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At least 955 records · Page 53

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential while Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential While Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics: Preprint

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗

Equation of state for He bubbles in W and model of He bubble growth and bursting near W{100} surfaces derived from molecular dynamics simulations

Abstract Molecular dynamics (MD) simulations are performed to derive an equation of state (EOS) for helium (He) bubbles in tungsten (W) and to study the growth of He bubbles under a W(100) surface until they burst. We study the growth as a function of the initial nucleation depth of the bubbles. During growth, successive loop-punching events are observed, accompanied by shifts in the depth of the bubble towards the surface. Subsequently, the MD data are used to derive models that describe the conditions that cause the loop punching and bursting events. Simulations have been performed at 500, 933, 1500, 2000, and 2500 K to fit the parameters in the models. To compute the pressure in the bubble at the loop punching and bursting events from the models, we derive an EOS for He bubbles in tungsten with an accompanying volume model to compute the bubble volume for a given number of vacancies ( $$N_\text {V}$$ N V ), He atoms ( $$N_\text {He}$$ N He ), and temperature ( T ). To derive the bubble EOS, we firstly derive the EOS for a free He gas. The derived free-gas EOS can accurately predict all MD data included in the analysis (which span up to 54 GPa at 2500 K). Subsequently, the bubble EOS is derived based on the free-gas EOS by correcting the gas density to account for the interaction between He and W atoms. The EOS for the bubbles is fitted to data from MD simulations of He bubbles in bulk W that span a wide range of gas density and sizes up to about 3 nm in diameter. The pressure of subsurface bubbles at the loop punching events as calculated using the bubble-EOS and the volume model agrees well with the pressure obtained directly from the MD simulations. In the loop punching model, for bubbles consisting of $$N_\text {V}$$ N V vacancies and $$N_\text {He}$$ N He helium atoms, the $$N_\text {He}/N_\text {V}$$ N He / N V ratio that causes the event, the resulting increase in $$N_\text {V}$$ N V , and the associated shift of the bubble depth are formulated as a function of $$N_\text {V}$$ N V and T . In the bursting model, a bubble must simultaneously reach a certain depth and $$N_\text {He}/N_\text {V}$$ N He / N V ratio in order to burst. The burst depth and $$N_\text {He}/N_\text {V}$$ N He / N V are also modeled as a function of $$N_\text {V}$$ N V and T . The majority of the loop punching events occur at bubble pressures between 20 and 60 GPa, depending on the bubble size and temperature. The larger the bubble and the higher the temperature, the lower the bubble pressure. Furthermore, our results indicate that at a higher temperature, a bubble can burst from a deeper region.

36 MATERIALS SCIENCE↗

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗

SU-E-T-557: Monte Carlo Modeling of Philips RT-250 Orthovoltage Unit for Beam Spectrum Modulation

Purpose: To develop and validate a Monte Carlo (MC) model of a Phillips RT-250 orthovoltage unit to test various beam spectrum modulation strategies for in vitro/vivo studies. A model of this type would enable the production of unconventional beams from a typical orthovoltage unit for novel therapeutic applications such as gold nanoparticle-aided radiotherapy. Methods: The MCNP5 code system was used to create a MC model of the head of RT-250 and a 30 × 30 × 30 cm{sup 3} water phantom. For the x-ray machine head, the current model includes the vacuum region, beryllium window, collimators, inherent filters and exterior steel housing. For increased computational efficiency, the primary x-ray spectrum from the target was calculated from a well-validated analytical software package. Calculated percentage-depth-dose (PDD) values and photon spectra were validated against experimental data from film and Compton-scatter spectrum measurements. Results: The model was validated for three common settings of the machine namely, 250 kVp (0.25 mm Cu), 125 kVp (2 mm Al), and 75 kVp (2 mm Al). The MC results for the PDD curves were compared with film measurements and showed good agreement for all depths with a maximum difference of 4 % around dmax and under 2.5 % for all other depths. The primary photon spectra were also measured and compared with the MC results showing reasonable agreement between the two, validating the input spectra and the final spectra as predicted by the current MC model. Conclusion: The current MC model accurately predicted the dosimetric and spectral characteristics of each beam from the RT-250 orthovoltage unit, demonstrating its applicability and reliability for beam spectrum modulation tasks. It accomplished this without the need to model the bremsstrahlung xray production from the target, while significantly improved on computational efficiency by at least two orders of magnitude. Supported by DOD/PCRP grant W81XWH-12-1-0198.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Utah FORGE 2439: Well 16B(78)-32 Field-Test Data from Mini-Frac Tests

