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At least 793 records · Page 44

Discovering Hidden Geothermal Signatures using Unsupervised Machine Learning

Discovering hidden geothermal resources is a very challenging task. It requires the mining of large datasets, including various diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used Play Fairway Analysis (PFA) typically relies on subject-matter expertise to analyze site or regional data to estimate geothermal conditions and prospectivity. Here, we demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset of Southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. However, most of these systems are poorly characterized because of insufficient existing data and limited past explorative studies. This study aims to discover hidden patterns and relationships in the SWNM geothermal dataset to better understand regional hydrothermal conditions. This is achieved by applying an unsupervised machine learning algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden (latent) signatures characterizing datasets, (2) the optimal number of these signatures, (3) dominant data attributes associated with each signature, and (4) spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, geothermal attributes at 44 locations in SWNM. NMFk successfully finds data patterns and identifies the spatial associations of hydrothermal signatures with the four physiographic provinces in SWNM (Colorado Plateau, Volcanic Field, Basin and Range, and the Rio Grande rift). The algorithm identified up to 5 hydrothermal signatures in the SWNM datasets that differentiate between low- and medium-temperature hydrothermal systems in different provinces. Also, the algorithm identifies two medium-temperature hydrothermal systems in SWNM that require further exploration for geothermal resource development. Based on our analyses, 12 of the attributes are important to identify medium-temperature hydrothermal systems, and the remaining six attributes are critical to characterize low-temperature hydrothermal systems. Based on the obtained results, we identify potential physiographic provinces for further exploration to characterize them as geothermal resources. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored areas.

58 GEOSCIENCES↗

A bibliography of planetary geology and geophysics principal investigators and their associates, 1983 - 1984

A compilation is given of selected bibliographic data specifically relating to recent publications submitted by principle investigators and their associates, supported through NASA's Office of Space Science and Applications, Solar System Exploration Division, Planetary Geology and Geophysics Program. Topics include the solar system, asteroids, volcanoes, stratigraphy, remote sensing, and planetary craters.

Witbeck, N. E.↗

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects

Researchers at New Mexico Tech, Los Alamos National Laboratory (LANL), Sandia National Laboratory (SNL), and other collaborators are developing a methodology to improve characterization of stress in the subsurface by means of a model-based inversion of reservoir engineering data, time lapse seismic measurements, and microseismicity. Historically, various geophysical techniques have been used in efforts to understand the state of stress in the subsurface through direct and indirect imaging of stress sensitive features (faults and fractures) and observations of transient stress related observations (time variant elastic moduli and microseismicity). Standard direct and indirect techniques for seismic fault and fracture imaging suffer from detectability limits due to reliance on high data quality and multiplicity. Variations in effective elastic properties from inversion of high quality seismic (Vertical Seismic Profile (VSP)) data may be used to infer stress near the wellbore through integration with independent experimental characterization of the stress-velocity relationship. Given a sufficiently robust observation network, microseismic emissions may be inverted to characterize focal mechanisms which, together with supporting assumptions and constraints, inform estimates of in-situ stress. While each of these techniques contributes in part to the characterization of stress within limited spatial and temporal domains, no one method provides an unambiguous stress measurement or a predictive capability over a site scale spatial extent. Challenges associated with solution non-uniqueness, measurement ambiguity, and irregular sampling may be greatly minimized through combination of one or more of independent measurements within a common framework in which realistic geological, hydrodynamic, geomechanical, and seismological constituent process models may act as constraints.

