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Acoustic Sensor Network for Planetary Exploration

This paper investigates the concept of an acoustic sensor network that can monitor a variety of geophysical processes occurring on other planetary bodies. In many cases sound is naturally omnidirectional and travels at known speeds which depend on the composition and density of the atmosphere. The differences in the time of flight of signals received by a distributed microphone network can be used to locate the source of the sound. We suggest this property is ideal for mobile planetary robots and can be used to expand the exploration envelope considerably by directing camera pointing or rover path planning thus extending beyond line-of-sight exploration. Acoustic signatures have been used in a variety of fields (e.g., sonar, heavy machinery) to identify and catalog sounds associated with a specific vessels and malfunctioning machinery. Our ears have cataloged hundreds of sounds and we continuously use these sounds both consciously and subconsciously to extract information about our surroundings. This paper investigates the use acoustic measurements on other planetary bodies that could be used to characterize specific environmental parameters such as rain droplet size, wind speed, thunder, or dust devil vortex diameter. The paper identified other important sound sources that are thought to occur on other bodies in our solar system include; booming or singing dunes, waves, rivers, streams, fluidfalls, geysers, hurricanes, tornados, ice flow, volcanoes, planetary quakes, avalanche, rock slides and ice cracking. In addition, this paper focused on issues associated with the development of appropriate sensors for the network including the specification of the sensitivity, frequency response, and directional response of each of the microphones in the network in order to aid in localization of sound sources. We also presented our initial development of the transducers for potential mission targets including Mars and Titan and investigated the use of signal processing techniques including windowing, time frequency plots and correlation techniques to resolve phase differences between sensors in the network to aid in localization. We also identified additional benefits of these sensor networks in that they could used as engineering sensors to diagnose mechanical malfunctions on a rover or lander actuators or mechanisms. We also noted that they could also enhance public outreach by adding sound to videos.

Malaska, Mike↗

Geo Thermal Cloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

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.

15 GEOTHERMAL ENERGY↗

Remote Sensing Applied to Geology (Latest Citations from the Aerospace Database)

The bibliography contains citations concerning the use of remote sensing in geological resource exploration. Technologies discussed include thermal, optical, photographic, and electronic imaging using ground-based, aerial, and satellite-borne devices. Analog and digital techniques to locate, classify, and assess geophysical features, structures, and resources are also covered. Application of remote sensing to petroleum and minerals exploration is treated in a separate bibliography. (Contains 50-250 citations and includes a subject term index and title list.)

BIBLIOGRAPHIES↗

Exploring Asteroid Interiors: The Deep Interior Mission Concept

Deep Interior is a mission to determine the geophysical properties of near-Earth objects, including the first volumetric image of the interior of an asteroid. Radio reflection tomography will image the 3D distribution of complex dielectric properties within the ~1 km rendezvous target and hence map structural, density or compositional variations. Laser altimetry and visible imaging will provide high-resolution surface topography. Smart surface pods culminating in blast experiments, imaged by the high frame rate camera and scanned by lidar, will characterize active mechanical behavior and structure of surface materials, expose unweathered surface for NIR analysis, and may enable some characterization of bulk seismic response. Multiple flybys en route to this target will characterize a diversity of asteroids, probing their interiors with non-tomographic radar reflectance experiments. Deep Interior is a natural follow-up to the NEARShoemaker mission and will provide essential guidance for future in situ asteroid and comet exploration. While our goal is to learn the interior geology of small bodies and how their surfaces behave, the resulting science will enable pragmatic technologies required of hazard mitigation and resource utilization.