This submittal includes the field-test data collected during stress tests conducted in the Utah FORGE 16B(78)-32 wellbore to measure/characterize the stresses in the geothermal reservoir. The type of stress test performed is referred to as a mini-frac test or a micro-frac test. The test is a hydraulic fracture test that involves injecting a small volume of water into a short interval of the reservoir that is isolated by a straddle packer to create a fracture. The test provides information about the minimum and maximum horizontal stress at the test depths. A total of seven mini-frac tests were performed within the upper (vertical or nearly vertical) section of the 9-5/8-inch diameter uncased wellbore, between depths of 5,202 ft MD [5,202 ft TVD] and 5,980 ft MD [5966.18 ft TVD]. Two types of data were generated as part of the mini-frac tests. The first type of data is time-series data for each mini-frac test (e.g., injection-rate, test-interval pressure), and are contained in the "Mini-Frac Test Data.zip" file below. The second type is geophysical log data, attached below in the "Geophysical Logs.zip" file. Here, two types of image logs and acoustic logs were obtained before and after the mini-frac tests to examine each test depth for visual evidence of induced fracture(s) and to measure the azimuth (orientation) of any observed fractures. The attached Readme file includes the test depth information and contents of each data file included here. Analysis of the field-test data was conducted and is documented in the attached report below.

15 GEOTHERMAL ENERGY↗

Cavity evolution and void swelling in dual ion irradiated tempered martensitic steels

Microstructural evolutions in two variants of the F82H 8 wt%Cr tempered martensitic steel under dual (He + plus Fe 3+ ) ion irradiations at 500 °C have been characterized by transmission electron microscopy. Emphasis is on understanding the combined effects of displacements per atom (dpa) and the helium/dpa ratio (He/dpa) on cavity evolution and void swelling (f v ). The dual ion database includes 231 alloy-dpa-He/dpa conditions for irradiations up to ~ 82 dpa and 3700 appm helium. Here, we hypothesize that the large “scatter” observed in the f v data is primarily due to local microstructural variations, especially those that shield regions at shallower depths from the effects of injected interstitial atoms, which would otherwise reduce f v . More generally, our hypothesis is that the highest f v data, at a specified dpa and He/dpa, provides the most appropriate estimate of swelling for fusion neutron irradiation conditions. The dose dependence of f v can be described by an incubation dpa i , marking the onset of significant void growth, and a post-incubation swelling rate, f v ’ = Δf v /Δdpa. Both dpa i and f v ’ decrease with increasing He/dpa. The f v ’ data are quantitatively consistent with a simple model for defect partitioning between evolving bubble, void, and dislocation sinks strengths and biases. Most notably, the model correctly predicts both the incubation dpa i , and the subsequent f v ’, in spite of the fact that they reflect somewhat different physics. Our analysis also suggests that defect recombination is modest at 500 °C. Along with other considerations, this supports the hypothesis that, even at high dpa rates, dual ion irradiations can be used to reasonably emulate void nucleation and growth for a range of fusion-relevant neutron irradiation service conditions. A companion paper incorporates the results of this study in a reduced-order, data-driven void swelling model.

36 MATERIALS SCIENCE↗

Reciprocal space XRD mapping with varied incident angle as a probe of structure variation within surface depth

In this study, we used a differential-depth X-Ray diffraction Reciprocal Spacing Mapping (XRD RSM) technique to investigate the crystal quality of a variety of SRF-relevant Nb film and bulk materials. By choosing different X-ray probing depths, the RSM study successfully revealed evolution the of materials microstructure after different materials processes, such as energetic condensation or surface polishing. The RSM data clearly measured the materials crystal quality at different thickness. Through a novel differential-depth RSM technique, this study found: I. for a heteroepitaxy Nb film Nb(100)/MgO(100), the film thickening process, via a cathodic arc-discharge Nb ion deposition, created a near-perfect single crystal Nb on the surfaces top-layer; II. for a mechanically polished single-crystal bulk Nb material, the microstructure on the top surface layer is more disordered than that in-grain.