02 PETROLEUM↗

Satellite Data Sets in the Polar Regions

We have generated about two decades of consistently derived geophysical parameters in the polar regions. The key parameters are sea ice concentration, surface temperature, albedo, and cloud cover statistics. Sea ice concentrations were derived from the Scanning Multichannel Microwave Radiometer (SMMR) data and the Special Scanning Cl Microwave Imager (SSM/I) data from several platforms using the enhanced Bootstrap Algorithm for the period 1978 through 1999. The new algorithm reduces the errors associated with spatial and temporal variations in the emissivity and surface temperatures of sea ice. Also, bad data at ocean/land interfaces are identified and deleted in an unsupervised manner. Surface ice temperature, albedo and cloud cover statistics are derived simultaneously from the Advanced Very High Resolution Radiometer (AVHRR) data from 1981 through 1999 and mapped at a higher resolution but the same format as the ice concentration data. The technique makes use these co-registered ice concentration maps to enable cloud masking to be done separately for open ocean, sea ice and land areas. The effect of inversion is minimized by taking into consideration the expected changes in the effect of inversion with altitude, especially in the Antarctic. A technique for ice type regional classification has also been developed using multichannel cluster analysis and a neural network. This provide a means to identify large areas of thin ice, first year ice, and older ice types. The data sets have been shown to be coherent with each other and provide a powerful tool for in depth studies of the currently changing Arctic and Antarctic environment.

Comiso, Josefino C.↗

Extracting Independent Local Oscillatory Geophysical Signals by Geodetic Tropospheric Delay

Zenith Tropospheric Delay (ZTD) due to water vapor derived from space geodetic techniques and numerical weather prediction simulated-reanalysis data exhibits non-linear and non-stationary properties akin to those in the crucial geophysical signals of interest to the research community. These time series, once decomposed into additive (and stochastic) components, have information about the long term global change (the trend) and other interpretable (quasi-) periodic components such as seasonal cycles and noise. Such stochastic component(s) could be a function that exhibits at most one extremum within a data span or a monotonic function within a certain temporal span. In this contribution, we examine the use of the combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis (ICA): the EEMD-ICA algorithm to extract the independent local oscillatory stochastic components in the tropospheric delay derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) over six geodetic sites (HartRAO, Hobart26, Wettzell, Gilcreek, Westford, and Tsukub32). The proposed methodology allows independent geophysical processes to be extracted and assessed. Analysis of the quality index of the Independent Components (ICs) derived for each cluster of local oscillatory components (also called the Intrinsic Mode Functions (IMFs)) for all the geodetic stations considered in the study demonstrate that they are strongly site dependent. Such strong dependency seems to suggest that the localized geophysical signals embedded in the ZTD over the geodetic sites are not correlated. Further, from the viewpoint of non-linear dynamical systems, four geophysical signals the Quasi-Biennial Oscillation (QBO) index derived from the NCEP/NCAR reanalysis, the Southern Oscillation Index (SOI) anomaly from NCEP, the SIDC monthly Sun Spot Number (SSN), and the Length of Day (LoD) are linked to the extracted signal components from ZTD. Results from the synchronization analysis show that ZTD and the geophysical signals exhibit (albeit subtle) site dependent phase synchronization index.

Botai, O. J.↗

Relaxation behavior in low-frequency complex conductivity of sands caused by bacterial growth and biofilm formation by Shewanella oneidensis under a high-salinity condition

Complex electrical conductivity is increasingly used to monitor subsurface processes associated with microbial activities because microbial cells mostly have surface charges and thus electrical double layers. Although highly saline environments are frequently encountered in coastal and marine sediments, there are limited data available on the complex conductivity associated with microbial activities under a high-salinity condition. Therefore, we have developed the spectral responses of complex conductivity of sand associated with bacterial growth and biofilm formation under a highly saline condition of approximately 1% salinity and approximately 2 S/m pore water conductivity with an emphasis on relaxation behavior. A column test is performed, in which the model bacteria Shewanella oneidensis MR-1 are stimulated for cell growth and biofilm formation in a sand pack, whereas the complex conductivity is monitored from 0.01 Hz to 10 kHz. The test results indicate that the real conductivity increases in the early stage due to the microbial metabolites and the increased surface conduction with cell growth but soon begin to decrease because of the reduction of charge passages due to bioclogging. However, the imaginary conductivity significantly increases with time, and clear bell-shaped relaxation behaviors are observed with the peak frequency of 0.1–1 Hz, associated with the double-layer polarization of cells and electrically conductive pili and biofilms. The Cole-Cole relaxation model appears to capture such relaxation behaviors well, and the modeling results indicate gradual increases in normalized chargeability and decreases in relaxation time during bacterial growth and biofilm formation in the highly saline condition. Comparison with previous literature confirms that the high-salinity condition further increases the normalized chargeability, whereas it suppresses the phase shift and thus the imaginary conductivity. Our results suggest that the complex conductivity can effectively capture microbial biomass formation in sands under a highly saline condition.