Asphaug, E.↗

Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference Over Snow-Covered Terrain in High Mountain Asia

Snow is an important component of the terrestrial freshwater budget in high mountainAsia (HMA) and contributes to the runoff in Himalayan rivers through snowmelt. Despitethe importance of snow in HMA, considerable spatiotemporal uncertainty exists across the different estimates of snow water equivalent for this region. In order to better estimate snow water equivalent, radiative transfer models are often used in conjunction with microwave brightness temperature measurements. In this study, the efficacy of support vector machines (SVMs), a machine learning technique, to predict passive microwave brightness temperature spectral difference (1Tb) as a function of geophysical variables (snow water equivalent, snow depth, snow temperature, and snow density) is explored through a sensitivity analysis. The use of machine learning (as opposed to radiative transfer models) is a relatively new and novel approach for improving snow water equivalent estimates. The Noah-MP land surface model within the NASALand Information System framework is used to simulate the hydrologic cycle over HMA and model geophysical variables that are then used for SVM training. The SVMsserve as a nonlinear map between the geophysical space (modeled in Noah-MP) andthe observation space (1Tb as measured by the radiometer). Advanced MicrowaveScanning Radiometer-Earth Observing System measured passive microwave brightness temperatures over snow-covered locations in the HMA region are used as training data during the SVM training phase. Sensitivity of well-trained SVMs to each Noah-MP modeled state variable is assessed by computing normalized sensitivity coefficients. Sensitivity analysis results generally conform with the known first-order physics. Input states that increase volume scattering of microwave radiation, such as snow density and snow water equivalent, exhibit a plurality of positive normalized sensitivity coefficients. In general, snow temperature was the most sensitive input to the SVM predictions. The sensitivity of each state is location and time dependent. The signs of normalized sensitivity coefficients that indicate physical irrationality are ascribed to significant cross-correlation between Noah-MP simulated states and decreased SVM prediction capability at specific locations due to insufficient training data. SVM prediction pitfalls do exist that serve to highlight the limitations of this particular machine learning algorithm.

high mountain Asia↗

The Antarctic Search for Meteorites: A Model for Deep Space Exploration

In an era of shrinking buying power and reduced flight opportunities, NASA must extract the greatest possible value from all sources of insight into the future of human space exploration. Antarctica is one such source. The history of Antarctic exploration has many political and technical parallels with the development of space, and Antarctica's remoteness and harsh climate make it an excellent proxy for space (e.g., [1,2]). Links between exploration of space and of the Antarctic date back to the International Geophysical Year of 1957-1958, which saw both the launch of Sputnik 1 and the establishment of a station at the South Pole. The Antarctic Search for Meteorites (ANSMET) is an annual expedition to the south polar plateau to collect meteorites. Although its intent is not to simulate a space mission, the handful of astronauts who have participated in ANSMET agree that it is very similar to a long-duration space flight. Independently, NASA and other space agencies have simulated deep space exploration missions in "analog" activities at remote field sites on Earth (e.g., [3]). These include NASA Extreme Environment Mission Operations (NEEMO) [4,5], Desert Research And Technology Studies (Desert RATS) [6,7], and the Pavilion Lake Research Project (PLRP or simply Pavilion Lake) [8]. This report focuses on NEEMO, Desert RATS, and PLRP because of the author's firsthand experience with them. Other noteworthy analogs, such as the arctic Haughton Mars Project and the European Space Agency's underground Cooperative Adventure for Valuing and Exercising human behavior and performance Skills (CAVES), are not treated here. NASA analogs often include fully staffed control centers, astronauts serving as crew, and realistic mission timelines lasting one to two weeks. Analogs have provided key insights into system architectures and operational concepts for the future human exploration of deep space. They have pioneered techniques for human communication with significant speed-of-light delays, for conducting spacewalks on natural objects with negligible surface gravity, and for empowering exploration crews to work with reduced dependence on a ground control center. They have field-tested dozens of emerging technologies including spacewalking tools and full-scale prototype vehicles and habitats. They have provided valuable experience for astronauts preparing for their first space flight, and for flown crewmembers who will take command roles on later flights. Some analogs, especially PLRP, have connected observers in the field with science teams in remotely located control centers to produce high-quality, publishable scientific results. The analogs have accomplished all of this at a tiny fraction of the cost of an actual space flight. This report treats ANSMET as space flight analog. The chapter following this introduction describes ANSMET in depth. The report then presents data on logistics and crew considerations that may be useful for developers of future human space exploration missions. It offers detailed comparisons between ANSMET and past, present, and future space flights on the Space Shuttle, the International Space Station (ISS), and a proposed Mars mission. Those comparisons are intended to complement the work of Eppler [2], who compares ANSMET to the Apollo moon flights. This report also compares ANSMET with the Desert RATS, NEEMO, and PLRP analogs. It then presents observations and makes recommendations related to ANSMET's value as a simulated space mission. The report ends with a short conclusion. The remainder of this introductory chapter provides background material to help readers interpret the rest of the report. It gives brief overviews of Space Shuttle and ISS missions along with information on a notional future human flight to Mars. It also presents the general features of three of NASA's space flight "analog" projects. With those points of reference in place, the chapter concludes with an overview of ANSMET.

