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At least 415 records · Page 23Linked to original sources
USGS2021

Revisiting the declustering of spatial data with preferential sampling

Preferential sampling is a form of data collection that may significantly distort the histogram and the semivariogram of spatially correlated data . Typical situations are a higher sampling density at high-valued areas favorable for mining, and highly contaminated areas in need of environmental remediation. Multiple statistical procedures are devoted to obtaining representative statistics, whose magnitudes should be close to the respective population values. This paper proposes a resampling method that can compensate for preferential sampling of spatially correlated data without using declustering weights. The application of the method herein generates a dataset of median estimates of quantiles of multiple stratified resamples that is free of preferential sampling. The methodology is illustrated with two examples. The first one involves values actually measured in the field and has the advantage of representing a real scenario of spatial fluctuations and preferential sampling. A second dataset is synthetic and has the main benefit of a priori knowledge of the underlying spatial distribution, thus allowing a satisfactory evaluation of the results against the known baseline. Access to computer code is offered for practical application of the method.

Computers & Geosciences↗
USGS2022

gTOOLS, an open-source MATLAB program for processing high precision, relative gravity data for time-lapse gravity monitoring

gTOOLS is an open-source software for the processing of relative gravity data. gTOOLS is available in MATLAB and as a compiled executable to be run under the free MATLAB Runtime Compiler. The software has been designed for time-lapse (temporal) gravity monitoring. Although programmed to read the Scintrex CG-5 and CG-6 gravimeters output data files, it can be easily modified to read data files from other gravimeters. The software binds together single-task processing modules within a very simple user interface that is based on one text file. Gravity processing involves three modules: (a) gravimeter calibration; (b) automatic processing of gravity data to find adjusted gravity differences; and (c) post processing of results. Each module is optional and runs independently from the others. Data processing includes (a) averaging out the measurements noise, and correction for solid Earth tides, and ocean loading, and residual instrumental drift, and (b) calculate the residual instrumental drift and gravity differences between the base station and monitoring sites, and their uncertainties, by a weighted least square analysis of the gravity data. The software allows the automatic processing of a gravity campaign spanning multiple days in a single run. The software is tested on gravity data from 2015 eruption at Cotopaxi volcano, Ecuador.

Computers & Geosciences↗
USGS2022

MTH5: An archive and exchangeable data format for magnetotelluric time series data

Magnetotellurics (MT) is a passive electromagnetic geophysical method that measures variations in subsurface electrical resistivity. MT data are collected in the time domain and processed in the frequency domain to produce estimates of a transfer function representing the Earth’s electrical structure. Unfortunately, the MT community lacks metadata and data standards for time series data. As the community grows and findability, accessibility, interoperability, and reuse of digital assets (FAIR) data principles are enforced by government and funding agencies, a standard is needed for time series data. Presented here is a hierarchical data format (MTH5) that is logically formatted to how MT data are collected. Open-source Python packages are also described to read, write, and manipulate MTH5 files. These include a package to deal with metadata ( mt_metadata ) based on standards developed by the Working Group for Magnetotelluric Data Handling and Software assembled by the Incorporated Research Institutions for Seismology (IRIS), and mth5 : a package to interact with MTH5 files that uses mt_metadata . Example code and workflows are presented.

Computers & Geosciences↗
USGS2024

Hybrid CPU-GPU solution to regularized divergence-free curl-curl equations for electromagnetic inversion problems

The Curl-Curl equation is the foundation of time-harmonic electromagnetic (EM) problems in geophysics. The efficiency of its solution is key to EM simulations, accounting for over 95% of the computation cost in geophysical inversions for magnetotelluric or controlled-source EM problems. However, most published EM inversion codes are still central processing unit (CPU)-based and cannot utilize recent computational developments on the graphic processing units (GPUs). Based on a previously proposed divergence-free algorithm developed on CPUs, this study demonstrates the current limits of the CPU-based inversion procedure. To exploit the high throughput capability of GPUs, we propose a hybrid CPU-GPU framework to solve forward and adjoint problems required for EM inversions. The large sparse linear systems arising from the staggered-grid finite difference approximation of the Curl-Curl equation are solved with a mixed-precision Krylov subspace solver implemented on a GPU. The algorithm is then tested in EM forward and adjoint calculations, with real-world three-dimensional numerical examples. Test results show promising 30× kernel-level speed-ups over the conventional CPU algorithm. This approach may further take the complex frequency domain EM inversions onto the next, practical stage on small affordable GPU platforms.

