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At least 181 records · Page 10

Software Analysis of New Space Gravity Data for Geophysics and Climate Research

Both the Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellites are returning rich data for the study of the solid earth, the oceans, and the climate. Current software analysis tools do not provide researchers with the ease and flexibility required to make full use of this data. We evaluate the capabilities and shortcomings of existing software tools including Mathematica, the GOCE User Toolbox, the ICGEM's (International Center for Global Earth Models) web server, and Tesseroids. Using existing tools as necessary, we design and implement software with the capability to produce gridded data and publication quality renderings from raw gravity data. The straight forward software interface marks an improvement over previously existing tools and makes new space gravity data more useful to researchers. Using the software we calculate Bouguer anomalies of the gravity tensor's vertical component in the Gulf of Mexico, Antarctica, and the 2010 Maule earthquake region. These maps identify promising areas of future research.

Gravity Recovery and Climate Experiment (GRACE)↗

Ensemble Kalman inversion of induced polarization data

SUMMARY This paper explores the applicability of ensemble Kalman inversion (EKI) with level-set parametrization for solving geophysical inverse problems. In particular, we focus on its extension to induced polarization (IP) data with uncertainty quantification. IP data may provide rich information on characteristics of geological materials due to its sensitivity to characteristics of the pore–grain interface. In many IP studies, different geological units are juxtaposed and the goal is to delineate these units and obtain estimates of unit properties with uncertainty bounds. Conventional inversion of IP data does not resolve well sharp interfaces and tends to reduce and smooth resistivity variations, while not readily providing uncertainty estimates. Recently, it has been shown for DC resistivity that EKI is an efficient solver for inverse problems which provides uncertainty quantification, and its combination with level set parametrization can delineate arbitrary interfaces well. In this contribution, we demonstrate the extension of EKI to IP data using a sequential approach, where the mean field obtained from DC resistivity inversion is used as input for a separate phase angle inversion. We illustrate our workflow using a series of synthetic and field examples. Variations with uncertainty bounds in both DC resistivity and phase angles are recovered by EKI, which provides useful information for hydrogeological site characterization. Although phase angles are less well-resolved than DC resistivity, partly due to their smaller range and higher percentage data errors, it complements DC resistivity for site characterization. Overall, EKI with level set parametrization provides a practical approach forward for efficient hydrogeophysical imaging under uncertainty.

Geochemistry & Geophysics↗

Sensitivity Studies for Space-Based Global Measurements of Atmospheric Carbon Dioxide

Carbon dioxide (CO2) is well known as the primary forcing agent of global warming. Although the climate forcing due to CO2 is well known, the sources and sinks of CO2 are not well understood. Currently the lack of global atmospheric CO2 observations limits our ability to diagnose the global carbon budget (e.g., finding the so-called "missing sink") and thus limits our ability to understand past climate change and predict future climate response. Space-based techniques are being developed to make high-resolution and high-precision global column CO2 measurements. One of the proposed techniques utilizes the passive remote sensing of Earth's reflected solar radiation at the weaker vibration-rotation band of CO2 in the near infrared (approx. 1.57 micron). We use a line-by-line radiative transfer model to explore the potential of this method. Results of sensitivity studies for CO2 concentration variation and geophysical conditions (i.e., atmospheric temperature, surface reflectivity, solar zenith angle, aerosol, and cirrus cloud) will be presented. We will also present sensitivity results for an O2 A-band (approx. 0.76 micron) sensor that will be needed along with CO2 to make surface pressure and cloud height measurements.

Mao, Jian-Ping↗

Efficient Flowline Simulations of Ice Shelf-Ocean Interactions: Sensitivity Studies with a Fully Coupled Model

Thermodynamic flowline and plume models for the ice shelf-ocean system simplify the ice and ocean dynamics sufficiently to allow extensive exploration of parameters affecting ice-sheet stability while including key physical processes. Comparison between geophysically and laboratory-based treatments of ice-ocean interface thermodynamics shows reasonable agreement between calculated melt rates, except where steep basal slopes and relatively high ocean temperatures are present. Results are especially sensitive to the poorly known drag coefficient, highlighting the need for additional field experiments to constrain its value. These experiments also suggest that if the ice-ocean interface near the grounding line is steeper than some threshold, further steepening of the slope may drive higher entrainment that limits buoyancy, slowing the plume and reducing melting; if confirmed, this will provide a stabilizing feedback on ice sheets under some circumstances.