Love, Stanley G.↗

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗

The use of radar and LANDSAT data for mineral and petroleum exploration in the Los Andes region, Venezuela

A geological study of a 27,500 sq km area in the Los Andes region of northwestern Venezuela was performed which employed both X-band radar mosaics and computer processed Landsat images. The 3.12 cm wavelength radar data were collected with horizontal-horizontal polarization and 10 meter spatial resolution by an Aeroservices SAR system at an altitude of 12,000 meters. The radar images increased the number of observable suspected fractures by 27 percent over what could be mapped by LANDSAT alone, owing mostly to the cloud cover penetration capabilities of radar. The approximate eight fold greater spatial resolution of the radar images made possible the identification of shorter, narrower fractures than could be detected with LANDSAT data alone, resulting in the discovery of a low relief anticline that could not be observed in LANDSAT data. Exploration targets for petroleum, copper, and uranium were identified for further geophysical work.

Vincent, R. K.↗

CLAES Product Improvement by use of GSFC Data Assimilation System

Recent development in chemistry transport models (CTM) and in data assimilation systems (DAS) indicate impressive predictive capability for the movement of airparcels and the chemistry that goes on within these. This project was aimed at exploring the use of this capability to achieve improved retrieval of geophysical parameters from remote sensing data. The specific goal was to improve retrieval of the CLAES CH4 data obtained during the active north high latitude dynamics event of 18 to 25 February 1992. The model capabilities would be used: (1) rather than climatology to improve on the first guess and the a-priori fields, and (2) to provide horizontal gradients to include in the retrieval forward model. The retrieval would be implemented with the first forward DAS prediction. The results would feed back to the DAS and a second DAS prediction for first guess, a-priori and gradients would feed to the retrieval. The process would repeat to convergence and then proceed to the next day.

Kumer, J. B.↗

Continuous monitoring of the lunar or Martian subsurface using on-board pattern recognition and neural processing of Rover geophysical data

The ultimate goal is to create an extraterrestrial unmanned system for subsurface mapping and exploration. Neural networks are to be used to recognize anomalies in the profiles that correspond to potentially exploitable subsurface features. The ground penetrating radar (GPR) techniques are likewise identical. Hence, the preliminary research focus on GPR systems will be directly applicable to seismic systems once such systems can be designed for continuous operation. The original GPR profile may be very complex due to electrical behavior of the background, targets, and antennas, much as the seismic record is made complex by multiple reflections, ghosting, and ringing. Because the format of the GPR data is similar to the format of seismic data, seismic processing software may be applied to GPR data to help enhance the data. A neural network may then be trained to more accurately identify anomalies from the processed record than from the original record.

