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At least 127 records · Page 7Linked to original sources
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↗
USGS2008

Northeast storms ranked by wind stress and wave-generated bottom stress observed in Massachusetts Bay, 1990-2006

Along the coast of the northeastern United States, strong winds blowing from the northeast are often associated with storms called northeasters, coastal storms that strongly influence weather. In addition to effects caused by wind stress, the sea floor is affected by bottom stress associated with these storms. Bottom stress caused by orbital velocities associated with surface waves integrated over the duration of a storm is a metric of storm strength at the sea floor. Near-bottom wave-orbital velocities calculated by using measurements of significant wave height and dominant wave period and the parametric spectral method described in Wiberg and Sherwood [Wiberg, P.L., Sherwood, C.R. Calculating wave-generated bottom orbital velocities from surface wave parameters. Computers in Geosciences, in press] compared well with observations in Massachusetts Bay. Integrated bottom-wave stress (called IWAVES), calculated at 30 m water depth, and a companion storm-strength metric, integrated surface wind stress at 10 m (called IWINDS), are used to provide an overview of the strength, frequency, and timing of large storms in Massachusetts Bay over a 17-year period from January 1990 through December 2006. These new metrics reflect both storm duration and intensity. Northeast storms were the major cause of large waves in Massachusetts Bay because of the long fetch to the east: of the strongest 10% of storms (n=38) ranked by IWAVES, 22 had vector-averaged wind stress from the northeast quadrant. The Blizzard of December 1992, the Perfect Storm of October 1991, and a December 2003 storm were the strongest three storms ranked by IWAVES and IWINDS, and all were northeasters. IWAVES integrated over the winter season (defined as October-May) ranged by about a factor of 11; the winters with the highest integrated IWAVES were 1992-1993 and 2004-2005 and the winter with the lowest integrated IWAVES was 2001-2002. May 2005 was the only month in the 17-year record that two of the nine strongest northeast storms ranked by IWINDS occurred in the same month or year; these were also the only storms of the nine strongest northeast storms to occur in the spring.

Massachusetts Bay↗
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↗
USGS2003

Comparison of approaches for simulating reactive solute transport involving organic degradation reactions by multiple terminal electron acceptors

Reactive solute transport models are useful tools for analyzing complex geochemical behavior resulting from biodegradation of organic compounds by multiple terminal electron acceptors (TEAPs). The usual approach of simulating the reactions of multiple TEAPs by an irreversible Monod rate law was compared with simulations that assumed a partial local equilibrium or kinetically controlled reactions subject to the requirement that the Gibbs free energy of reaction (Δ G) was either less than zero or less than a threshold value. Simulations were performed using a single organic substrate and O 2 , FeOOH, SO 4 -2 and CO 2 as the terminal electron acceptors. It was assumed that the organic substrate was slowly and completely fermented to CO 2 and H 2 and the H 2 was oxidized by the TEAPs. Simulations using the Monod approach showed that this irreversible rate law forced the reduction of both FeOOH and CO 2 to proceed even when Δ G was positive. This resulted in an over prediction in amount of FeOOH reduced to Fe(II) in parts of the domain and it resulted in large errors in pH. Simulations using mass action kinetics agreed with equilibrium simulations for the case of large rate constants. The extent of reductive dissolution of FeOOH was strongly dependent on the thermodynamic stability of the FeOOH phase. Transport simulations performed assuming that the reactions of the TEAPs stopped when Δ G exceeded a threshold value showed that only simulated H 2 concentrations were affected if the threshold value was the same for each TEAP. Simulated H2 concentrations were controlled by the fastest reaction of the TEAP, but it was common for reactions to occur concomitantly rather than sequentially.

Computers & Geosciences↗
USGS2003

Modeling Np and Pu transport with a surface complexation model and spatially variant sorption capacities: Implications for reactive transport modeling and performance assessments of nuclear waste disposal sites

