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Data from the UW Enterpirses LP Well described in Hu, L.; Paronish, T.; Crandall, D.; Jarvis, K.; Mitchell, N.; Brown, S.; Workman, S; Douds, A., Mastalerz, M, Computed Tomography Scanning and Geophysical Measurements of the UW Enterprises Well in Southwestern Indiana; DOE.NETL-2024.XXXX; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2024; p 49.
Satellite orbit analyses are presented which were undertaken for: (1) reasons of insight and economy; (2) obtaining geophysically interesting tesseral harmonics; (3) comparing effects of tracking station location error drag, radiation pressure, and luni-solar attraction to tesseral harmonic effects; and (4) combination of satellite and terrestrial data. The analyses were divided into the following phases: (1) MINITRACK interferometry; early Baker-Nunn camera directions; (2) late Baker-Nunn camera directions; and (3) combined Baker-Nunn camera and TRANET Doppler data.
A compilation of equatorial coordinates, spectral types, magnitudes, and fluxes from five catalogues of infrared observations is presented. This first edition of the Merged Infrared Catalogue contains 11,201 oservations from the Two-Micron Sky Survey, Observations of Infrared Radiation from Cool Stars, the Air Force Geophysics Laboratory four Color Infrared Sky Survey and its Supplemental Catalog, and from Catalog of 10 micron Celestial Objects (HALL). This compilation is a by-product of a computerized infrared data base under development at Goddard Space Flight Center; the objective is to maintain a complete and current record of all infrared observations from 1 micron m to 1000 micron m of nonsolar system objects. These observations are being placed into a standardized system.
In order to use gravity anomalies in geodetic computations and geophysical interpretations, the observed gravity values from which anomalies are derived should be referred to one consistent world wide system. The International Gravity Standardization Net 1971 was adapted by the International Union of Geodesy and Geophysics at Moscow in 1971, the network was result of extensive cooperation by many organizations and individuals around the world. The network contains more than 1800 stations around the world. The data used in the adjustment included more than 25,000 gravimetry, pendulum and absolute measurements.
In certain kinds of geophysical surveys, the fields are continua, but measured at discrete points referenced by their position or time of measurement. Systems of this kind are better modelled by databases built from basic data structures attuned to representing traverses across continua that are not of pre-defined fixed length. The general Array DataBase is built on arrays (ordered sequencies of data) with each array holding data elements of one type. The arrays each occupy their own physical data set, in turn inter-related by a hierarchy to other arrays over the same space/time reference points. The GADB illustrates the principle that a data facility should reflect the fundamental properties of its data, and support retrieval based on the application's view. The GADB is being tested by its use in NASA's project MAGSAT.
The NASA Scatterometer, NSCAT, is an active spaceborne radar designed to measure the normalized radar backscatter coefficient (sigma0) of the ocean surface. These measurements can, in turn, be used to infer the surface vector wind over the ocean using a geophysical model function. Several ambiguous wind vectors result because of the nature of the model function. A median-filter-based ambiguity removal algorithm will be used by the NSCAT ground data processor to select the best wind vector from the set of ambiguous wind vectors. This process is commonly known as dealiasing or ambiguity removal. The baseline NSCAT ambiguity removal algorithm and the method used to select the set of optimum parameter values are described. An extensive simulation of the NSCAT instrument and ground data processor provides a means of testing the resulting tuned algorithm. This simulation generates the ambiguous wind-field vectors expected from the instrument as it orbits over a set of realistic meoscale wind fields. The ambiguous wind field is then dealiased using the median-based ambiguity removal algorithm. Performance is measured by comparison of the unambiguous wind fields with the true wind fields. Results have shown that the median-filter-based ambiguity removal algorithm satisfies NSCAT mission requirements.
The morphology and morphometry of a number of coronae and related features on Venus are discussed with reference to new data from the Magellan spacecraft. The specific features discussed are concentrated in the portion of Venus imaged during about the first three months of Magellan mapping. Sequences of events and basic geophysical processes involved in the formation of these features are inferred.
