysical interest. Furthermore, interannual variations, whose magnitude can be estimated from the SBUV data set, could obscure a CFC-related trend in radiance when viewed over a period less than a decade. Even when such atmospheric noise and possible solar cycle variations are neglected, the detection of an ozone trend of the magnitude predicted for CFC-related chemistry requires a set of radiance measurements that are internally consistent to 1 percent or better over a time span of a decade.

Frederick, J. E.↗