Yang, Qiguang↗

2017 Meander C sediment characterization from the East River, Colorado

This dataset includes characterization data collected on sediment samples from Meander C as part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected to investigate the nature of mineral-organic associations across the meander transect and with depth. Samples were collected in 2017, and analyzed using sequential extractions (water, pyrophosphate, HCl, and dithionite) and density fractionation. Data collected include: texture, pH, root biomass, and metals (Fe, Al, Ca, Si) of bulk sediment samples; C and N of heavy fraction; and extractable OC, Fe, and Al, and organic matter characterization using high-resolution mass spectrometry (FT-ICR-MS) of sequential extractions. Sample locations are included in the ‘sample_metadata.xlsx” file. Sediment characterization data is included in the accompanying csv files: bulk and density fractions (MCB2017_density-and-bulk-fractions.csv), sequential extractions (MCB2017_sequential-extractions.csv), and FT-ICR-MS data from sequential extractions in three files to be read by the R package ftmsRanalysis (MCB2017_FTICRMS-sequential-edata.csv, MCB2017_FTICRMS-sequential-emeta.csv, and MCB2017_FTICRMS-sequential-fdata.csv). Sediment was collected in triplicate; ID’s refer to individual samples.

54 ENVIRONMENTAL SCIENCES↗

Agulhas Current Properties Shape Microbial Community Diversity and Potential Functionality

Understanding the impact of oceanographic features on marine microbial ecosystems remains a major ecological endeavour. Here we assess microbial diversity, community structure and functional capacity along the Agulhas current system and the Subtropical convergence in the South Indian Ocean (SIO). Samples collected from the epipelagic, oxygen minimum and bathypelagic zones were analysed by 16S rRNA gene amplicon and metagenomic sequencing. In contrast to previous studies, we found high taxonomic richness in surface and deep water samples, but generally low richness for oxygen minimum zone communities. Beta-diversity analysis revealed significant dissimilarity between the three water depths. Most microbial communities were dominated by marine Gammaproteobacteria, with strikingly low levels of picocyanobacteria. Community composition was strongly influenced by specific environmental factors including depth, salinity, and the availability of both oxygen and light. Carbon, nitrogen and sulphur cycling capacity is the SIO was linked to several autotrophic and copiotrophic Alphaproteobacteria and Gammaproteobacteria. Taken together, our data suggest that the environmental conditions in the Agulhas current system, particularly depth-related parameters, substantially influence microbial community structure. While the capacity for biogeochemical cycling of nitrogen and sulphur is linked primarily by the dominant Gammaproteobacterial taxa, ecologically rare taxa drive carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Deuterium Depth Profile in Neutron-Irradiated Tungsten Exposed to Plasma

The effect of radiation damage has been mainly simulated using high-energy ion bombardment. The ions, however, are limited in range to only a few microns into the surface. Hence, some uncertainty remains about the increase of trapping at radiation damage produced by 14 MeV fusion neutrons, which penetrate much farther into the bulk material. With the Japan-US joint research project: Tritium, Irradiations, and Thermofluids for America and Nippon (TITAN), the tungsten samples (99.99 % pure from A.L.M.T., 6mm in diameter, 0.2mm in thickness) were irradiated to high flux neutrons at 50 C and to 0.025 dpa in the High Flux Isotope Reactor (HFIR) at the Oak Ridge National Laboratory (ORNL). Subsequently, the neutron-irradiated tungsten samples were exposed to a high-flux deuterium plasma (ion flux: 1021-1022 m-2s-1, ion fluence: 1025-1026 m-2) in the Tritium Plasma Experiment (TPE) at the Idaho National Laboratory (INL). First results of deuterium retention in neutron-irradiated tungsten exposed in TPE have been reported previously. This paper presents the latest results in our on-going work of deuterium depth profiling in neutron-irradiated tungsten via nuclear reaction analysis. The experimental data is compared with the result from non neutron-irradiated tungsten, and is analyzed with the Tritium Migration Analysis Program (TMAP) to elucidate the hydrogen isotope behavior such as retention and depth distribution in neutron-irradiated and non neutron-irradiated tungsten.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Association between soil organic carbon and calcium in acidic grassland soils from Point Reyes National Seashore, CA