Mcgill, J. W.↗

Mars Radar Observations with the Goldstone Solar System Radar

The Goldstone Solar System Radar (GSSR) has successfully collected radar echo data from Mars over the past 30 years. As such, the GSSR has played a role as a specific mission element within Mars exploration. The older data provided local elevation information for Mars, along with radar scattering information with global resolution. Since the upgrade to the 70-m Deep Space Network (DSN) antenna at Goldstone completed in 1986, Mars data has been collected during all but the 1997 Mars opposition. Radar data, and non-imaging delay-Doppler data in particular, requires significant data processing to extract elevation, reflectivity and roughness of the reflecting surface. The spatial resolution of these experiments is typically some 20 km in longitude by some 150 km in latitude. The interpretation of these parameters while limited by the complexities of electromagnetic scattering, do provide information directly relevant to geophysical and geomorphic analyses of Mars. The usefulness of radar data for Mars exploration has been demonstrated in the past. Radar data were critical in assessing the Viking Lander 1 site as well as, more recently, the Pathfinder landing site. In general, radar data have not been available to the Mars exploration community at large. A project funded initially by the Mars Exploration Directorate Science Office at the Jet Propulsion Laboratory (JPL), and later funded by NASA's Mars Data Analysis Program has reprocessed to a common format a decade's worth of raw GSSR Mars delay-Doppler data in aid of landing site characterization for the Mars Program. These data will soon be submitted to the Planetary Data System (PDS). The radar data used were obtained between 1988 and 1995 by the GSSR, and comprise some 63 delay-Doppler radar tracks. Of these, 15 have yet to be recovered from old 9-track tapes, and some of the data may be permanently lost.

Haldemann, A. F. C.↗

Mars exploration planning

Mars exploration planning is discussed which is based on three scientific objectives: to understand Mars' geologic and geophysical evolution; to understand the present state and past evolution of Martian climate, and to determine the state of present biological activity and past life. The plan assumes a 25-year planning horizon, from 1995-2020, and includes both broad-scale and local exploration capabilities.

Eppler, Dean B.↗

Basin and Range Investigation for Developing Geothermal Energy: Exploration Data

This data package includes exploration material from the Basin & Range Investigation for Developing Geothermal Energy [in Hidden Systems] project (BRIDGE), which is part of a broader initiative to advance the exploration of hidden geothermal resources in the Basin & Range Province of the western U.S. Data modalities include a helicopter-borne time-domain electromagnetic survey, magnetotellurics, 2-meter temperature measurements, ground-based gravity and legacy aeromagnetic surveys, geochemistry, geologic mapping, LiDAR analysis, 3D models, associated geospatial data, and a bibliography of existing data and references utilized in prospect characterization and conceptual modeling. Key files are in CSV, Geosoft, and Geotools formats. Please refer to READMEs for dataset-specific information. Where applicable, acquisition data and inversion models for a particular prospect or area of interest are organized separately. This BRIDGE data package is the product of a collaboration led by Sandia National Laboratories with partners from Geologica Geothermal Group, Inc., the U.S. Navy Geothermal Program Office, and consultants Steven Sewell (Australis Geoscience Ltd) and William Cumming (Cumming Geoscience). The project's areas of interest (AOIs) are based off priority areas of interest in the southwestern portion of the Nevada Play Fairway map, distribution across tectonic provinces, accessibility, and the project team's extensive experience in the region. AOIs cover about a dozen basins that include unexplored prospects, partially explored prospects, and some developed analogue resources that provide validation cases. Many unexplored and partially explored prospects are on U.S. Department of Defense (DoD) land, though adjacent lands are included as well.

15 GEOTHERMAL ENERGY↗

The SMART Cables Initiative for Ocean and Geophysical Observing [Slides]

SMART Cables are becoming a reality, and have the potential to revolutionize submarine oceanographic and geophysical sensing. Pilot / demonstration projects are underway to test the technology and explore the feasibility of incorporating both in-repeater standardized sensor packets but also ancillary sensor types on external, branching nodes. The projects currently in planning will set the standard and influence the norms for the future of SMART systems. The interest of all potential stakeholders and users, and input as to needs and concerns, is welcomed as testing proceeds.

54 ENVIRONMENTAL SCIENCES↗

The EUV flux inferred from AE-C He/+/ abundances

The ionization rate of helium in the thermosphere is inferred from He(+) abundances determined by instrumentation on the Atmosphere Explorer-C satellite. The inferred ionization rate is independent of the particular geophysical parameters of the thermosphere for solar zenith angles less than 80 deg and altitudes between 280 and 360 km. The ionization rate is consistent with a value calculated from the EUV flux of Hinteregger (1976) below 504 A.