Computers and Geosciences↗
USGS2006

Geodetic observations of post-seismic transients in the context of the earthquake deformation cycle

Satellite geodetic techniques that can measure displacements with millimeter-level accuracy reveal transient signals in the deformation fields produced by both moderate and large earthquakes. These post-seismic signals exhibit characteristic time scales ranging from weeks to decades and distance scales from hundreds of meters to hundreds of kilometers. By considering them in the context of the earthquake deformation cycle, we can test hypotheses about the processes driving them and constrain the rheology of the lithosphere. We discuss three broad categories of mechanism: afterslip in the plane of the co-seismic rupture (analogous to a rubber eraser), fluid flow in the fault zone (analogous to a water-laden sponge), and ductile flow in a weak substrate (analogous to a pot of honey).

Comptes Rendus - Geoscience↗
USGS2009

Structural evolution of the Ural-Tian Shan junction: A view from Karatau ridge, South Kazakhstan

The deformation history of the Late Palaeozoic Ural-Tian Shan junction is discussed for the example of the Karatau ridge in southern Kazakhstan. Three deformation events are recognized. The Late Carboniferous D1 event is characterized by Laramide-style thrust-and-fold structures on the southern margin of Kazakhstan with shortening in a NE-SW direction. The Latest Permian and Triassic D2 event is controlled by compression in an east-west direction, which reflects collisional deformation in the Urals. The main structures are submeridional folds and north-west-striking sinistral strike-slip faults. The Triassic D3 event with shortening in a north-south direction reflects collision of the Turan microcontinent against the southern margin of Kazakhstan. The main structures are north-west-striking dextral strike-slip faults. Our new data provides important clues for the reconstruction of pre-Cretaceous structures between the Urals and the Tian Shan. ?? 2008 Acad??mie des sciences.

Comptes Rendus - Geoscience↗
USGS2011

Structural stability of methane hydrate at high pressures

The structural stability of methane hydrate under pressure at room temperature was examined by both in-situ single-crystal and powder X-ray diffraction techniques on samples with structure types I, II, and H in diamond-anvil cells. The diffraction data for types II (sII) and H (sH) were refined to the known structures with space groups Fd 3 m and P 6 3 / mmc , respectively. Upon compression, sI methane hydrate transforms to the sII phase at 120 MPa, and then to the sH phase at 600 MPa. The sII methane hydrate was found to coexist locally with sI phase up to 500 MPa and with sH phase up to 600 MPa. The pure sH structure was found to be stable between 600 and 900 MPa. Methane hydrate decomposes at pressures above 3 GPa to form methane with the orientationally disordered Fm 3 m structure and ice VII ( Pn 3 m ). The results highlight the role of guest (CH 4 )-host (H 2 O) interactions in the stabilization of the hydrate structures under pressure.

Geoscience Frontiers↗
USGS2013

History and evaluation of national-scale geochemical data sets for the United States

