Recent developments in the direct-current geoelectrical imaging method

Arc-magmatism and subduction history beneath the Zagros Mountains, Iran: A new report of adakites and geodynamic consequences

We want to develop a dialogue between geophysicists and hydrologists interested in synergistically advancing process based watershed research. We identify recent advances in geophysical instrumentation, and provide a vision for the use of electrical and magnetic geophysical instrumentation in watershed scale hydrology. The focus of the paper is to identify instrumentation that could significantly advance this vision for geophysics and hydrology during the next 3–5 years. We acknowledge that this is one of a number of possible ways forward and seek only to offer a relatively narrow and achievable vision. The vision focuses on the measurement of geological structure and identification of flow paths using electrical and magnetic methods. The paper identifies instruments, provides examples of their use, and describes how synergy between measurement and modelling could be achieved. Of specific interest are the airborne systems that can cover large areas and are appropriate for watershed studies. Although airborne geophysics has been around for some time, only in the last few years have systems designed exclusively for hydrological applications begun to emerge. These systems, such as airborne electromagnetic (EM) and transient electromagnetic (TEM), could revolutionize hydrogeological interpretations. Our vision centers on developing nested and cross scale electrical and magnetic measurements that can be used to construct a three-dimensional (3D) electrical or magnetic model of the subsurface in watersheds. The methodological framework assumes a ‘top down’ approach using airborne methods to identify the large scale, dominant architecture of the subsurface. We recognize that the integration of geophysical measurement methods, and data, into watershed process characterization and modelling can only be achieved through dialogue. Especially, through the development of partnerships between geophysicists and hydrologists, partnerships that explore how the application of geophysics can answer critical hydrological science questions, and conversely provide an understanding of the limitations of geophysical measurements and interpretation. Copyright © 2008 John Wiley & Sons, Ltd.

Advancing process‐based watershed hydrological research using near‐surface geophysics: A vision for, and review of, electrical and magnetic geophysical methods

Low-frequency geoelectrical methods include mainly self-potential, resistivity, and induced polarization techniques, which have potential in many environmental and hydrogeological applications. They provide complementary information to each other and to in-situ measurements. The self-potential method is a passive measurement of the electrical response associated with the in-situ generation of electrical current due to the flow of pore water in porous media, a salinity gradient, and/or the concentration of redox-active species. Under some conditions, this method can be used to visualize groundwater flow, to determine permeability, and to detect preferential flow paths. Electrical resistivity is dependent on the water content, the temperature, the salinity of the pore water, and the clay content and mineralogy. Time-lapse resistivity can be used to assess the permeability and dispersivity distributions and to monitor contaminant plumes. Induced polarization characterizes the ability of rocks to reversibly store electrical energy. It can be used to image permeability and to monitor chemistry of the pore water–minerals interface. These geophysical methods, reviewed in this paper, should always be used in concert with additional in-situ measurements (e.g. in-situ pumping tests, chemical measurements of the pore water), for instance through joint inversion schemes, which is an area of fertile on-going research.

Review: Some low-frequency electrical methods for subsurface characterization and monitoring in hydrogeology

SUMMARY Two automatic ways of estimating the regularization parameter in underdetermined, minimumstructure-type solutions to non-linear inverse problems are compared: the generalized crossvalidation and L-curve criteria. Both criteria provide a means of estimating the regularization parameter when only the relative sizes of the measurement uncertainties in a set of observations are known. The criteria, which are established components of linear inverse theory, are applied to the linearized inverse problem at each iteration in a typical iterative, linearized solution to the non-linear problem. The particular inverse problem considered here is the simultaneous inversion of electromagnetic loop‐loop data for 1-D models of both electrical conductivity and magnetic susceptibility. The performance of each criteria is illustrated with inversions of a variety of synthetic and field data sets. In the great majority of examples tested, both criteria successfully determined suitable values of the regularization parameter, and hence credible models of the subsurface.

https://gif.eos.ubc.ca/sites/default/files/Farquharson_regparam_04.pdf

A comparison of automatic techniques for estimating the regularization parameter in non-linear inverse problems

This paper presents a new methodology for computing a time-frequency map for nonstationary signals using the continuous-wavelet transform (CWT). The conventional method of producing a time-frequency map using the short time Fourier transform (STFT) limits time-frequency resolution by a predefined window length. In contrast, the CWT method does not require preselecting a window length and does not have a fixed time-frequency resolution over the timefrequency space. CWT uses dilation and translation of a wavelet to produce a time-scale map. A single scale encompasses a frequency band and is inversely proportional to the time support of the dilated wavelet. Previous workers have converted a time-scale map into a time-frequency map by taking the center frequencies of each scale. We transform the time-scale map by taking the Fourier transform of the inverse CWT to produce a time-frequency map. Thus, a time-scale map is converted into a time-frequency map in which the amplitudes of individual frequencies rather than frequency bands are represented. We refer to such a map as the time-frequency CWT (TFCWT). We validate our approach with a nonstationary synthetic example and compare the results with the STFT and a typical CWT spectrum. Two field examples illustrate that the TFCWT potentially can be used to detect frequency shadows caused by hydrocarbons and to identify subtle stratigraphic features for reservoir characterization.

http://luminageo.us/papers/Sinha,%20Routh,%20Anno,%20Castagna%20(2005)%20SD%20of%20seismic%20data%20with%20CWT.pdf