Oppenheimer, M.↗

The Mark III Hypercube-Ensemble Computers

Mark III Hypercube concept applied in development of series of increasingly powerful computers. Processor of each node of Mark III Hypercube ensemble is specialized computer containing three subprocessors and shared main memory. Solves problem quickly by simultaneously processing part of problem at each such node and passing combined results to host computer. Disciplines benefitting from speed and memory capacity include astrophysics, geophysics, chemistry, weather, high-energy physics, applied mechanics, image processing, oil exploration, aircraft design, and microcircuit design.

Peterson, John C.↗

NASA today, and a vision for tomorrow

Under the administration of Dan Goldin's leadership, NASA is reinventing itself. In the process, the agency is also searching for a vision to define its role, both as a US Government agency and as a leading force in humanity's exploration of space. An adaption of Goldin's speech to the American Geophysical Union on 26 May 1994 in which he proposes one possible unifying vision is presented.

Goldin, Daniel S.↗

DOE Award No.: DE-FE0023919 Phase 4 Scientific/Technical Report

This is the Phase 4 Report for the ‘Deepwater Methane Hydrate Characterization and Scientific Assessment or Genesis of Methane Hydrates in the Gulf of Mexico (GOM2)’ research project (DOE Award No. DE-FE0023919). The report summarizes activities from October 1, 2019 to September 30, 2020. The project is led by the University of Texas at Austin (UT). The project objective is to gain insight into the nature, formation, occurrence and physical properties of methane hydrate-bearing sediments for the purpose of methane hydrate resource appraisal through the planning and execution of drilling, coring, logging, testing and analytical activities that assess the geologic occurrence, regional context, and characteristics of marine methane hydrate deposits in the Gulf of Mexico outer continental shelf (OCS). We published a dedicated American Association of Petroleum Geologists Bulletin volume describing initial results from the UT-GOM2-1 expedition in Sept. 2020. This is part 1 of a multi-volume commitment by AAPG to this project. We further confirmed that the natural gas in hydrate at GC-955 was formed by primary microbial processes (>76.1 %). The in-situ effective permeability hydrate-bearing sandy silts at the GC-955 reservoir ranges from 0.1 md (1.0×10-16 m2) to 2.4 md (2.4×10-15m2) in cores with 83% to 93% hydrate saturation. The intrinsic permeability (the single phase permeability) is estimated from reconstituted samples to be ~12 md (1.2×10-14 m2) to ~41 md (4.1×10-14 m2). We used observation and models to interpret that the core degradation that is found in pressure cores is due to dissociation of the methane hydrate in the outer circumference of the core and dissolution of that methane into the fresh pore water that the core is stored with. We are designing approaches to minimize this core loss in the future. We spent an enormous amount of effort to further improve the ability of the pressure coring tool (the PCTB) to pressure seal correctly. We completed upgrading the upper section of the PCTB to address poor pressure. We successful tested the modifications at Geotek’s test facility in Salt Lake City (Bench Test II). We completed a Land Test of the PCTB at the Schlumberger Cameron Test and Training Facility (CTTF). The tool did not seal in 6 out of 7 tests and we clearly demonstrated that cuttings were wedging in the ball valve assembly, keeping the ball valve from sealing. We reproduced the failure mechanism observed during the land test at Salt Lake City and confirmed the sensitivity of the ball valve assembly to grit. Geotek designed and tested 9 modifications to address this issue and the PCTB is now 100% successfully sealing in the presence of grit. Our science expedition is scheduled for spring 2022 and we are fully focused on preparing for this. UT and Ohio State completed a Shallow Hazard Assessment report for each proposed UT-GOM2-2 drilling location, pursuant to 30 CFR 250.214(f) and 250.244 (f). The Shallow Hazard Reports will accompany the UT-GOM2-2 Exploration Plan that is submitted to BOEM, and completes the geological and geophysical analysis for UT-GOM2-2 permitting efforts. We updated the UT-GOM2-2 Operations Plan (Version 1). We completed the UT-GOM2-2 Science and Sample Distribution Plan (Version 1). We evaluated the scope, budget, and schedule that would result from using a commercial vessel. We developed detailed drilling schedule, mud volume, and resource estimates. We developed a vessel specification document and a well plan, and sent these documents to prospective vessel contractors.

03 NATURAL GAS↗