All data is collected from across 3 soil cores spanning a pH gradient at Point Reyes National Seashore, as part of a recent publication. The bulk data csv includes hygroscopic moisture content, soil pH, total C and N values, particle size distributions, cation exchange capacity and extractable cations. The STXM data package includes raw spectra data from scanning transmission X-ray microscopy C near-edge X-ray absorption fine structure spectroscopy analysis, extracted from STXM Image Reader analysis and then subsequently normalised in Athena (see details in paper). The data file also contains a bulk chemistry and mineralogy dataset, including total and trace element contents from 3 depths and mineral compositions as measured at BL 11-3 SSRL and semi-quantified in HighScore. Finally the final data file is calcium K-edge X-ray absorption near-edge structure spectroscopy (BL 4-3) and micro-XANES and micro-X-ray fluorescence (BL 14-3b) data.

54 ENVIRONMENTAL SCIENCES↗

SU-F-T-487: On-Site Beam Matching of An Elekta Infinity with Agility MLC with An Elekta Versa HD

Purpose: Historically, beam matching of similar Linear Accelerators has been accomplished by sending beam data to the manufacturer to match at their factory. The purpose of this work is to demonstrate that fine beam matching can be carried out on-site as part of the acceptance test, with similar or better results. Methods: Initial scans of a 10 × 10 Percent depth dose (PDD) and a 40 × 40 beam profile at the depth of Dmax, for 6MV and 10 MV were taken to compare with the standard beam data from the Versa. The energy was then adjusted and the beam steered to achieve agreement between the depth dose and the horns of the beam profile. This process was repeated until the best agreement between PDD and profiles was achieved. Upon completion, all other clinical data were measured to verify match. This included PDD, beam profiles, output factors and Wedge factors. For electron beams PDD’s were matched and the beam profiles verified for the final beam energy. Confirmatory PDD and beam profiles for clinical field sizes, as well as Output Factors were measured. Results: The average difference in PDD’s for 6MV and 10MV were within 0.4% for both wedged and open fields. Beam profile comparisons over the central 80% of the field, at multiple depths, show agreement of 0.8% or less for both wedged and open fields. Average output factor agreement over all field sizes was 0.4% for 6MV and 0.2 % for 10MV. Wedge factors agreement was less than 0.6% for both photon energies over all field sizes. Electron PDD agreed to 0.5mm. Cone ratios agreed to 1% or less. Conclusion: This work indicates that beam matching can be carried out on-site simply and quickly. The results of this beam matching can achieve similar or better results than factory matching.

43 PARTICLE ACCELERATORS↗

The impacts of permafrost thaw on land-atmosphere greenhouse gas exchange

Permafrost thaw and the subsequent mobilization of carbon stored in previously frozen soil organic matter (SOM) would be a strong positive feedback to climate1. As the northern permafrost region experiences double the rate of warming as the rest of the Earth2, the vast amount of carbon in permafrost soils3 is vulnerable to thaw, decomposition and release as atmospheric greenhouse gases (GHG). Here, we employ a process-based model simulation experiment to assess the net effect of this so-called permafrost carbon feedback (PCF) in recent decades. Results show a wide-spread increase in the depth to permafrost between 1990 and 2006, with simulated active layer thickness (ALT) capturing the mean and spatial variability of the observational data. Analysis of the simulation experiment provides an estimate of a 2.8 mm/yr increase in permafrost depth, which translates to 281 TgC/yr thawed from previously frozen SOM. Overall, we estimate a net GHG forcing of 534 MtCO2eq/yr directly tied to ALT dynamics, while accounting for CO2 (562 MtCO2eq/yr) and CH4 (52 MtCO2eq/yr) release as well as CO2 uptake by vegetation (-80 MtCO2eq/yr). This net forcing represents a significant factor in the estimated 640 MtCO2eq/yr pan-arctic GHG source4, and an additional 6.9% contribution on top of the combined 7792 MtCO2eq/yr fossil fuel emissions from the eight Arctic nations over this time period5.

carbon↗

Alabama Carbon Storage: Data Sharing and Engagement (Final Report)

This report is the final technical report on Alabama Carbon Storage: Data Sharing Engagement (ACS:DSE) project activities. The goals of the ACS:DSE project are to compile geologic, geophysical, infrastructure, and other relevant CCUS datasets for the study area and develop a geologic model of the study area; develop an online platform to serve data to stakeholders; engage with the public, students, and industry to educate them about CCUS and the data platform; and ensure energy and environmental justice is central to all aspects of the project. Datasets compiled and expanded include formation depths and elevations, digital geophysical well logs, reservoir properties, geologic structures, and geologic models. The geologic data were used to create a three-dimensional geologic model, structure grids, structure contour maps, and fault trace maps. In addition to downloadable datasets, links to CCUS relevant regulatory agencies (e.g., OGB, U.S. Environmental Protection Agency) and sources for infrastructure and educational information were included on the website Educational materials on CCUS for use by K-12 teachers were produced as part of the ACS:DSE project.

