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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Vector elastic deconvolution migration with dual wavefield decomposition

Here, we report elastic-wave imaging using multicomponent data can provide more useful subsurface information than acoustic-wave imaging, but it is usually algorithmically challenging. We have developed a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method uses a vector deconvolution imaging condition based on dual wavefield decomposition, including an explicit directional wavefield separation using the Hilbert transform and a P/S vector wavefield decomposition using the low-rank decomposition method. Using three elastic models, we numerically determine that our new method produces notably higher resolution and more amplitude-balanced elastic images compared with a crosscorrelation-based vector elastic reverse time migration method.

58 GEOSCIENCES↗
DOE OSTI2023

Seismic Characterization of the Blue Mountain Geothermal Field

Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.

58 GEOSCIENCES↗
DOE OSTI2020

Three-dimensional seismic characterization and imaging of the Soda Lake geothermal field

Accurate characterization of subsurface geophysical properties and detection of the fault system are essential for geothermal energy exploration and production. The Soda Lake geothermal field is in western Nevada with a complex fault system. Previous seismic characterization only produced a low-resolution, smooth velocity model along with a simple, conceptual fault model. Using optimized correlation-based full-waveform inversion, wavefield-separation-based reverse-time migration, and automatic fault detection techniques, we present 3D seismic characterization for the Soda Lake geothermal field using 3D surface seismic data acquired with Vibroseis sources. Here, we obtain 3D high-resolution velocity, density, and acoustic impedance models, 3D seismic images with different grid spacings, and a high-resolution fault system. Consistency check between the constructed faults and currently active injection and production geothermal wells verifies that our seismic inversion and imaging results and detected faults are reliable. These results can provide valuable information for optimizing well placement and geothermal energy production at the Soda Lake geothermal field.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Breeding latitude is associated with the timing of nesting and migration around the annual calendar among Purple Martin (Progne subis) populations

Timing is critical for species that migrate seasonally, as timing mismatches can lead to reduced reproductive success and population declines. We investigated the effect of breeding latitude on the migration timing of a long-distance migratory songbird (Purple Martin, Progne subis subis) by using light-level geolocators deployed across breeding sites between 26° and 53° latitude (n = 329). We used nesting data (1st egg dates; n=28,165) to explore latitudinal patterns in the timing of breeding. Using generalized linear mixed models (GLMMs) we found that breeding latitude was highly associated with timing around the calendar, explaining population-level timing across both spring and fall migration. Populations breeding at more northern latitudes migrated later in fall (mean days/degree latitude =2), in spring (mean days/degree latitude =3), and nested later (days/degree latitude = 3) than populations breeding at more southern latitudes. Generalized additive mixed models (GAMMs) revealed significant non-linearity between breeding latitude and spring and fall migration timing, and the timing of nesting. In spring, the most northern breeders (> 40 degrees N) were more synchronous in their timing, departing their nonbreeding sites and arriving earlier at their breeding sites relative to their breeding latitude. These most northern breeders also had similar nest timing and fall migration departure timing. Breeding latitude was also associated with seasonal partitioning of migratory and sedentary periods. The most northern breeders spent 10% more time on fall migration, 2% more at wintering grounds, 1% more on spring migration, and 13% less time at their breeding sites. Our results support the notion that selection for timing at breeding latitudes can have year-round effects on the timing of seasonal events in long-distance migratory songbirds. Future studies should examine whether these timing patterns associated with latitude limit phenotypic responses to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Indexing habitat opportunity for juvenile anadromous fishes in tidal-fluvial wetland systems

In intertidal wetlands, annual habitat use by migrating juvenile salmon is limited by both physical and biological constraints. Physical limits are set by inundation patterns and water quality parameters, while biological bounds are determined by species specific migration timing and seasonal residency behaviors. We developed a new metric called the fish habitat opportunity index (FHOI) to quantify the total time per calendar year that salmon could access intertidal sites, based on periods of inundation and juvenile salmon seasonal migration. The index was applied using data collected at a recently reconnected tidal freshwater wetland area during 2006-2009. We found the wetland to be accessible to different salmon species for different lengths of time and periods of the year. On average, chum salmon (Oncorhynchus keta) had remarkably consistent opportunities to use marsh habitat over the 4 years sampled, while opportunities were more variable for Chinook (O. tshawytscha), and coho salmon (O. kisutch). Inundation varied nonlinearly with tidal height, and fish had access to the productive marsh edge for approximately 40-50% of the time during periods of access. The FHOI is widely applicable to wetland systems throughout the tidal fluvial continuum, and provides a metric for assessing fish habitat opportunity that is more realistic than simple wetted area calculations. Finally, the FHOI affords a method of a priori comparison among potential restoration sites to help resource managers predict the likely relative benefit to juvenile salmon.

