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At least 199 records · Page 11

Geosat Data Assimilation with Application to the Eastern North Atlantic

An attempt is made to determine the three-dimensional ocean circulation from satellite altimeter measurements by assimilating Geosat sea surface height data into an eddy-resolving QuasiGeostrophic (QG) model of the eastern North Atlantic Ocean. Results are tested against independent information from hydrographic field observations and moored current meter data collected during the Geosat ERM. The comparison supports the concept of inferring aspects of the three-dimensional flow field from sea surface height observations by combining altimetric measurements with the dynamics of ocean circulation models. A Holland-type QG model with open boundaries is set up on a 2000 km X 2000 km domain of the eastern North Atlantic between 25 deg. and 45 deg. N, 32 deg. and 8 deg. W. By using a simple nudging technique, about two years of Geosat altimeter data are assimilated into the model every five days as space-time objective analyses on the model grid. The error information resulting from the analysis is used during the assimilation procedure to account for data uncertainties. Results show an intense eddy field, which in the surface layer interacts with a meandering Azores Front. Compared to Geosat, the model leads to smoothed fields that follow the observations. Model simulations are significantly correlated with hydrographic data from March 1988 and June 1989, both close to the surface and in the subsurface. Good agreement is also found between the model velocity fields and moored current meter data in the top two model layers. The agreement is visually weak in the bottom layer, although a coherence analysis reveals an agreement between the model simulation and current meter data over the full water column at periods exceeding 80 days.

Stammer, Detlef↗

Regolith Properties of Asteroid 21 Lutetia Constrained by Combined Data Sets of the MIRO and VIRTIS Instruments During the Rosetta Spacecraft Flyby

During the July 10, 2010 flyby of Asteroid 21 Lutetia by the Rosetta spacecraft, maps of surface and subsurface temperatures were derived from the VIRTIS and MIRO instruments respectively. Both data sets indicated a porous surface layer with an extremely low, lunar-like thermal inertia. However, comparisons of the VIRTIS-measured and MIRO-modelled surface temperatures revealed offsets of 10- 30 K, indicative of self-heating or "beaming" effects that were not taken into account in the MIRO thermal modeling. Inclusion of a model of hemispherical craters at all scales 1 cm and larger, covering 50% of the surface, removes most of the offsets in the VIRTIS, MIRO surface temperature determinations.

Rosetta spacecraft↗

Technical Report on Subsurface Monitoring of the Brady Hot Spring Geothermal Site, Nevada, based upon Full Waveform Inversion

Abilities to accurately characterize the subsurface in a geothermal setting is key to assess and support production. An important element of geothermal reservoir monitoring is also the ability to investigate fluid transport within fracture network. This report focuses on improving subsurface imaging and monitoring in geothermal settings using full waveform inversion based on the adjoint method and time-lapse imaging. To assess our method, we rely on a dense seismic dataset collected in 2016 at the Brady Hot Springs geothermal site in Nevada for the DOE-funded project Poroelastic Tomography by Adjoint Inverse Modeling of Data from Seismology, Geodesy, and Hydrology. This dataset captures subsurface changes across four stages of geothermal power plant operations, which involve varying rates of fluid injection and extraction. Two velocity models were previously derived from this dataset using different methods: one based on travel times and another on sweep interferometry. Our first step is to refine these models using adjoint tomography, which has been applied successfully at global and regional-scales but is less common at the reservoir-scale. Two approaches are then explored for time-lapse analysis: directly comparing refined tomographic models from different stages or backpropagating waveform differences relative to a baseline tomographic model. The main take away is that both approaches highlight similar reservoir behaviors, but the latter approach is more computationally effective in capturing small-scale changes in subsurface properties. For this work, we leverage the use of Salvus (www.mondaic.com), an end-to-end seismic imaging solution, relying on the spectral element method to compute forward and adjoint simulations, and developed by Mondaic Ltd. It includes integrated workflow management that handles waveform and metadata, launches simulations, computes waveform misfits and adjoint sources, and iterates for model updates by nonlinear optimization.