Six national-scale, or near national-scale, geochemical data sets for soils or stream sediments exist for the United States. The earliest of these, here termed the ‘Shacklette’ data set, was generated by a U.S. Geological Survey (USGS) project conducted from 1961 to 1975. This project used soil collected from a depth of about 20 cm as the sampling medium at 1323 sites throughout the conterminous U.S. The National Uranium Resource Evaluation Hydrogeochemical and Stream Sediment Reconnaissance (NURE-HSSR) Program of the U.S. Department of Energy was conducted from 1975 to 1984 and collected either stream sediments, lake sediments, or soils at more than 378,000 sites in both the conterminous U.S. and Alaska. The sampled area represented about 65% of the nation. The Natural Resources Conservation Service (NRCS), from 1978 to 1982, collected samples from multiple soil horizons at sites within the major crop-growing regions of the conterminous U.S. This data set contains analyses of more than 3000 samples. The National Geochemical Survey, a USGS project conducted from 1997 to 2009, used a subset of the NURE-HSSR archival samples as its starting point and then collected primarily stream sediments, with occasional soils, in the parts of the U.S. not covered by the NURE-HSSR Program. This data set contains chemical analyses for more than 70,000 samples. The USGS, in collaboration with the Mexican Geological Survey and the Geological Survey of Canada, initiated soil sampling for the North American Soil Geochemical Landscapes Project in 2007. Sampling of three horizons or depths at more than 4800 sites in the U.S. was completed in 2010, and chemical analyses are currently ongoing. The NRCS initiated a project in the 1990s to analyze the various soil horizons from selected pedons throughout the U.S. This data set currently contains data from more than 1400 sites. This paper (1) discusses each data set in terms of its purpose, sample collection protocols, and analytical methods; and (2) evaluates each data set in terms of its appropriateness as a national-scale geochemical database and its usefulness for national-scale geochemical mapping.

Conterminous United States↗
USGS2013

The dilemma of the Jiaodong gold deposits: Are they unique?

The ca. 126–120 Ma Au deposits of the Jiaodong Peninsula, eastern China, define the country's largest gold province with an overall endowment estimated as >3000 t Au. The vein and disseminated ores are hosted by NE- to NNE-trending brittle normal faults that parallel the margins of ca. 165–150 Ma, deeply emplaced, lower crustal melt granites. The deposits are sited along the faults for many tens of kilometers and the larger orebodies are associated with dilatational jogs. Country rocks to the granites are Precambrian high-grade metamorphic rocks located on both sides of a Triassic suture between the North and South China blocks. During early Mesozoic convergent deformation, the ore-hosting structures developed as ductile thrust faults that were subsequently reactivated during Early Cretaceous “Yanshanian” intracontinental extensional deformation and associated gold formation. Classification of the gold deposits remains problematic. Many features resemble those typical of orogenic Au including the linear structural distribution of the deposits, mineralization style, ore and alteration assemblages, and ore fluid chemistry. However, Phanerozoic orogenic Au deposits are formed by prograde metamorphism of accreted oceanic rocks in Cordilleran-style orogens. The Jiaodong deposits, in contrast, formed within two Precambrian blocks approximately 2 billion years after devolatilization of the country rocks, and thus require a model that involves alternative fluid and metal sources for the ores. A widespread suite of ca. 130–123 Ma granodiorites overlaps temporally with the ores, but shows a poor spatial association with the deposits. Furthermore, the deposit distribution and mineralization style is atypical of ores formed from nearby magmas. The ore concentration requires fluid focusing during some type of sub-crustal thermal event, which could be broadly related to a combination of coeval lithospheric thinning, asthenospheric upwelling, paleo-Pacific plate subduction, and seismicity along the continental-scale Tan-Lu fault. Possible ore genesis scenarios include those where ore fluids were produced directly by the metamorphism of oceanic lithosphere and overlying sediment on the subducting paleo-Pacific slab, or by devolatilization of an enriched mantle wedge above the slab. Both the sulfur and gold could be sourced from either the oceanic sediments or the serpentinized mantle. A better understanding of the architecture of the paleo-Pacific slab during Early Cretaceous below the eastern margin of China is essential to determination of the validity of possible models.