wetland restoration, estuary, habitat opportunity,↗
DOE OSTI2024

High-resolution source imaging and moment tensor estimation of acoustic emissions during brittle creep of basalt undergoing carbonation

SUMMARY As the high-frequency analogue to field-scale earthquakes, acoustic emissions (AEs) provide a valuable complement to study rock deformation mechanisms. During the load-stepping creep experiments with CO2-saturated water injection into a basaltic sample from Carbfix site in Iceland, 8791 AE events are detected by at least one of the seven piezoelectric sensors. Here, we apply a cross-correlation-based source imaging method, called geometric-mean reverse-time migration (GmRTM) to locate those AE events. Besides the attractive picking-free feature shared with other waveform-based methods (e.g. time-reversal imaging), GmRTM is advantageous in generating high-resolution source images with reduced imaging artefacts, especially for experiments with relatively sparse receivers. In general, the imaged AE locations are found to be scattered across the sample, suggesting a complicated fracture network rather than a well-defined major shear fracture plane, in agreement with X-ray computed tomography imaging results after retrieval of samples from the deformation apparatus. Clustering the events in space and time using the nearest-neighbour approach revealed a group of ‘repeaters’, which are spatially co-located over an elongated period of time and likely indicate crack, or shear band growth. Furthermore, we select 2196 AE events with high signal-to-noise-ratio (SNR) and conduct moment tensor estimation using the adjoint (backpropagated) strain tensor fields at the locations of AE sources. The resulting AE locations and focal mechanisms support our previously assertion that creep of basalt at the experimental conditions is accommodated dominantly by distributed microcracking.

58 GEOSCIENCES↗
DOE OSTI2019

Modeling Frequency–Independent Q Viscoacoustic Wave Propagation in Heterogeneous Media

Quantifying the attenuation of seismic waves propagating in the Earth interior is critical to study the subsurface structure. Previous studies have proposed fractional anelastic wave equations to model the frequency–independent Q seismic wave propagation. Such wave equations involve fractional derivatives that pose computational challenges for the numerical schemes in terms of accuracy and efficiency when dealing with heterogeneous Earth media. To tackle these challenges, here we derive a new viscoacoustic wave equation, where the power terms of the fractional Laplacian operators are spatially independent, thus accurate and efficient methods (e.g., the Fourier pseudospectral method) can be adopted. Our derivation enables the resultant equation to capture both amplitude and phase signatures of the anelastic wave propagation by matching the complex wave numbers for all the frequencies of interest. We verify the derivation by comparing the dispersion curves of both the attenuation factor and the phase velocity produced by the new wave equation with their theoretical values as well as the Pierre Shale in situ measurements. Following that, we use a synthetic attenuating gas chimney model to demonstrate the attenuation effects on seismic waveforms and then construct the Q–compensated reverse time migration to undo these effects for seismic image enhancement. Finally, we find that our forward modeling results can characterize the spatiotemporal attenuation effects revealed in the Frio–II CO2 injection time–lapse seismic monitoring data. Here, we expect this proposed equation to be useful to quantify the attenuation in seismic data to push the resolution limits of seismic imaging and inversion.