One-dimensional (1D) geochemical transport modeling is used to demonstrate the effects of speciation and sorption reactions on the ground-water transport of Np and Pu, two redox-sensitive elements. Earlier 1D simulations (Reardon, 1981) considered the kinetically limited dissolution of calcite and its effect on ion-exchange reactions (involving 90 Sr, Ca, Na, Mg and K), and documented the spatial variation of a 90 Sr partition coefficient under both transient and steady-state chemical conditions. In contrast, the simulations presented here assume local equilibrium for all reactions, and consider sorption on constant potential, rather than constant charge, surfaces. Reardon's (1981) seminal findings on the spatial and temporal variability of partitioning (of 90 Sr) are reexamined and found partially caused by his assumption of a kinetically limited reaction. In the present work, sorption is assumed the predominant retardation process controlling Pu and Np transport, and is simulated using a diffuse-double-layer-surface-complexation (DDLSC) model. Transport simulations consider the infiltration of Np- and Pu-contaminated waters into an initially uncontaminated environment, followed by the cleanup of the resultant contamination with uncontaminated water. Simulations are conducted using different spatial distributions of sorption capacities (with the same total potential sorption capacity, but with different variances and spatial correlation structures). Results obtained differ markedly from those that would be obtained in transport simulations using constant K d , Langmuir or Freundlich sorption models. When possible, simulation results (breakthrough curves) are fitted to a constant K d advection–dispersion transport model and compared. Functional differences often are great enough that they prevent a meaningful fit of the simulation results with a constant K d (or even a Langmuir or Freundlich) model, even in the case of Np, a weakly sorbed radionuclide under the simulation conditions. Functional behaviors that cannot be fit include concentration trend reversals and radionuclide desorption spikes. Other simulation results are fit successfully but the fitted parameters ( K d and dispersivity) vary significantly depending on simulation conditions (e.g. “infiltration” vs. “cleanup” conditions). Notably, an increase in the variance of the specified sorption capacities results in a marked increase in the dispersion of the radionuclides. The results presented have implications for the simulation of radionuclide migration in performance assessments of nuclear waste-disposal sites, for the future monitoring of those sites, and more generally for modeling contaminant transport in ground-water environments.

Computers & Geosciences↗
USGS2003

A Visual Basic program to classify sediments based on gravel-sand-silt-clay ratios

Nomenclature describing size distributions is important to geologists because grain size is the most basic attribute of sediments. Traditionally, geologists have divided sediments into four size fractions that include gravel, sand, silt, and clay, and classified these sediments based on ratios of the various proportions of the fractions. Definitions of these fractions have long been standardized to the grade scale described by Wentworth (1922), and two main classification schemes have been adopted to describe the approximate relationship between the size fractions. Specifically, according to the Wentworth grade scale gravel-sized particles have a nominal diameter of ⩾2.0 mm; sand-sized particles have nominal diameters from <2.0 mm to ⩾62.5 μm; silt-sized particles have nominal diameters from <62.5 to ⩾4.0 μm; and clay is <4.0 μm. As for sediment classification, most sedimentologists use one of the systems described either by Shepard (1954) or Folk (1954, 1974). The original scheme devised by Shepard (1954) utilized a single ternary diagram with sand, silt, and clay in the corners to graphically show the relative proportions among these three grades within a sample. This scheme, however, does not allow for sediments with significant amounts of gravel. Therefore, Shepard's classification scheme (Fig. 1) was subsequently modified by the addition of a second ternary diagram to account for the gravel fraction (Schlee, 1973). The system devised by Folk (1954, 1974) is also based on two triangular diagrams (Fig. 2), but it has 23 major categories, and uses the term mud (defined as silt plus clay). The patterns within the triangles of both systems differ, as does the emphasis placed on gravel. For example, in the system described by Shepard, gravelly sediments have more than 10% gravel; in Folk's system, slightly gravelly sediments have as little as 0.01% gravel. Folk's classification scheme stresses gravel because its concentration is a function of the highest current velocity at the time of deposition, together with the maximum grain size of the detritus that is available; Shepard's classification scheme emphasizes the ratios of sand, silt, and clay because they reflect sorting and reworking (Poppe et al., 2000).

Computers & Geosciences↗
USGS1996

A model of Precambrian geology of Kansas derived from gravity and magnetic data

The fabric of the Precambrian geology of Kansas is revealed through inversion of gravity and magnetic data to pseudo-lithology. There are five main steps in the inversion process: (1) reduction of potential-field data to a horizontal plane in the wavenumber domain; (2) separation of the residual anomaly of interest from the regional background, where an assumption is made that the regional anomaly could be represented by some order of polynomial; (3) subtraction of the signal due to the known topography on the Phanerozoic/Precambrian boundary from the residual anomaly (we assume what is left at this stage are the signals due to lateral variation in the Precambrian lithology); (4) inversion of the residual anomaly in the wavenumber domain to density and magnetization distribution in the top part of the Precambrian constrained by the known geologic information; (5) derivation of pseudo-lithology by characterization of density and magnetization. The boundary between the older Central Plains Province to the north and the Southern Granite-Rhyolite Province to the south is clearly delineated. The Midcontinent Rift System appears to widen in central Kansas and involve a considerable portion of southern Kansas. Lithologies in southwestern Kansas appear to change over fairly small areas and include mafic rocks which have not been encountered in drill holes. The texture of the potential field data from southwestern Kansas suggests a history of continental growth by broad extension. Copyright ?? 1996 Elsevier Science Ltd.