Shandong Province↗
USGS2016

The conjunction of factors that lead to formation of giant gold provinces and deposits in non-arc settings

It is quite evident that it is not anomalous metal transport, nor unique depositional conditions, nor any single factor at the deposit scale, that dictates whether a mineral deposit becomes a giant or not. A hierarchical approach thus is required to progressively examine controlling parameters at successively decreasing scales in the total mineral system to understand the location of giant gold deposits in non-arc environments. For giant orogenic, intrusion-related gold systems (IRGS) and Carlin-type gold deposits and iron oxide-copper-gold (IOCG) deposits, there are common factors among all of these at the lithospheric to crustal scale. All are sited in giant gold provinces controlled by complex fundamental fault or shear zones that follow craton margins or, in the case of most Phanerozoic orogenic giants, define the primary suture zones between tectonic terranes. Giant provinces of IRGS, IOCG, and Carlin-type deposits require melting of metasomatized lithosphere beneath craton margins with ascent of hybrid lamprophyric to granitic magmas and associated heat flux to generate the giant province. The IRGS and IOCG deposits require direct exsolution of volatile-rich magmatic-hydrothermal fluids, whereas the association of such melts with Carlin-type ores is more indirect and enigmatic. Giant orogenic gold provinces show no direct relationship to such magmatism, forming from metamorphic fluids, but show an indirect relationship to lamprophyres that reflect the mantle connectivity of controlling first-order structures. In contrast to their province scale similarities, the different giant gold deposit styles show contrasting critical controls at the district to deposit scale. For orogenic gold deposits, the giants appear to have formed by conjunction of a greater number of parameters to those that control smaller deposits, with resultant geometrical and lithostratigraphic complexity as a guide to their location. There are few giant IRGS due to their inferior fluid-flux systems relative to orogenic gold deposits, and those few giants are essentially preservational exceptions. Many Carlin-type deposits are giants due to the exceptional conjunction of both structural and lithological parameters that caused reactive and permeable rocks, enriched in syngenetic gold, to be located below an impermeable cap along antiformal “trends”. Hydrocarbons probably played an important role in concentrating metal. The supergiant Post-Betze deposit has additional ore zones in strain heterogeneities surrounding the pre-gold Goldstrike stock. All unequivocal IOCG deposits are giant or near-giant deposits in terms of gold-equivalent resources, partly due to economic factors for this relatively poorly understood, low Cu-Au grade deposit type. The supergiant Olympic Dam deposit, the most shallowly formed deposit among the larger IOCGs, probably owes its origin to eruption of volatile-rich hybrid magma at surface, with formation of a large maar and intense and widespread brecciation, alteration and Cu-Au-U deposition in a huge rock volume.

Geoscience Frontiers↗
USGS2019

Arsenic variability and groundwater age in three water supply wells in southeast New Hampshire

Three wells in New Hampshire were sampled bimonthly over three years to evaluate the temporal variability of arsenic concentrations and groundwater age. All samples had measurable concentrations of arsenic throughout the entire sampling period and concentrations in individual wells varied, on average, by more than 7 µg/L. High arsenic concentrations (>10 µg/L) were measured in bedrock wells KFW-87 and SGW-93, consistent with the high pH and low dissolved oxygen typically found in fractured crystalline bedrock aquifers in New Hampshire. Lower arsenic concentrations (<10 µg/L) at well SGW-65 were consistent with lower pH typical of glacial aquifers in New Hampshire.

New Hampshire↗
USGS2023

The drift history of the Dharwar Craton and India from 2.37 Ga to 1.01 Ga with refinements for an initial Rodinia configuration

Coupled paleomagnetic and geochronologic data derived from mafic dykes provide valuable records of continental movement. To reconstruct the Proterozoic paleogeographic history of Peninsular India, we report paleomagnetic directions and U-Pb zircon ages from twenty-nine mafic dykes in the Eastern Dharwar Craton near Hyderabad. Paleomagnetic analysis yielded clusters of directional data that correspond to dyke swarms at 2.37 Ga, 2.22 Ga, 2.08 Ga, 1.89–1.86 Ga, 1.79 Ga, and a previously undated dual polarity magnetization. We report new positive baked contact tests for the 2.08 Ga swarm and the 1.89–1.86 Ga swarm(s), and a new inverse baked contact test for the 2.08 Ga swarm. Our results promote the 2.08 Ga Dharwar Craton paleomagnetic pole (43.1° N, 184.5° E; A95 = 4.3°) to a reliability score of R = 7 and suggest a position for the Dharwar Craton at 1.79 Ga based on a virtual geomagnetic pole (VGP) at 33.0° N, 347.5° E (a95 = 16.9°, k = 221, N = 2). The new VGP for the Dharwar Craton provides support for the union of the Dharwar, Singhbhum, and Bastar Cratons in the Southern India Block by at least 1.79 Ga. Combined new and published northeast-southwest moderate-steep dual polarity directions from Dharwar Craton dykes define a new paleomagnetic pole at 20.6° N, 233.1° E (A95 = 9.2°, N = 18; R = 5). Two dykes from this group yielded 1.05–1.01 Ga 207 Pb/ 206 Pb zircon ages and this range is taken as the age of the new paleomagnetic pole. A comparison of the previously published poles with our new 1.05–1.01 Ga pole shows India shifting from equatorial to higher (southerly) latitudes from 1.08 Ga to 1.01 Ga as a component of Rodinia.