The University of Kansas and the University of Washington conducted a series of experiments during July and August of 1989, and July and August of 1990, to study the effects of various geophysical parameters on radar backscatter. The experiments were conducted from a platform in Lake Washington. Measurements of backscattered power and radar range were made by the University of Kansas, and environmental data such as wind speed, wind direction, and air and water temperature were measured by the University of Washington. Results of preliminary data processing are described. Radar data were acquired using two radars, one that operated at C and X bands and another at Ka band. Measurements were made at W and HH antenna polarizations, at different angles of incidence and under various wind conditions. Plots of backscattered power, normalized radar cross section, and wave height, and the Modulation Transfer Functions of selected data are presented.
This report provides a context in which questions put forth by NASA's Office of Mission to Planet Earth (OMPTE) regarding the next steps in spaceborne synthetic aperture radar (SAR) science and technology can be addressed. It summarizes the state-of-the-art in theory, experimental design, technology, data analysis, and utilization of SAR data for studies of the Earth, and describes potential new applications. The report is divided into five science chapters and a technology assessment. The chapters summarize the value of existing SAR data and currently planned SAR systems, and identify gaps in observational capabilities needing to be filled to address the scientific questions. Cases where SAR provides complementary data to other (non-SAR) measurement techniques are also described. The chapter on technology assessment outlines SAR technology development which is critical not only to NASA's providing societally relevant geophysical parameters but to maintaining competitiveness in SAR technology, and promoting economic development.
Several years of total ozone measured from space by the ERS-2 GOME, the Earth Probe Total Ozone Mapping Spectrometer (TOMS), and the ADEOS TOMS, are compared with high-quality ground-based observations associated with the Network for the Detection of Stratospheric Change (NDSC), over an extended latitude range and a variety of geophysical conditions. The comparisons with each spaceborne sensor are combined altogether for investigating their respective solar zenith angle (SZA) dependence, dispersion, and difference of sensitivity. The space- and ground-based data are found to agree within a few percent on average. However, the analysis highlights for both Global Ozone Monitoring Experiment (GOME) and TOMS several sources of discrepancies, including a dependence on the SZA at high latitudes and internal inconsistencies.
Numerous geophysical inverse problems prove difficult because the available measurements are indirectly related to the underlying unknown dynamic state and the physics governing the system may involve imperfect models or unobserved parameters. Data assimilation addresses these difficulties by combining the measurements and physical knowledge. The main challenge in such problems usually involves their high dimensionality and the standard statistical methods prove computationally intractable. This paper develops and addresses the theoretical convergence of a new high-dimensional Monte-Carlo approach called the localized ensemble Kalman smoother.
The Manson Impact Structure (MIS) is located in northwest Iowa, has an age of approximately 74 Ma, and diameter of approximately 35 km. MIS is characterized by a central uplift of crystalline rock surounded by a depression filled with breccia and in turn surrounded by a terraced rim of slumped blocks. MIS is buried by glacial till; hence the geology must be studied through coring and geophysical techniques. Here, results of a gravity survey are reported. The residual gravity pattern is complicated by numerous highs and lows associated with density variations within the crystalline basement. The gravity data indicate a complex central uplift, perhaps a pitted central peak; a breccia unit approximately 3000 m thick surrounding the central uplift, and a diameter of about 35 km.
Developing a machine learning pipeline to automatic the classification of research article topics, where topics are geophysical descriptors. The resulting classified documents will be added to the Usage-Based Discovery graph database, along with corresponding NASA Earth Science datasets, with the intent of linking the NASA data product with uses of it that can be searched by topic. The project will aid in the following goals (1) creating a wider representation of how and how much NASA Earth Science data products are used, (2) identifying when NASA data products have been used even when they are not clearly cited, and (3) providing the UBD search tool end-user with set of recommended datasets based on a given topic query.
