[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Hermans et al., 2016 - Google Patents

Direct prediction of spatially and temporally varying physical properties from time‐lapse electrical resistance data

Hermans et al., 2016

View PDF @Full View
Document ID
16824485199995977029
Author
Hermans T
Oware E
Caers J
Publication year
Publication venue
Water Resources Research

External Links

Snippet

Time‐lapse applications of electrical methods have grown significantly over the last decade. However, the quantitative interpretation of tomograms in terms of physical properties, such as salinity, temperature or saturation, remains difficult. In many applications, geophysical …
Continue reading at agupubs.onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V99/00—Subject matter not provided for in other groups of this subclass
    • G01V99/005—Geomodels or geomodelling, not related to particular measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/12—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with electromagnetic waves
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/38—Processing data, e.g. for analysis, for interpretation, for correction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
    • G01V1/282—Application of seismic models, synthetic seismograms
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/18—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation specially adapted for well-logging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
    • G01V3/083—Controlled source electromagnetic [CSEM] surveying
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/61—Analysis by combining or comparing a seismic data set with other data
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V9/00—Prospecting or detecting by methods not provided for in groups G01V1/00 - G01V8/00
    • G01V9/02—Determining existence or flow of underground water
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V11/00—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/66—Subsurface modeling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30861—Retrieval from the Internet, e.g. browsers

Similar Documents

Publication Publication Date Title
Hermans et al. Direct prediction of spatially and temporally varying physical properties from time‐lapse electrical resistance data
Hermans et al. Uncertainty in training image‐based inversion of hydraulic head data constrained to ERT data: Workflow and case study
Hermans et al. Uncertainty quantification of medium‐term heat storage from short‐term geophysical experiments using Bayesian evidential learning
Zhu et al. Analysis of hydraulic tomography using temporal moments of drawdown recovery data
Doherty et al. Use of paired simple and complex models to reduce predictive bias and quantify uncertainty
Hinnell et al. Improved extraction of hydrologic information from geophysical data through coupled hydrogeophysical inversion
Li et al. Coupled time‐lapse full‐waveform inversion for subsurface flow problems using intrusive automatic differentiation
Moysey et al. A framework for inferring field‐scale rock physics relationships through numerical simulation
Cardiff et al. Hydraulic conductivity imaging from 3‐D transient hydraulic tomography at several pumping/observation densities
Irving et al. Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities
Cardiff et al. A field proof‐of‐concept of aquifer imaging using 3‐D transient hydraulic tomography with modular, temporarily‐emplaced equipment
Huang et al. Robustness of joint interpretation of sequential pumping tests: Numerical and field experiments
Cardiff et al. Bayesian inversion for facies detection: An extensible level set framework
Fienen et al. An interactive Bayesian geostatistical inverse protocol for hydraulic tomography
Liu et al. Large‐scale inverse modeling with an application in hydraulic tomography
Li et al. Geostatistical inverse modeling of transient pumping tests using temporal moments of drawdown
Tso et al. On the field estimation of moisture content using electrical geophysics: The impact of petrophysical model uncertainty
Singha et al. Hydrogeophysical tracking of three‐dimensional tracer migration: The concept and application of apparent petrophysical relations
Pollock et al. Fully coupled hydrogeophysical inversion of synthetic salt tracer experiments
Chen et al. Three‐dimensional Bayesian geostatistical aquifer characterization at the Hanford 300 Area using tracer test data
Valstar et al. A representer‐based inverse method for groundwater flow and transport applications
Castagna et al. A Bayesian approach for inversion of hydraulic tomographic data
Tavakoli et al. Comparison of ensemble filtering algorithms and null‐space Monte Carlo for parameter estimation and uncertainty quantification using CO2 sequestration data
Wilson et al. Data assimilation and bathymetric inversion in a two‐dimensional horizontal surf zone model
Riva et al. Role of model selection criteria in geostatistical inverse estimation of statistical data‐and model‐parameters