15 GEOTHERMAL ENERGY↗

Water Quality Monitor

An automated water quality monitoring system was developed by Langley Research Center to meet a need of the Environmental Protection Agency (EPA). Designed for unattended operation in water depths up to 100 feet, the system consists of a subsurface buoy anchored in the water, a surface control unit (SCU) and a hydrophone link for acoustic communication between buoy and SCU. Primary functional unit is the subsurface buoy. It incorporates 16 cells for water sampling, plus sensors for eight water quality measurements. Buoy contains all the electronic equipment needed for collecting and storing sensor data, including a microcomputer and a memory unit. Power for the electronics is supplied by a rechargeable nickel cadmium battery that is designed to operate for about two weeks. Through hydrophone link the subsurface buoy reports its data to the SCU, which relays it to land stations. Link allows two-way communications. If system encounters a problem, it automatically shuts down and sends alert signal. Sequence of commands sent via hydrophone link causes buoy to release from anchor and float to the surface for recovery.

Source record↗

Multipolarization radar images for geologic mapping and vegetation discrimination

NASA has developed an airborne SAR that simultaneously yields image data in four linear polarizations in L-band with 10-m resolution over a swath of about 10 km. Signal data are recorded both optically and digitally and annotated in each of the channels to facilitate completely automated digital correlation. Comparison of the relative intensities of the different polarizations furnishes discriminatory mapping information. Local intensity variations in like-polarization images result from topographic effects, while strong cross polarization responses denote the effects of vegetation cover and, in some cases, possible scattering from the subsurface. In each of the areas studied, multiple polarization data led to the discrimination and mapping of unique surface unit features.

Evans, D. L.↗

Potential of Radar Imaging and Sounding Methods in Mapping Heavily Eroded Impact Craters: Mapping Some Structural Elements of the Hico Crater, TX

Shuttle Radar Topography Mission (SRTM) and Ground Penetrating Radar (GPR) data collected over an area north of the town of Hico, central Texas, have been used to map disturbances in the surface topography and subsurface stratigraphy. The Radar topography results confirm the presence of multiple rings suggestive of an impact crater. Correlation between the orbital SRTM and on-the-ground GPR field data are affected by different biases related to variations in terrain and vegetation cover. Nevertheless, the correspondence of the two data sets supports the earlier conclusions that a complex, multiple ring impact structure is reflected in the topography of this area. The SRTM data reveal three previously unrecognized rings; with the outermost ring some 5-6 km in diameter. The crater appears to be significantly larger than the size (2.5 km diameter) previously inferred on the basis of aerial images. In addition, the GPR data suggest the presence of subsurface faulting that spatially coincides with the two inner rings of the crater. This suggests that the topographic rings are structurally controlled by faulting.