The project is motivated by the challenges, risks, and costs associated with geothermal exploration and production. Many processes and parameters impacting geothermal conditions are poorly understood. Diverse datasets are available to help characterize subsurface geothermal conditions (public and proprietary; satellite, airborne surveys, vegetation/water sampling, geological, geophysical, etc.). Yet, it is not clear how to properly leverage these datasets for geothermal exploration due to an incomplete understanding of how physical processes impacting subsurface geothermal conditions are represented in these observations. Recent advancements in machine learning (ML) provide great promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. Our goals and work under Phases 1 and 2 (as proposed) of this project address all these needs.
The number of permanently operating precision Global Positioning System (GPS) receivers in the Southern California Integrated GPS Network has increased dramatically in the past year to several dozen. This number is expected to increase to hundreds within a few years. A prototype system to process all of these data, accurately, rapidly, and economically, has been in operation since May 1995.
Hidden geothermal systems represent a potentially prolific energy resource that could support critical U.S. public and government energy priorities. Basin and Range Investigations for Developing Geothermal Energy (BRIDGE) addressed some the challenges associated with hidden system exploration by prioritizing cost-effective exploration early on through strategic workflow and informed decision-making that mitigates early risk and shifts resources to later exploration stages (e.g., drilling). Sandia National Laboratories partnered with U.S. Navy Geothermal Office, Geologic Geothermal Group, and independent consultants, with additional collaboration with U.S. Geological Survey and private industry. The primary tool of the BRIDGE project was to deploy a regional-scale airborne electromagnetic method to investigate the shallow resistivity structure in areas with high prospectivity. This was followed up at several prospects by a multidisciplinary exploration approach, including additional geologic, geophysical and geochemical studies. A central tenet to the BRIDGE methodology is that zones of low resistivity frequently occur over geothermal systems in the Basin and Range, and when paired with other data constraints, imaging these zones can enable discovery of these systems. In addition to exploring greenfield areas (i.e., Grover Point), the BRIDGE project also flew HTEM resistivity surveys over known geothermal systems including those with established power plants (Don A. Campbell and Salt Wells) and prospects that are known to the literature but remain undeveloped, at least in part, due to a lack of understanding on the location of their producible reservoirs. BRIDGE produced a comprehensive set of data from prospects identified in the Nevada Play Fairway Analysis along with conceptual models for top ranking prospects, wherein all of the observations are used to inform an interpreted model of the system. These models present a range of possible system parameters such as temperature and size, and they are further informed by system analogues in the Basin and Range province and elsewhere. The results of this work leave space for further exploration that may now occur at prospects ‘down the list’ rather than distribution exploration resources evenly across all prospects.
Disaster mitigation consists of many activities, including vulnerability assessment, disaster warning and prediction and disaster relief. Various types of satellites can be applied to these endeavors: communications, geophysical, meteorological and Earth resources. The latter two are considered 'remote sensing' satellites. There are many limitations in the design and development of remote sensing satellites; limitations in cost and the acceptable data rate and limitations in our technology. Nevertheless, there are a large number of satellites, both currently in orbit and planned, with capabilities pertinent to disaster mitigation. Some of these are operational and can be relied upon to provide continued data sources. Others are experimental and provide the disaster management community and opportunity to assess the potential usefulness of the techniques and to impact the design of future operational systems. A table lists the operational parameters and potential application in disaster mitigation of 44 current and planned remote sensing satellites and instruments.
The use of the Principal Component Analysis technique for the analysis of geophysical time series has been questioned in particular for its tendency to extract components that mix several physical phenomena even when the signal is just their linear sum. We demonstrate with a data simulation experiment that the Independent Component Analysis, a recently developed technique, is able to solve this problem. This new technique requires the statistical independence of components, a stronger constraint, that uses higher-order statistics, instead of the classical decorrelation a weaker constraint, that uses only second-order statistics. Furthermore, ICA does not require additional a priori information such as the localization constraint used in Rotational Techniques.