Geoscience Frontiers↗
USGS2000

Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗
USGS2001

A two-dimensional, time-dependent model of suspended sediment transport and bed reworking for continental shelves

A two-dimensional, time-dependent solution to the transport equation is formulated to account for advection and diffusion of sediment suspended in the bottom boundary layer of continental shelves. This model utilizes a semi-implicit, upwind-differencing scheme to solve the advection-diffusion equation across a two-dimensional transect that is configured so that one dimension is the vertical, and the other is a horizontal dimension usually aligned perpendicular to shelf bathymetry. The model calculates suspended sediment concentration and flux; and requires as input wave properties, current velocities, sediment size distributions, and hydrodynamic sediment properties. From the calculated two-dimensional suspended sediment fluxes, we quantify the redistribution of shelf sediment, bed erosion, and deposition for several sediment sizes during resuspension events. The two-dimensional, time-dependent approach directly accounts for cross-shelf gradients in bed shear stress and sediment properties, as well as transport that occurs before steady-state suspended sediment concentrations have been attained. By including the vertical dimension in the calculations, we avoid depth-averaging suspended sediment concentrations and fluxes, and directly account for differences in transport rates and directions for fine and coarse sediment in the bottom boundary layer. A flux condition is used as the bottom boundary condition for the transport equation in order to capture time-dependence of the suspended sediment field. Model calculations demonstrate the significance of both time-dependent and spatial terms on transport and depositional patterns on continental shelves. ?? 2001 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗
USGS2002

Description and comparison of geologic maps with FRAGSTATS - A spatial statistics program

FRAGSTATS is a public-domain GIS implementation of a set of spatial statistics that address a fundamental problem in GIS applications, description and comparison of maps. The spatial statistics from the 1:2,500,000-scale United States geologic map of Nevada, the central United States, and the northeastern United States quantify the differences in complexity and variability between these three geologic terranes. Nevada is defined by a large number of patches of small size and low size variability, whereas the Central area has a small number of patches with smaller relative size variability. All three areas have similar map-unit shape complexity with Nevada having the lowest. Based on the density of edges, the areas can be ranked from highest to lowest, as Nevada, Central, and Northeast. The Shannon diversity index ranks the areas from highest to lowest, as Northeast, Nevada, and Central, but the Shannon evenness index ranks them from highest to lowest, as Northeast, Central, and Nevada. These rankings may reflect the influence of folding in the Northeast and Central areas as opposed to basin and range extension in Nevada. The core areas statistic ranks the areas for spatial accuracy from highest to lowest, as Central, Northeast, and Nevada, with Northeast and Nevada being similar. For a scale comparison, the FRAGSTATS statistics quantify the increased complexity and spatial accuracy that is inherent in going from small- to larger-scale maps. For example for 1:2,500,000-1:500,000-scale maps of Nevada, respectively, the area weighted fractal dimension increase from 1.1 to 1.18, and the total core areas index almost doubles from 39.09 to 63.38. In addition, the fractal dimensions discriminate gross lithology and tectonic terranes. ?? 2002 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗
USGS2001

1r2dinv: A finite-difference model for inverse analysis of two dimensional linear or radial groundwater flow