Heggy, E.↗

Long-Lasting Science Returns from the Apollo Heat Flow Experiments

The Apollo astronauts deployed geothermal heat flow instruments at landing sites 15 and 17 as part of the Apollo Lunar Surface Experiments Packages (ALSEP) in July 1971 and December 1972, respectively. These instruments continuously transmitted data to the Earth until September 1977. Four decades later, the data from the two Apollo sites remain the only set of in-situ heat flow measurements obtained on an extra-terrestrial body. Researchers continue to extract additional knowledge from this dataset by utilizing new analytical techniques and by synthesizing it with data from more recent lunar orbital missions such as the Lunar Reconnaissance Orbiter. In addition, lessons learned from the Apollo experiments help contemporary researchers in designing heat flow instruments for future missions to the Moon and other planetary bodies. For example, the data from both Apollo sites showed gradual warming trends in the subsurface from 1971 to 1977. The cause of this warming has been debated in recent years. It may have resulted from fluctuation in insolation associated with the 18.6-year-cycle precession of the Moon, or sudden changes in surface thermal environment/properties resulting from the installation of the instruments and the astronauts' activities. These types of reanalyses of the Apollo data have lead a panel of scientists to recommend that a heat flow probe carried on a future lunar mission reach 3 m into the subsurface, approx 0.6 m deeper than the depths reached by the Apollo 17 experiment. This presentation describes the authors current efforts for (1) restoring a part of the Apollo heat flow data that were left unprocessed by the original investigators and (2) designing a compact heat flow instrument for future robotic missions to the Moon. First, at the conclusion of the ALSEP program in 1977, heat flow data obtained at the two Apollo sites after December 1974 were left unprocessed and not properly archived through NASA. In the following decades, heat flow data from January 1975 through February 1976, as well as the metadata necessary for processing the data (the data reduction algorithm, instrument calibration data, etc.), were somehow lost. In 2010, we located 450 original master archival tapes of unprocessed data from all the ALSEP instruments for a period of April through June 1975 at the Washington National Records Center. We are currently extracting the heat flow data packets from these tapes and processing them. Second, on future lunar missions, heat flow probes will likely be deployed by a network of small robotic landers, as recommended by the latest Decadal Survey of the National Academy of Science. In such a scenario, the heat flow probe must be a compact system, and that precludes use of heavy excavation equipment such as a rotary drill for reaching the 3-m target depth. The new heat flow system under development uses a pneumatically driven penetrator. It utilizes a stem that winds out of a reel and pushes its conical tip into the regolith. Simultaneously, gas jets, emitted from the cone tip, loosen and blow away the soil. Lab experiments have demonstrated its effectiveness in lunar vacuum.

Nagihara, S.↗

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗

Prairie State Generating Company 2D Seismic Interpretation

The objectives of the Illinois Storage Corridor (ISC) project are to accelerate commercial deployment of carbon capture utilization and storage at two individual sites and receive approvals for Underground Injection Control (UIC) Class VI permits for construction at each site (ISC Project Narrative, 2020). As part of this project, and as part of the subsurface geologic characterization, two-dimensional (2D) seismic data was acquired at both sites. This report summarizes the findings from two phases of 2D acquisition and seismic interpretation at the Prairie State Generating Company site near Marissa, Illinois. The seismic data indicates the presence of three faults that completely transect the storage and confining units. The initial 2021 2D seismic acquisition revealed the presence of a feature two miles east of the Lively Grove #1 characterization well. The feature is a polyphase fault with a component of strike-slip motion, forming a small positive flower structure. The second phase of 2D seismic acquisition in 2022 constrained the maximum extent of the fault, indicating it has a relatively limited length. Other 2022 seismic lines revealed the presence of two other faults that transect the storage and confining units in the southwest and northeast portions of the 2D seismic acquisition area. The 2021 and 2022 2D seismic surveys have identified three specific locations within the project area that may have an elevated risk of out of zone CO 2 migration due to faulting. Further technical work will be needed to quantify this risk and determine how and if this risk will impact the placement of CO 2 injection wells across the project area.

01 COAL, LIGNITE, AND PEAT↗

Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management

This review synthesizes methods for measuring, modeling, and managing hydrologic connectivity, offering pathways to improve practices and address environmental challenges (e.g., climate change) and sustainability. As a key driver of water movement and nutrient cycling, hydrologic connectivity influences flood mitigation, water quality regulation, and biodiversity conservation. However, traditional field-based methods (e.g., dye tracing), indirect measurements (e.g., runoff analysis), and remote sensing techniques (e.g., InSAR) often struggle to capture the complexity of catchment-scale interactions. Similarly, modeling approaches—including process-based and percolation theory-based models, graph theory, and entropy-based metrics—face limitations in fully representing these interconnected processes. Both modeling and measurement techniques are constrained by inadequate spatial and temporal coverage, high data demands, computational complexity, and difficulties in representing subsurface connectivity. Subsequently, we critique current management practices that prioritize isolated variables (e.g., streamflow, sediment transport) over system-wide strategies and emphasize the need for adaptive, connectivity-based approaches in water resource planning and restoration. Moving forward, we highlight the importance of interdisciplinary collaboration, technological innovations (e.g., AI-driven modeling, real-time monitoring), and integrated frameworks to improve connectivity measurement, modeling, and adaptive management to restore fragmented hydrologic networks. This integrated approach sets the stage for transformative water resource management, fostering proactive policy development and stakeholder engagement.