25 ENERGY STORAGE↗
DOE OSTI2023

Machine learning methods for particle stress development in suspension Poiseuille flows

Numerical simulations are used to study the dynamics of a developing suspension Poiseuille flow with monodispersed and bidispersed neutrally buoyant particles in a planar channel, and machine learning is applied to learn the evolving stresses of the developing suspension. The particle stresses and pressure develop on a slower time scale than the volume fraction, indicating that once the particles reach a steady volume fraction profile, they rearrange to minimize the contact pressure on each particle. Here we consider how the stress development leads to particle migration, time scales for stress development, and present a new physics-informed Galerkin neural network that allows for learning the particle stresses when direct measurements are not possible. The particle fluxes are compared with the Suspension Balance Model with good agreement. We show that when stress measurements are possible, the MOR-physics operator learning method can also capture the particle stresses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

3D seismic imaging of a fracture damage zone controlling reservoir compartmentalization at the Raft River EGS using multi-azimuth walkaway VSP

Accurate imaging of steeply dipping fracture zones in crystalline enhanced geothermal systems (EGS) is critical for constraining permeability architecture and guiding stimulation design. However, such structures remain poorly resolved by conventional surface seismic methods. We present a fully three-dimensional (3D) elastic-waveform inversion-migration workflow applied to multi-azimuth walkaway vertical seismic profiling (VSP) data acquired in a deviated borehole at the Raft River EGS. The workflow integrates first-arrival traveltime tomography, multi-scale elastic waveform inversion (EWI), and elastic least-squares reverse-time migration (ELSRTM) to recover high-resolution compressional-and shear-wave velocity models and to image structural discontinuities in the crystalline basement. The results reveal a laterally continuous low-velocity anomaly, with shear-wave velocity reductions of 25-30%, consistent with fractureinduced mechanical weakening. Two steeply dipping discontinuities bound a 50-80 m wide fracture damage zone. Independent constraints from microseismic clustering and geochemical compartmentalization corroborate the geometry and structural significance of this feature. Synthetic modeling further confirms that structures of this scale are resolvable (~30 m). These findings indicate that the Narrows structure is a distributed fracture damage zone rather than a discrete fault plane. By resolving fracture-zone geometry at the tens-of-meters scale using a single borehole, this workflow provides a practical and transferable approach for improving structural characterization, reducing uncertainty in permeability architecture, and supporting reservoir modeling and stimulation design in fractured crystalline EGS reservoirs.

58 GEOSCIENCES↗
DOE OSTI2020

Efficient 3-D velocity model building using joint inline and crossline plane-wave wave-equation migration velocity analyses

SUMMARY Wave-equation migration velocity analysis (WEMVA) is an image-domain inversion method for velocity model building. Automatic plane-wave WEMVA (PWEMVA) calculates the moveouts of plane-wave common-image gathers (CIGs) by searching a best-fitting parabola with semblance analysis and backprojects residual CIG moveouts into wavefield wave paths with a reflection tomographic kernel. However, 3-D PWEMVA is very computationally expensive because 3-D reflection tomographic inversion requires at least five 3-D reverse-time migrations per iteration and stores two types of source wavefields at model boundaries. We develop a joint inline and crossline PWEMVA method for efficient 3-D velocity model building. We alternatively implement the inline and crossline PWEMVAs with a constraint for each other, in which we iteratively construct the 3-D velocity model update through 1-D spline interpolation of 2-D gradients. The inline and crossline joint inversion is practical since PWEMVA only inverts for low-wavenumber velocity perturbations along wave paths, and the method can take less than 1 per cent of the computational cost of full 3-D PWEMVA. To construct unaliased plane waves for our joint inline and crossline PWEMVA, we develop a 3-D data interpolation method in the frequency–wavenumber (FK) domain to recover regularly and randomly missing traces. The method minimizes the misfit on sufficiently localized data subsets with iterative optimal step lengths and a gradient preconditioner that iteratively selects dominant dips along different azimuths. In numerical experiments, we use a 3-D synthetic seismic data set and a land 3-D field seismic data set acquired at the Farnsworth CO2-EOR (enhanced oil recovery) field to demonstrate the efficacy of our velocity model building and data interpolation methods.

Liu, Xuejian↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2021

Passage and survival of juvenile salmonid smolts through dams in the Columbia and Snake Rivers, 2010-2018