01 COAL, LIGNITE, AND PEAT↗

Temperature-At-Depth Maps For the Conterminous US and Geothermal Resource Estimates

A third generation geothermal resource assessment has recently been completed for the conterminous US based on a revised heat flow map using over 35,000 data sites. Improvements include: nearly doubling the number of data points used in the analysis, more detailed thermal conductivity models for temperature-at-depth and heat flow calculations, and addition of a significant number of calibration wells as checks on the bottom hole temperature (BHT) correction. The results increase the accuracy of temperature-at-depth models for the conterminous US. These temperature models are the key input required for evaluating the non-conventional geothermal resources on a regional to sub-regional basis. The new resource assessment was prepared according to a proposed global protocol for estimating Enhanced/ Engineered Geothermal Systems (EGS) resource potential. A comparison of the new assessment approach with previous studies is provided, along with a discussion of the differences associated with the revised approach.

15 GEOTHERMAL ENERGY↗

Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone

The critical zone sustains terrestrial life, but we have few tools to explore it efficiently beyond the first few meters of the subsurface. Using analyses of high-frequency ambient seismic noise from densely spaced seismometers deployed in the forested Shale Hills subcatchment of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), we show that temporal changes in seismic velocities at depths from ~1 m to tens of m can be detected. Furthermore, these changes are driven by variations at the land surface. The Moving-Window Cross-Spectral (MWCS) method was employed to measure seismic-velocity changes in coda waves at hourly resolution in 10 different frequency bands. We observed a diurnal signal, a seasonal signal, and a meteorological-event-based signal. These signals were compared to time-series measurements of precipitation, well water levels, soil moisture, soil temperature, air temperature, latent heat flux, and air pressure in the heavily instrumented catchment. Most of the velocity changes can be explained by variations in temperature that result in thermoelastic strains that propagate to depth. But some double minima in seismic velocity time-series observed after large rain events were attributed in part to the effects of water infiltration. These results show that high-frequency ambient noise data may in some locations be used to detect changes in the critical zone from ~1 to ~100 m or greater depth with hourly resolution. But interpretation of such data requires multiple environmental data sets to deconvolve the complex interrelationships among thermoelastic and hydrological effects in the subsurface critical zone.

54 ENVIRONMENTAL SCIENCES↗

Three-dimensional gravity modeling and focusing inversion using rectangular meshes.

Rectangular grid cells are commonly used for the geophysical modeling of gravity anomalies, owing to their flexibility in constructing complex models. The straightforward handling of cubic cells in gravity inversion algorithms allows for a flexible imposition of model regularization constraints, which are generally essential in the inversion of static potential field data. The first part of this paper provides a review of commonly used expressions for calculating the gravity of a right polygonal prism, both for gravity and gradiometry, where the formulas of Plouff and Forsberg are adapted. The formulas can be cast into general forms practical for implementation. In the second part, a weighting scheme for resolution enhancement at depth is presented. Modelling the earth using highly digitized meshes, depth weighting schemes are typically applied to the model objective functional, subject to minimizing the data misfit. The scheme proposed here involves a non-linear conjugate gradient inversion scheme with a weighting function applied to the non-linear conjugate gradient scheme's gradient vector of the objective functional. The low depth resolution due to the quick decay of the gravity kernel functions is counteracted by suppressing the search directions in the parameter space that would lead to near-surface concentrations of gravity anomalies. Further, a density parameter transformation function enabling the imposition of lower and upper bounding constraints is employed. Using synthetic data from models of varying complexity and a field data set, it is demonstrated that, given an adequate depth weighting function, the gravity inversion in the transform space can recover geologically meaningful models requiring a minimum of prior information and user interaction.

54 ENVIRONMENTAL SCIENCES↗