Computers & Geosciences↗
USGS1997

An interactive program for computer-aided map design, display, and query: EMAPKGS2

EMAPKGS2 is a user-friendly, PC-based electronic mapping tool for use in hydrogeologic exploration and appraisal. EMAPKGS2 allows the analyst to construct maps interactively from data stored in a relational database, perform point-oriented spatial queries such as locating all wells within a specified radius, perform geographic overlays, and export the data to other programs for further analysis. EMAPKGS2 runs under Microsoft?? Windows??? 3.1 and compatible operating systems. EMAPKGS2 is a public domain program available from the Kansas Geological Survey. EMAPKGS2 is the centerpiece of WHEAT, the Windows-based Hydrogeologic Exploration and Appraisal Toolkit, a suite of user-friendly Microsoft?? Windows??? programs for natural resource exploration and management. The principal goals in development of WHEAT have been ease of use, hardware independence, low cost, and end-user extensibility. WHEAT'S native data format is a Microsoft?? Access?? database. WHEAT stores a feature's geographic coordinates as attributes so they can be accessed easily by the user. The WHEAT programs are designed to be used in conjunction with other Microsoft?? Windows??? software to allow the natural resource scientist to perform work easily and effectively. WHEAT and EMAPKGS have been used at several of Kansas' Groundwater Management Districts and the Kansas Geological Survey on groundwater management operations, groundwater modeling projects, and geologic exploration projects. ?? 1997 Elsevier Science Ltd.

Computers & Geosciences↗
USGS1997

Time-series animation techniques for visualizing urban growth

Time-series animation is a visually intuitive way to display urban growth. Animations of landuse change for the Baltimore-Washington region were generated by showing a series of images one after the other in sequential order. Before creating an animation, various issues which will affect the appearance of the animation should be considered, including the number of original data frames to use, the optimal animation display speed, the number of intermediate frames to create between the known frames, and the output media on which the animations will be displayed. To create new frames between the known years of data, the change in each theme (i.e. urban development, water bodies, transportation routes) must be characterized and an algorithm developed to create the in-between frames. Example time-series animations were created using a temporal GIS database of the Baltimore-Washington area. Creating the animations involved generating raster images of the urban development, water bodies, and principal transportation routes; overlaying the raster images on a background image; and importing the frames to a movie file. Three-dimensional perspective animations were created by draping each image over digital elevation data prior to importing the frames to a movie file.

Computers & Geosciences↗
USGS1997

The future of scientific communication in the earth sciences: The impact of the internet

Publication on paper of research results following peer-review and editing has been the accepted means of scientific communication for several centuries. Today, the continued growth in the volume of scientific literature, the increased unit costs of archiving paper publications, and the rapidly increasing power and availability of electronic technology are creating tremendous pressures on traditional scientific communication. The earth sciences are not immune from these pressures, and the role of the traditional publication as the primary means of communication is rapidly changing. Electronic publications and network technology are radically altering the relationship between interpretative result and the underlying data. Earth science research institutions, including the Kansas Geological Survey, are experimenting with new forms of on-line publication that assure broad access to research and data and improve application of research results to societal problems. ?? 1997 Elsevier Science Ltd.

Computers & Geosciences↗
USGS1997

GSLIB-style programs for discriminant analysis and regionalized classification

Discriminant analysis is a statistical technique used to predict the group membership of a set of multivariate observations, each of which is assumed to arise from one of a set of distinct classes or groups. Each group is characterized by a certain distribution in multivariate space, and group allocations are based on the similarity of each sample to each group. Assuming multivariate normality, generalized distance measures based on the squared Mahalanobis distance from each sample to each group centroid arise as the natural measure of similarity. One can allocate samples to groups either on the basis of minimum generalized distance or, equivalently, maximum posterior probability of group membership. In earth science applications samples are often associated with geographic locations. In this situation regionalized classification can be used to produce a map representing group membership throughout the sampled domain. This can be accomplished by interpolating either generalized distances or membership probabilities from sample locations to regularly spaced grid nodes and comparing resulting grids to produce a classification map. This paper presents a set of GSLIB-style FORTRAN programs for performing discriminant analysis and regionalized classification. The program disco performs discriminant analysis and the programs xmd2cls and prb2cls combine interpolated distances and probabilities, respectively, to create a grid of predicted classifications. In addition, the utility program colbind allows the user to combine selected columns from different GSLIB-style data files into one file. ?? 1997 Elsevier Science Ltd.

Computers & Geosciences↗