polar oceanography↗

The Aerosol Component of the ACCP Designated Observable Study

The 2017 Earth Science Decadal Survey (DS) recommended science and applications priorities to be pursued by NASA during the 2017-2027 timeframe. Aerosols (A) and clouds, convection, and precipitation (CCP) were identified as essential “designated observables” requiring additional capabilities beyond those planned in the current Program of Record. The DS recommended NASA develop a medium-to-large mission to address these observables, which would represent foundational elements of the future global observing system. In response, NASA initiated a 3-year study, to conclude in 2021, of a combined ACCP architecture, including identification of science and application goals and objectives, desired geophysical variables, and observing system capabilities. The goal of the study is to develop and explore a variety of concepts and develop several recommendations. ACCP science objectives include improving characterization of the distribution and properties of aerosols, the direct and indirect impacts of aerosol on the radiation budget, and improving understanding of aerosol processes related to air quality. The study is currently exploring satellite architecture concepts and suborbital measurements to provide desired observational capabilities, within the context of the planned international Earth observation program. This presentation will summarize ACCP science objectives and the potential suite of aerosol-oriented observing system capabilities.

David M Winker↗

Mission Planning for Trident: Discovery proposal to Neptune’s moon, Triton

Trident was one of the four Discovery-class Step-1 mission proposals selected by NASA in 2020 for further development and study; however, in 2021, the Step-2 proposal was not down-selected to transition into the next phase of mission development, i.e., a mission for flight.Neptune’s largest moon, Triton, was the primary focus of study for Trident. Triton’s physical and orbital characteristics make it a unique planetary target for scientific exploration, providing opportunities for investigations in a wide variety of scientific fields, including geomorphological, atmospheric, geophysical, magnetospheric, and ionospheric studies. The science objectives of the Trident mission encompassed an in-depth interior-to-exterior set of objectives, focused on multiple outstanding questions resulting from the 1989 encounter of Voyager 2, and subsequent analysis.Ball Aerospace Corp. was tasked with building the Trident spacecraft, with JPL responsible for providing Engineering Support (Mission Design & Navigation, Mission Planning, Flight Operations, Ground Data Systems, Systems Engineering) and leading Project Management. The observatory would carry a wide-ranging suite of scientific instruments onboard, including an Infrared Spectrometer (IRS) and Narrow Angle Camera (NAC) to be provided by Ball Aerospace Corp., a Wide Angle Camera (WAC) from JPL, a Magnetometer from UCLA, a contributed Plasma Science Suite from IRF (Sweden), and a contributed Radio Science instrument from ASI (Italy). All of these instruments would be used to collect unique datasets during the Triton encounter. Trident would have taken advantage of an ~13-yr, nearly-ballistic trajectory to Triton, utilizing a timely Jupiter Gravity Assist, to execute a 10-day long encounter in the Neptunian system. Launch was planned for October 2025, with Triton arrival scheduled for December 2038. The timeline for this mission would have been sub-divided into seven major phases: Launch, Commissioning, Inner Planet Cruise, Outer Planet Cruise, Approach, Encounter, and Science Data Return. Multiple planetary flybys were planned to be performed during the cruise, including three Earth flybys and one Venus flyby in the Inner Planet Cruise phase, and one Jupiter flyby in the Outer Planet Cruise phase. Along with conventional (Range and Doppler) tracking data, Delta-DOR and Optical Navigation data were also to be acquired to assist with spacecraft navigation during the Approach and Encounter phases. A 3 meter X-Band High Gain Antenna would allow playback of all science data at 1 kbps within 1 year after the Triton Encounter. The Mission Planning element on Trident encompassed and informed multiple aspects of this proposal, ranging from science observation planning during the Triton Encounter phase, to generation of activity timelines for all mission phases; performing ground coverage analysis for science observations to be acquired by all instruments and tracing them to science requirements; evaluation of spacecraft resources including data volume stored onboard, power/energy consumption, telecom (commanding/telemetry) requirements, and overall, working at the interface of science and engineering teams on the mission. All of these functions that were performed by the Mission Planning team on this proposal are discussed in this paper.