Dwivedi, Dipankar↗

Ocean color spectrum calculations

The development is considered of procedures for measuring a number of subsurface oceanographic parameters using remotely sensed ocean color data. It is proposed that the first step in this effort should be the development of adequate theoretical models relating the desired oceanographic parameters to the upwelling radiances to be observed. A portion of a contributory theoretical model is shown to be described by a modified single scattering approach based upon a simple treatment of multiple scattering. The resulting quasi-single scattering model can be used to predict the upwelling distribution of spectral radiance emerging from the sea. The shape of the radiance spectrum predicted by this model for clear ocean water shows encouraging agreement with measurments made at the edge of the Sargasso Sea off Cape Hatteras.

Mccluney, W. R.↗

Ocean color spectrum calculations

There is obvious value in developing the means for measuring a number of subsurface oceanographic parameters using remotely sensed ocean color data. The first step in this effort should be the development of adequate theoretical models relating the desired oceanographic parameters to the upwelling radiances to be observed. A portion of a contributory theoretical model can be described by a modified single scattering approach based on a simple treatment of multiple scattering. The resulting quasisingle scattering model can be used to predict the upwelling distribution of spectral radiance emerging from the sea. The shape of the radiance spectrum predicted by this model for clear ocean water shows encouraging agreement with measurements made at the edge of the Sargasso Sea off Cape Hatteras.

Mccluney, W. R.↗

The gravity method and interpretive techniques for detecting vertical crustal movements

Observations of temporal variations of gravity can be used as an inexpensive and rapid means of detecting, monitoring, and studying crustal deformation associated with many active geological processes. Such observations can yield qualitative or semiquantitative information on elevation changes and, when combined with independent elevation data, can yield information about changes of the subsurface density field arising from both subsurface displacements and temporal variations of the density of materials in the subsurface. The effectiveness of gravity techniques in specific cases of crustal deformation depends on the configuration of the local gravity field, the physical processes involved in the deformation, and the accuracy with which temporal gravity variations can be measured.

Jachens, R. C.↗

Fiber Optic Thermal Health Monitoring of Aerospace Structures and Materials

A new technique is presented for thermographic detection of flaws in materials and structures by performing temperature measurements with fiber Bragg gratings. Individual optical fibers with multiple Bragg gratings employed as surface temperature sensors were bonded to the surfaces of structures with subsurface defects or thickness variations. Both during and following the application of a thermal heat flux to the surface, the individual Bragg grating sensors measured the temporal and spatial temperature variations. The investigated structures included a 10-ply composite specimen with subsurface delaminations of various sizes and depths. The data obtained from grating sensors were further analyzed with thermal modeling to reveal particular characteristics of the interested areas. These results were found to be consistent with those from conventional thermography techniques. Limitations of the technique were investigated using both experimental and numerical simulation techniques. Methods for performing in-situ structural health monitoring are discussed.

Wu, Meng-Chou↗

Preliminary Regional Analysis of the Kaguya Lunar Radar Sounder (LRS) Data through Eastern Mare Imbrium

The Lunar Radar Sounder (LRS) experiment on board the Kaguya spacecraft is observing the subsurface structure of the Moon, using ground-penetrating radar operating in the frequency range of 5 MHz [1]. Because LRS data provides in-formation about lunar features below the surface, it allows us to improve our understanding of the processes that formed the Moon, and the post-formation changes that have occurred (such as basin formation and volcanism). We look at a swath of preliminary LRS data, that spans from 7 to 72 N, and from 2 to 10 W, passing through the eastern portion of Mare Imbrium (Figure 1). Using software, designed for the mineral exploration industry, we produce a preliminary, coarse 3D model, showing the regional structure beneath the study area. Future research will involve smaller subsets of the data in regions of interest, where finer structures, such as those identified in [2], can be studied.