We have developed a program for inverse analysis of two-dimensional linear or radial groundwater flow problems. The program, 1r2dinv, uses standard finite difference techniques to solve the groundwater flow equation for a horizontal or vertical plane with heterogeneous properties. In radial mode, the program simulates flow to a well in a vertical plane, transforming the radial flow equation into an equivalent problem in Cartesian coordinates. The physical parameters in the model are horizontal or x-direction hydraulic conductivity, anisotropy ratio (vertical to horizontal conductivity in a vertical model, y-direction to x-direction in a horizontal model), and specific storage. The program allows the user to specify arbitrary and independent zonations of these three parameters and also to specify which zonal parameter values are known and which are unknown. The Levenberg-Marquardt algorithm is used to estimate parameters from observed head values. Particularly powerful features of the program are the ability to perform simultaneous analysis of heads from different tests and the inclusion of the wellbore in the radial mode. These capabilities allow the program to be used for analysis of suites of well tests, such as multilevel slug tests or pumping tests in a tomographic format. The combination of information from tests stressing different vertical levels in an aquifer provides the means for accurately estimating vertical variations in conductivity, a factor profoundly influencing contaminant transport in the subsurface. ?? 2001 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗
USGS2002

Identification of lithofacies using Kohonen self-organizing maps

Lithofacies identification is a primary task in reservoir characterization. Traditional techniques of lithofacies identification from core data are costly, and it is difficult to extrapolate to non-cored wells. We present a low-cost automated technique using Kohonen self-organizing maps (SOMs) to identify systematically and objectively lithofacies from well log data. SOMs are unsupervised artificial neural networks that map the input space into clusters in a topological form whose organization is related to trends in the input data. A case study used five wells located in Appleton Field, Escambia County, Alabama (Smackover Formation, limestone and dolomite, Oxfordian, Jurassic). A five-input, one-dimensional output approach is employed, assuming the lithofacies are in ascending/descending order with respect to paleoenvironmental energy levels. To consider the possible appearance of new logfacies not seen in training mode, which may potentially appear in test wells, the maximum number of outputs is set to 20 instead of four, the designated number of lithosfacies in the study area. This study found eleven major clusters. The clusters were compared to depositional lithofacies identified by manual core examination. The clusters were ordered by the SOM in a pattern consistent with environmental gradients inferred from core examination: bind/boundstone, grainstone, packstone, and wackestone. This new approach predicted lithofacies identity from well log data with 78.8% accuracy which is more accurate than using a backpropagation neural network (57.3%). The clusters produced by the SOM are ordered with respect to paleoenvironmental energy levels. This energy-related clustering provides geologists and petroleum engineers with valuable geologic information about the logfacies and their interrelationships. This advantage is not obtained in backpropagation neural networks and adaptive resonance theory neural networks. ?? 2002 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗
USGS2002

VOLATILECALC: A silicate melt-H2O-CO2 solution model written in Visual Basic for excel

We present solution models for the rhyolite-H2O-CO2 and basalt-H2O-CO2 systems at magmatic temperatures and pressures below ~ 5000 bar. The models are coded as macros written in Visual Basic for Applications, for use within MicrosoftR Excel (Office'98 and 2000). The series of macros, entitled VOLATILECALC, can calculate the following: (1) Saturation pressures for silicate melt of known dissolved H2O and CO2 concentrations and the corresponding equilibrium vapor composition; (2) open- and closed-system degassing paths (melt and vapor composition) for depressurizing rhyolitic and basaltic melts; (3) isobaric solubility curves for rhyolitic and basaltic melts; (4) isoplethic solubility curves (constant vapor composition) for rhyolitic and basaltic melts; (5) polybaric solubility curves for the two end members and (6) end member fugacities of H2O and CO2 vapors at magmatic temperatures. The basalt-H2O-CO2 macros in VOLATILECALC are capable of calculating melt-vapor solubility over a range of silicate-melt compositions by using the relationships provided by Dixon (American Mineralogist 82 (1997) 368). The output agrees well with the published solution models and experimental data for silicate melt-vapor systems for pressures below 5000 bar. ?? 2002 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