58 GEOSCIENCES↗

Seismic Survey 2016 Data at Crescent Valley, Nevada

In September 2016, 989 vertical-component seismic instruments were deployed for 75 hours at the Crescent Valley greenfield geothermal play area in Nevada. Data were recorded 12/9/16 - 12/15/16. Data are stored in individual files in one-minute increments in SEGD formats. See the metadata in Crescent Valley Station Locations.sp1, Crescent Valley Observer Logs.xls, and the attached Metadata link for details about the seismic station locations, seismic data logger specifications, instrumentation specifications, descriptions of data, a fracture finding summary, and the final report for the 2016 seismic survey done in Crescent Valley, Nevada. Note that no discrete events were identified, and a 1750m x 2250m x 300m PSET volume of acoustic energy was delivered.

15 GEOTHERMAL ENERGY↗

Narrow-Band Least-Squares Infrasound Array Processing

Infrasound data from arrays can be used to detect, locate, and quantify a variety of natural and anthropogenic sources from local to remote distances. However, many array processing methods use a single broad frequency range to process the data, which can lead to signals of interest being missed due to the choice of frequency limits or simultaneous clutter sources. In this work, we introduce a new open-source Python code that processes infrasound array data in multiple sequential narrow frequency bands using the least-squares approach. We test our algorithm on a few examples of natural sources (volcanic eruptions, mass movements, and bolides) for a variety of array configurations. Our method reduces the need to choose frequency limits for processing, which may result in missed signals, and it is parallelized to decrease the computational burden. Improvements of our narrow-band least-squares algorithm over broad-band least-squares processing include the ability to distinguish between multiple simultaneous sources if distinct in their frequency content (e.g., microbarom or surf vs. volcanic eruption), the ability to track changes in frequency content of a signal through time, and a decreased need to fine-tune frequency limits for processing. We incorporate a measure of planarity of the wavefield across the array (sigma tau, στ) as well as the ability to utilize the robust least trimmed squares algorithm to improve signal processing and insight into array performance. Our implementation allows for more detailed characterization of infrasound signals recorded at arrays that can improve monitoring and enhance research capabilities.

58 GEOSCIENCES↗

J&L #1 Well-Pennsylvania Oriskany Characterization

Dataset for this database page represents data from technical report "Computed Tomography Scanning and Geophysical Measurements of Appalachian Basin Core from the Jones and Laughlin #1 Well, Beaver County PA " Sharma, M; Paronish, T.; Mitchell, N.; Crandall, D.; Neubaum, J. Computed Tomography Scanning and Geophysical Measurements of Appalachian Basin Core from the Jones and Laughlin #1 Well, Beaver County PA; DOE.NETL-2023.3889; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2023; p 37.

Appalachian Basin↗

Evaluation of a Potential Groundwater Tracer Test in the Ringold Upper Mud Aquifer at the 100-H Area of the Hanford Site

This document presents an evaluation of a potential groundwater tracer test in the uppermost RUM (Ringold Formation member of Wooded Island – upper mud unit) aquifer in the 100-H Area of the Hanford Site. The results from field electrical resistivity tomography (ERT) investigations, numerical flow and transport (F&T) modeling, coupled ERT-F&T model simulations, and laboratory resin experiments provide the technical basis for evaluating tracer test scenarios that minimize impacts to the 100-HX pump and treat (HX P&T) operations, and maximize hydrologic data acquisitions including the use of advanced surface geophysical techniques for monitoring tracer transport.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Techniques in Doppler gravity inversion

The types of Doppler gravity data available for local as opposed to planetwide geophysical modeling are reviewed. Those gravity fields that are determined dynamically in orbit determination programs yield a smoothed representation of the local gravity field that may be used for quantitative modeling. An estimate of the difference between smoothed and true fields can be considered as a noise limitation in generating local gravity models. A nonlinear inversion for the geometry, depth, and density of the Mare Serenitatis mascon using an ellipsoidal model yielded a global least squares minimum in horizontal dimensions, depth, and thickness-density contrast product. It was subsequently found, by using a linear model, that there were an infinite number of solutions corresponding to various combinations of depth and lateral inhomogeneity. Linear modeling was performed by means of generalized inverse theory.