Cooper, B.L.↗

3-D Geological Modeling for Numerical Flow Simulation Studies of Gas Hydrate Reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

58 GEOSCIENCES↗

Lessons Learned from Assimilating Altimeter Data into a Coupled General Circulation Model with the GMAO Augmented Ensemble Kalman Filter

Satellite altimetry measurements have provided global, evenly distributed observations of the ocean surface since 1993. However, the difficulties introduced by the presence of model biases and the requirement that data assimilation systems extrapolate the sea surface height (SSH) information to the subsurface in order to estimate the temperature, salinity and currents make it difficult to optimally exploit these measurements. This talk investigates the potential of the altimetry data assimilation once the biases are accounted for with an ad hoc bias estimation scheme. Either steady-state or state-dependent multivariate background-error covariances from an ensemble of model integrations are used to address the problem of extrapolating the information to the sub-surface. The GMAO ocean data assimilation system applied to an ensemble of coupled model instances using the GEOS-5 AGCM coupled to MOM4 is used in the investigation. To model the background error covariances, the system relies on a hybrid ensemble approach in which a small number of dynamically evolved model trajectories is augmented on the one hand with past instances of the state vector along each trajectory and, on the other, with a steady state ensemble of error estimates from a time series of short-term model forecasts. A state-dependent adaptive error-covariance localization and inflation algorithm controls how the SSH information is extrapolated to the sub-surface. A two-step predictor corrector approach is used to assimilate future information. Independent (not-assimilated) temperature and salinity observations from Argo floats are used to validate the assimilation. A two-step projection method in which the system first calculates a SSH increment and then projects this increment vertically onto the temperature, salt and current fields is found to be most effective in reconstructing the sub-surface information. The performance of the system in reconstructing the sub-surface fields is particularly impressive for temperature, but not as satisfactory for salt.

Keppenne, Christian↗

GRAIL Refinements to Lunar Seismic Structure

Joint interpretation of disparate geophysical datasets helps to reduce drawbacks that can result from analyzing them individually. The Apollo seismic network was situated on the lunar nearside surface in a roughly equilateral triangle having sides approximately 1000 km long, with stations 12/14 nearly co‐located at one corner. Due to this limited geographical extent, near‐surface ray coverage from moonquakes is low, but increases with depth. In comparison, gravity surveys and their resulting gravity anomaly maps have traditionally offered optimal resolution at crustal depths. Gravimetric maps and seismic data sets are therefore well suited to joint inversion, since the complementary information reduces inherent model ambiguity. Previous joint inversions of the Apollo seismic data (seismic phase arrival times) and Clementine‐ or Lunar Prospector‐derived gravity data (mass and moment of inertia) attempted to recover the subsurface structure of the Moon by focusing on hypothetical lunar compositions that explore the density/velocity relationship. These efforts typically search for the best fitting thermodynamically calculated velocity/density model, allowing variables like core size, velocity, and/or composition to vary freely. Seismic velocity profiles previously derived from the Apollo seismic data through inversion of travel times vary both in the depth of the crust and mantle layers, and the seismic velocities and densities assigned to those layers. The lunar mass and moment of inertia likewise only constrain gross variations in the density profile beyond that of a uniform density sphere. As a result, composition and structure models previously obtained by jointly inverting these data retain the original uncertainties inherent in the input data sets. We will perform a joint inversion of Apollo seismic delay times and gravity data collected by the GRAIL lunar gravity mission, in order to recover seismic velocities and density as a function of latitude, longitude, and depth within the Moon. We will relate density to seismic velocity using a linear relationship that is allowed to be depth‐dependent. The corresponding coefficient (B) can reflect a variety of material properties that vary with depth, including temperature and composition. The inversion seeks to recover the set of density, velocity, and B‐coefficient perturbations that minimize (in a least‐squares sense) the difference between the observed and calculated data.

Weber, Renee C.↗