Minimizing the mortality and migration time of juvenile salmon (smolts) passing dams is a longstanding objective in the pursuit of salmon recovery in the Columbia River Basin. We compiled and analyzed 40 juvenile salmonid acoustic-tag studies that were performed at seven of the eight hydroelectric projects in the Federal Columbia River Power System between 2010–2018. We found the utilization of non-turbine routes decreased monotonically moving downstream from the Snake River to the mainstem Columbia River and that route usage and associated mortality differed substantially between the dams in the two rivers. Spillways were the predominant passage route at mainstem Columbia River dams, whereas passage through surface weirs and juvenile bypass systems was more common and generally provided higher survival at Snake River dams. Stocks exhibited variable passage behaviors and mortalities, with the estimated probability of an individual passing through all eight dams in the system and never using a turbine route at 0.31, 0.47, and 0.60 for subyearling Chinook Salmon, yearling Chinook Salmon, and steelhead, respectively. Although subyearling Chinook Salmon were generally more likely to pass through a turbine route, they also experienced less turbine-associated mortality than other stocks, especially steelhead. Notably, the proportion of smolts passing through the spillway relative to the amount of water released was lowest at Bonneville Dam, the largest and lowermost dam in the system. Bonneville Dam also stood out as having the highest proportion of smolts passing through turbines, but the lowest rate of turbine-associated mortality.

Skalski, J R.↗
DOE OSTI2023

A Review of Factors Affecting the Susceptibility of Juvenile Salmonids to Avian Predation

Abstract We reviewed studies of piscivorous colonial waterbird predation on juvenile salmonids to synthesize current knowledge of factors affecting fish susceptibility to avian predators. Specifically, we examined peer-reviewed publications and reports from academic, governmental, and nongovernmental agencies to identify commonalities and differences in susceptibility of salmonids to avian predation, with a focus on mark–recovery studies in the Columbia River basin. Factors hypothesized to influence salmonid susceptibility to avian predation were grouped into four general categories: (1) salmonid species and populations, (2) environmental factors, (3) prey density, predator density, and migration timing, and (4) prey characteristics. Our review focused on predation by Caspian terns Hydroprogne caspia, double-crested cormorants Nannopterum auritum, and gull species Larus spp. as these are the most well-studied avian predators of salmonids. Results indicated that predator–prey interactions varied across salmonid species and populations and species of avian predator. Inferences across studies supported multiple hypotheses regarding predator–prey dynamics, including environmental factors that influence prey exposure to predators (e.g., river flows, turbidity, alternative prey), variation in predator and prey abundances, predator characteristics (e.g., foraging behavior, colony location), and prey characteristics (e.g., fish length, condition). Mark–recovery studies of avian predation on fish populations have greatly improved our understanding of the factors affecting fish susceptibility to avian predation, the relative contributions of abiotic and biotic factors to predation susceptibility, and the extent to which avian predation affects fish survival and the viability of prey populations. Future studies that jointly model predation and survival and the factors affecting those processes will further broaden our understanding of predator–prey dynamics and directly evaluate the effects of predation on prey population dynamics.

Hostetter, Nathan J. (ORCID:0000000160752157)↗
DOE OSTI2022

SREMI: Super-resolution electromagnetic imaging with single-channel ground-penetrating radar

High-resolution near-surface imaging has important applications in civil engineering, infrastructure inspection, military threat detection, geological characterization, and lunar and planetary exploration. Zero-offset, singlechannel ground penetrating radar (GPR) imaging is an established technique for near-surface target imaging and sensing but often suffers from low spatial resolution and imaging artifacts, especially of deep structures. In response, we formulate the GPR imaging as a dual-sparsity optimization problem, and develop a super-resolution electromagnetic imaging method based on a fast iterative shrinkage-thresholding algorithm. We develop our GPR imaging method in the framework of electromagnetic exploding-reflectors simulation theory, therefore the imaging method is computationally efficient. In this work, we demonstrate through synthetic and field data examples that our method can produce sharper, more reliable images with fewer artifacts compared with single-pass reverse-time migration GPR method, thus leading to improved near-surface interpretation and object identification.

58 GEOSCIENCES↗
DOE OSTI2021

Preliminary Analysis of Source Physics Experiment Explosion-Triggered Microseismicity Using the Back-Projection Method