Phillips, R. J.↗

The forecasting center of Meudon, France

Main features of solar activity are described in relation to solar and geophysical forecasting. Spectroheliograms, radio and X-ray data, white light coronal observations, particles data, photospheric images, and photospheric magnetic fields are among the types of data used to identify the active centers and flares of the Sun. Forecasting and identification of geomagnetic activity is also discussed. The forecasting technique is described along with the types of users.

Simon, P.↗

Antenna pattern correction procedures for the Scanning Multichannel Microwave Radiometer /SMMR/

Procedures for correcting antenna temperature measurements and retrieving the true brightness temperatures are developed for the Scanning Multichannel Microwave Radiometer (SMMR) flown on the Seasat-A and Nimbus-G satellites. These procedures are necessary to meet the measurement accuracies required for deriving sea surface temperatures and wind speeds. It is shown that sidelobe contributions and polarization cross-coupling are major effects to be accounted for, in addition to some unique features of the SMMR instrument such as integration times and antenna scan characteristics. Methods are presented for data averaging and data reformatting, these are to be used with geophysical parameter retrieval algorithms.

Njoku, E. G.↗

Satellite-tracking and Earth dynamics research programs

The major focus for operations during this period was the preliminary MERIT Campaign and its intensive tracking of LAGEOS for polar motion and Earth rotation studies. The data acquired from LAGEOS were used for other geophysical investigations, including studies of crustal dynamics, and Earth and ocean tides, and for the general development of precision orbit determination. The network performed regular tracking of several other retroreflector satellites including GEOS-1, GEOS-3, BE-C, and Starlette for refined determinations of station coordinates and Earth's gravity field and for studies of solid Earth dynamics.

Source record↗

The magnetic field of the earth - Performance considerations for space-based observing systems

Basic problems inherent in carrying out observations of the earth magnetic field from space are reviewed. It is shown that while useful observations of the core and crustal fields are possible at the peak of the solar cycle, the greatest useful data volume is obtained during solar minimum. During the last three solar cycles, the proportion of data with a planetary disturbance index of less than 2 at solar maximum was in the range 0.4-0.8 in comparison with solar minimum. It is found that current state of the art orbit determination techniques should eliminate orbit error as a problem in gravitational field measurements from space. The spatial resolution obtained for crustal field anomalies during the major satellite observation programs of the last 30 years are compared in a table. The relationship between observing altitude and the spatial resolution of magnetic field structures is discussed. Reference is made to data obtained using the Magsat, the Polar Orbiting Geophysical Observatory (POGO), and instruments on board the Space Shuttle.

Webster, W. J., Jr.↗

Atlas of Absorption Lines from 0 to 17900 Cm (sup)-1

Plots of logarithm (base 10) of absorption line strength versus wavenumber from 0 to 17900/cm(sup)-1 are shown for the 28 atmospheric gases (H2O, CO2, O3, N2O, CO, CH4, O2, NO, SO2, NO2, NH3, HNO3, OH, HF, HCl, HBr, HI, ClO, OCS, H2CO, HOCl, N2, HCN, CH3Cl, H2O2, C2H2, C2H6, PH3), which appear in the 1986 Air Force Geophysics Laboratory high-resolution transmission molecular absorption data base (HITRAN) compilation, and for O(P-3), O-18 isotopic ozone, and HO2 from the 1984 JPL compilation in the 0- to 200/cm(sup)-1 region, and infrared solar CO lines at 4500 K. Also shown are plots of logarithm (base 10) of approximate infrared absorption cross sections of 11 heavy molecules versus wavenumber. The cross-section data cover 700 to 1800/cm(sup)-1 and are included as a separate data file in the 1986 HITRAN database.

Park, J. H.↗