Prockter, Louise↗

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

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale that has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify highvalue data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies.

58 GEOSCIENCES↗

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

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from 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. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗

Apollo 17 Lunar Sounder Data provide Insight into Aitken Crater's Subsurface Structure

In preparation for the forthcoming avalanche of data from Lunar Reconnaissance Orbiter (LRO), we conducted a pilot study to demonstrate integration of multiple geophysical data sets. We applied methods of data integration that are used by the commercial mineral exploration industry to enhance the value of historical data sets and to provide a roadmap for future efforts.

Cooper, Bonnie L.↗

Remote sensing of ferric iron minerals as guides for gold exploration

The relationship between the surficial iron mineralogy and economic mineralization is investigated, using data from an airborne imaging spectrometer (the 63-channel Geophysical and Environmental Research Imaging Spectrometer) to map the distribution of iron minerals in the Cripple Creek mining district in Colorado. The airborne image data were coregistered with the field map data for the distribution of iron oxides in the district, in a geographic information computer system, in order to compare their information content. It is shown that the remote imagery was able to uniquely identify the mineral hematite, a mixture of goethite/jarosite, and a mixture of hematite/goethite.

Taranik, Dan L.↗

Stochastic Inversion of Gaussian Random Media Using Transverse Coherence Functions for Reflected Waves: Theory and Method

The transverse coherence functions (TCFs) of phase and amplitude fluctuations of a seismic wave are powerful to estimate the spatial distribution, length scales, and strength of random heterogeneities. However, TCFs have been formulated for transmitted waves only, not for reflected waves. In this paper, we derive reflection TCFs for Gaussian random media. Furthermore, we propose to invert for Gaussian random media using the reflection TCFs based on the grid search. We validate the new reflection TCF formulas using 2D finite-difference numerical experiments. The numerical example also illustrates the feasibility and efficiency of the inversion. The stochastic inversion using reflected waves can be used in both exploration and global seismology.

58 GEOSCIENCES↗

Salt Diapir‐Driven Recycling of Gas Hydrate

Abstract By harnessing both hypothetical, synthetic basin and gas hydrate (GH) system models and real‐world models of well‐studied salt diapir‐associated GH sites at Green Canyon (Gulf of Mexico) and Blake Ridge (U.S. Atlantic coast), we propose and demonstrate salt movement (and in particular, diapirism) to be a new mechanism for the recycling of marine GH. At Green Canyon, for example, we show that by considering this newly proposed diapir‐driven recycling mechanism in conjunction with previously proposed lithological control on sandy‐reservoir‐hosted hydrate at the base of the GH stability zone (BGHSZ; ∼bottom‐simulating reflector, BSR), modeled GH saturations match drilling data. Overall, salt diapir movement‐induced GH recycling provides a temperature‐driven mechanism by which GH saturations at the BGHSZ may reach >90 vol. % and by which GH volumes near and free gas volumes beneath the BGHSZ may be increased significantly through time. Interestingly, comparison of salt diapir‐driven recycling and sediment burial‐driven recycling scenarios suggests notably higher rates of recycling via diapir‐driven versus burial‐driven processes. Our results suggest that GH and associated free gas accumulations above salt diapir crests represent particularly attractive targets for unconventional and conventional hydrocarbon resource exploration and for scientific and academic drilling expeditions aimed at exploiting GH systems. Salt basins containing GH systems—including passive margin basins of the Gulf of Mexico, southeastern Brazil, and southwestern Africa—are therefore compelling localities for studying salt‐driven GH recycling and for salt diapir‐associated natural gas exploration.

58 GEOSCIENCES↗

The International Lunar Network (ILN) Anchor Nodes Mission Update

NASA s Science Mission Directorate (SMD) established the Lunar Quest Program (LQP) to accomplish lunar science objectives embodied in the National Academies report The Scientific Context for Exploration of the Moon (2007) and the NASA Advisory Council-sponsored Workshop on Science Associated with the Lunar Exploration Architecture (2007). A major element of LQP's lunar flight projects is the International Lunar Network (ILN), a network of small geophysical nodes on the lunar surface. NASA plans to provide the first two stations around 2014 and a second pair in the 2016-2017 timeframe. International involvement to provide additional stations will build up the network so that 8-10 nodes could be simultaneously operating. This flight project complements SMD's initiatives to build a robust lunar science community through R&A lines and increases international participation in NASA's robotic exploration of the moon.