A series of four chemical explosions were detonated in a deep borehole within the Yucca Flat Dry Alluvium Geology (DAG) at the Nevada National Security Site between 2018 and 2019. The two larger chemical explosions of 50 tons (DAG-2) and 10 tons (DAG-4) TNT equivalent yield triggered energetic aftershock sequences numbering 1392 and 347 microearthquakes, respectively, within the first 10 days. No significant aftershock activity was observed for the two smaller 1-ton explosions (DAG-1 and DAG-3). Here, we used a back-projection method based on travel-time migration and stacking of signal-to-noise ratio traces to detect, associate and locate aftershocks from a subset of 22-geophones within a larger 2 urn:x-wiley:21699313:media:jgrb54910:jgrb54910-math-0001 2 km seismic array surrounding the borehole. The aftershocks located within 300 m of the borehole and the depths were above the working points of 300 and 50 m depths of DAG-2 and DAG-4, respectively, ruling out triggering slip on geologic faults or disturbances beneath neighboring collapse craters. DAG-2 and DAG-4 aftershocks decayed at similar rates, with power-law exponents of p = 1.48 and p = 1.49, respectively. These decay rates are comparable to aftershocks sequences triggered by earthquakes and historical nuclear explosions at Yucca Flat. A smooth power-law aftershock decay within the first 10 days suggests a triggering mechanism from explosion generated stress relaxation due to the diffusion of high gas pressures in the cavity and radial fractures. A more random and episodic aftershock rate would be expected due to cavity collapse or falling rubble in chimney formation.

58 GEOSCIENCES↗
DOE OSTI2023

Contrasting patterns of sequence variation in steelhead populations reflect distinct evolutionary processes

Abstract Multiple evolutionary processes influence genome‐wide allele frequencies and quantifying effects of genetic drift, and multiple forms of selection remain challenging in natural populations. Here, we investigate variation at major effect loci in contrast to patterns of neutral drift across a wide collection of steelhead ( Oncorhynchus mykiss ) populations that have declined in abundance due to anthropogenic impacts. Whole‐genome resequencing of 74 populations of steelhead revealed genome‐wide patterns (~8 million SNPs) consistent with expected neutral population structure. However, allelic variation at major effect loci associated with adult migration timing (chromosome 28: GREB1L / ROCK1 ) and age at maturity (chromosome 25: SIX6 ) reflected how selection has acted on phenotypic variation in contrast with neutral structure. Variation at major effect loci was influenced by evolutionary processes with differing signals between the strongly divergent Coastal and Inland lineages, while allele frequencies within and among populations within the Inland lineage have been driven by local natural selection as well as recent anthropogenic influences. Recent anthropogenic effects appeared to have influenced the frequency of major effect alleles including artificial selection for specific traits in hatchery stocks with subsequent gene flow into natural populations. Selection from environmental factors at various scales has also likely influenced variation for major effect alleles. These results reveal evolutionary mechanisms that influence allele frequencies at major effect loci that are critical for conservation of phenotypic traits and life history variation of this protected species.

Willis, Stuart↗
DOE OSTI2023

Compensating attenuation effects in full-waveform inversion with dissipation-dispersion decoupling

Seismic attenuation poses challenges to velocity model building from acoustic/elastic full-waveform inversion (FWI). In particular, when constructing the FWI gradient for velocity inversion, recent studies have indicated that the high-attenuation structure could distort the gradient by damping the amplitudes and shifting the kinematic phases, resulting in an imbalanced update and thus unreliable velocity model. These Q effects are particularly significant in the reflection acquisition geometry due to the “double-damping” issue. Here, we develop a Q-compensated FWI algorithm for constructing a Q-free FWI gradient. By using a recently developed viscoacoustic wave propagator, this compensation can be done conveniently by keeping the dispersion term and flipping the dissipation term in the wave equation when we simulate the forward and time-reversed adjoint wavefields. The resultant gradient obtained by interacting these two wavefields has correct kinematics and Q-free amplitudes. This Q-compensated FWI can balance the update between Q- and no- Q-areas, which we determine using synthetic examples. In addition, we illustrate how to take advantage of the dissipation-dispersion decoupling to determine the anomalous Q value in the Q model building workflow via Q-compensated reverse time migration.

Geochemistry & Geophysics↗
DOE OSTI2019

Utah FORGE: GPS Data - Deformation Monitoring

This data bundle contains raw GPS data files and resulting data using Trimble Business Center and NOAA OPUS to process the GPS data in spreadsheets with station coordinates and elevations. A map of station locations is included along with the final processing report which includes pre-processing, pre-stack time migration, and pre-stack depth migration. It also contains a readme.text file goes into further explanation.

15 GEOTHERMAL ENERGY↗