Spectral decomposition of seismic data with continuous-wavelet transform

Magnetic susceptibility affects electromagnetic (EM) loop–loop observations in ways that cannot be replicated by conductive, nonsusceptible earth models. The most distinctive effects are negative in‐phase values at low frequencies. Inverting data contaminated by susceptibility effects for conductivity alone can give misleading models: the observations strongly influenced by susceptibility will be underfit, and those less strongly influenced will be overfit to compensate, leading to artifacts in the model. Simultaneous inversion for both conductivity and susceptibility enables reliable conductivity models to be constructed and can give useful information about the distribution of susceptibility in the earth. Such information complements that obtained from the inversion of static magnetic data because EM measurements are insensitive to remanent magnetization.We present an algorithm that simultaneously inverts susceptibility‐affected data for 1D conductivity and susceptibility models. The solution is obtaine...

https://www.eoas.ubc.ca/ubcgif/pubs/papers/geop68-1857.pdf

Simultaneous 1D inversion of loop loop electromagnetic data for magnetic susceptibility and electrical conductivity

Time-lapse electrical resistivity tomography ERT has many practical applications to the study of subsurface properties and processes. When inverting time-lapse ERT data, it is useful to proceed beyond straightforward inversion of data differences andtakeadvantageofthetime-lapsenatureofthedata.Weassess various approaches for inverting and interpreting time-lapse ERTdataanddeterminethattwoapproachesworkwell.Thefirst approachismodelsubtractionafterseparateinversionofthedata from two time periods, and the second approach is to use the inverted model from a base data set as the reference model or prior information for subsequent time periods. We prefer this second approach. Data inversion methodology should be considered when designing data acquisition; i.e., to utilize the second approach, it is important to collect one or more data sets for which the bulk of the subsurface is in a background or relatively unperturbed state.Athird and commonly used approach to time-lapse inversion,invertingthedifferencebetweentwodatasets,localizes the regions of the model in which change has occurred; however, varying noise levels between the two data sets can be problematic. To further assess the various time-lapse inversion approaches,weacquiredfielddatafromacatchmentwithintheDry Creek Experimental Watershed near Boise, Idaho, U.S.A. We combined the complimentary information from individual static ERTinversions,time-lapseERTimages,andavailablehydrologicdatainarobustinterpretationschemetoaidinquantifyingseasonalvariationsinsubsurfacemoisturecontent.

/pdf/application-of-time-lapse-ert-imaging-to-watershed-55fivs82hn.pdf

Application of time-lapse ERT imaging to watershed characterization

Toquantifyperformanceof3Dtime-lapseelectricalresistivity tomography ERT, a sequential injection/withdrawal experiment was designed for monitoring the pump-and-capture remediation of a conductive solute in an unconfined alluvial aquifer. Prior information is incorporated into the inversion procedure via regularization with respect to a reference model according to threeprotocols:1independentregularizationinvolvingasingle reference model, 2 background regularization involving a referencemodelobtainedviainversionofpreinjectiondata,and3 time-lapseregularizationinvolvinganevolvingreferencemodel obtained via inversion of data from previous experimental stages.Emplacementandsequentialwithdrawalofthesoluteisclearly imaged for all protocols. Time-lapse regularization results in greater amounts of model structure, while providing significantcomputationalsavings.ERT-estimatedelectricalconductivity is used to predict solute concentration and solute mass in the aquifer. At any experimental stage, we are able to estimate total solute mass in the aquifer with a maximum accuracy of 60%‐85% depending on regularization protocol and survey geometry.Wealsoestimatethewithdrawnsolutemassforeveryexperimentalstagethechangeinmassbetweenexperimentalstages. Withdrawn mass estimates are more reliable than total mass estimates and do not exhibit systematic underprediction or dependence on regularization protocol. Withdrawn mass estimates areaccurateforchangesinmassbelow2‐4 kgofpotassiumbromide KBr for horizontal and vertical dipole-dipole surveys, respectively. Estimating the withdrawn solute mass does not require background subtraction and, thus, does not require backgrounddata.

Time-lapse ERT monitoring of an injection/withdrawal experiment in a shallow unconfined aquifer

This efficient multiscale method for time-domain waveform tomography incorporates filters that are more efficient than Hamming-window filters. A strategy for choosing optimal frequency bands is proposed to achieve computational efficiency in the time domain. A staggered-grid, explicit finite-difference method with fourth-order accuracy in space and second-order accuracy in time is used for forward modeling and the adjoint calculation. The adjoint method is utilized in inverting for an efficient computation of the gradient directions. In the multiscale approach, multifrequency data and multiple grid sizes are used to overcome somewhat the severe local minima problem of waveform tomography. The method is applied successfully to 1D and 2D heterogeneous models; it can accurately recover low- and high-wavenumber components of the velocity models. The inversion result for the 2D model demonstrates that the multiscale method is computationally efficient and converges faster than a conventional, single-scale method.

/pdf/an-efficient-multiscale-method-for-time-domain-waveform-3kmt1wlz8x.pdf

Partha S. Routh

Papers

Spectral decomposition of seismic data with continuous-wavelet transform

Simultaneous 1D inversion of loop loop electromagnetic data for magnetic susceptibility and electrical conductivity

Application of time-lapse ERT imaging to watershed characterization

Time-lapse ERT monitoring of an injection/withdrawal experiment in a shallow unconfined aquifer

An efficient multiscale method for time-domain waveform tomography