Cohen, B. A.↗

Radar, an optimum remote-sensing tool for detailed plate tectonic analysis and its application to hydrocarbon exploration (an example in Irian Jaya Indonesia)

Geometric, geomorphic, and structural information derived from the examination of radar imagery and combined with geologic and geophysical evidences strongly indicates that Salawati Island was attached to the Irian Jaya mainland during the time of Miocene lower Pliocene reef development, and that it was separated in middle Pliocene to Pleistocene time, opening the Sele Strait rift zone. The island moved 17.5 km southwestward after an initial counterclockwise rotation of 13 deg. The rift zone is subsequent to the creation of the large left lateral Sorong fault zone that is part of the transitional area separating the westward-moving Pacific plate from the relatively stable Australian plate. The motion was triggered during a widespread magmatic intrusion of the Sorong fault zone, when the basalt infiltrated a right lateral fault system in the area of the present Sele Strait.

Froidevaux, C. M.↗

Machine Learning for Well Log Analysis in Uranium Mining

This project explores the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate well log analysis for uranium mining. Geophysical log data—spontaneous potential, resistivity, and gamma ray—were used to classify lithology, correlate well logs and identify roll front zonation patterns, which are critical for locating uranium ore bodies. Supervised ML algorithms such as eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Random Forest were trained to classify lithology with high accuracy. Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks were also used for role front zone identification. Moreover, a Fast Dynamic Time Warping (FastDTW) algorithm was employed for well log correlation. Additionally, sample lag was addressed using dynamic programming. Results demonstrate the potential of AI and ML to streamline well log analysis and enhance uranium exploration workflows.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Seismic constraints from a Mars impact experiment using InSight and Perseverance

NASA’s InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission has operated a sophisticated suite of seismology and geophysics instruments on the surface of Mars since its arrival in 2018. On 18 February 2021, we attempted to detect the seismic and acoustic waves produced by the entry, descent and landing of the Perseverance rover using the sensors onboard the InSight lander. Similar observations have been made on Earth using data from both crewed and uncrewed spacecraft, and on the Moon during the Apollo era, but never before on Mars or another planet. This was the only seismic event to occur on Mars since InSight began operations that had an a priori known and independently constrained timing and location. It therefore had the potential to be used as a calibration for other marsquakes recorded by InSight. Here we report that no signal from Perseverance’s entry, descent and landing is identifiable in the InSight data. Nonetheless, measurements made during the landing window enable us to place constraints on the distance–amplitude relationships used to predict the amplitude of seismic waves produced by planetary impacts and place in situ constraints on Martian impact seismic efficiency (the fraction of the impactor kinetic energy converted into seismic energy).

79 ASTRONOMY AND ASTROPHYSICS↗

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↗

Venus Mobile Explorer with RPS for Active Cooling: A Feasibility Study

We present our findings from a study to evaluate the feasibility of a radioisotope power system (RPS) combined with active cooling to enable a long-duration Venus surface mission. On-board power with active cooling technology featured prominently in both the National Research Council's Decadal Survey and in the 2006 NASA Solar System Exploration Roadmap as mission-enabling for the exploration of Venus. Power and cooling system options were reviewed and the most promising concepts modeled to develop an assessment tool for Venus mission planners considering a variety of future potential missions to Venus, including a Venus Mobile Explorer (either a balloon or rover concept), a long-lived Venus static lander, or a Venus Geophysical Network. The concepts modeled were based on the integration of General Purpose Heat Source (GPHS) modules with different types of Stirling cycle heat engines for power and cooling. Unlike prior investigations which reported on single point design concepts, this assessment tool allows the user to generate either a point design or parametric curves of approximate power and cooling system mass, power level, and number of GPHS modules needed for a "black box" payload housed in a spherical pressure vessel.

Leifer, Stephanie D.↗