scholarly journals Spectral Induced Polarization of limestones: time domain field data, frequency domain laboratory data and physicochemical rock properties

2019 ◽  
Author(s):  
Sara Johansson ◽  
Anders Lindskog ◽  
Gianluca Fiandaca ◽  
Torleif Dahlin
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Field Data ◽  
Induced Polarization ◽  
Coarse Grained ◽  
Laboratory Measurements ◽  
Spectral Parameters ◽  
The Core ◽  
Core Samples ◽  
Wide Range

Summary With advances in data acquisition and processing methods, spectral inversion of time domain induced polarization (IP) data is becoming more common. Geological interpretation of inverted spectral parameters, for instance Cole-Cole parameters, often relies on results from systematic laboratory measurements. These are most often carried out with frequency domain systems on sandstone samples. However, the two different methods of measuring the spectral IP response differ in both measurement technique and scale. One of the main objectives of the current study is, thus, to perform a direct comparison of inverted spectral parameters from time domain IP field data with frequency domain IP spectra from laboratory measurements. To achieve this, field measurements were carried out before a ∼50 m long rock core was drilled down along one of the measurement lines. Solid parts of the core were vacuum-sealed in plastic bags to preserve the natural groundwater in the samples, after which the core samples were measured with frequency domain spectral IP in laboratory. The results showed that the inverted Cole-Cole parameters closest to the borehole were comparable to the IP spectra measured at the core samples, despite differences in measurement techniques and scale. The field site chosen for the investigation was a limestone succession spanning over a well-known lithological boundary (the Cretaceous—Paleogene boundary). Little is known in previous research about varying spectral IP responses in limestones, and an additional objective of this study was, therefore, to investigate possible sources of these variations in the laboratory. The IP spectra were interpreted in light of measured lithological and physicochemical properties. The carbonate texture differed strongly across the Cretaceous—Paleogene boundary from fine-grained calcareous mudstone (Cretaceous) to more well-lithified and coarse-grained wackestone and packstone (Paleogene). Both laboratory and field spectral IP results showed that these differences cause a large shift in measured bulk conductivity across the boundary. Furthermore, carbonate mound structures with limestone grains consisting mainly of ∼cylindrical bryozoan fragments could be identified in the inverted Cole-Cole parameters as anomalies with high relaxation times. A general conclusion of this work is that limestones can give rise to a wide range of spectral responses. The carbonate texture and the dominant shape of the fossil grains seem to have important control over the electrical properties of the material. A main conclusion is that the inverted Cole-Cole parameters from the field scale time domain IP tomography were comparable to the magnitude and shape of frequency domain IP spectra at low frequencies. This opens up large interpretational possibilities, as the comprehensive knowledge about relationships between lithological properties and IP spectra from laboratory research can be used for field data interpretation.

Spectral induced polarization parameters as determined through time‐domain measurements

Geophysics ◽  
1984 ◽  
Vol 49 (11) ◽  
pp. 1993-2003 ◽  
Author(s):  
Ian M. Johnson
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Field Trials ◽  
Induced Polarization ◽  
Polarization Data ◽  
Forward Solution ◽  
Spectral Parameters ◽  
Impedance Model ◽  
Measurement And Analysis ◽  
The Time Domain

A method for the extraction of Cole-Cole spectral parameters from time‐domain induced polarization data is demonstrated. The instrumentation required to effect the measurement and analysis is described. The Cole-Cole impedance model is shown to work equally well in the time domain as in the frequency domain. Field trials show the time‐domain method to generate spectral parameters consistent with those generated by frequency‐domain surveys. This is shown to be possible without significant alteration to field procedures. Cole-Cole time constants of up to 100 s are shown to be resolvable given a transmitted current of a 2 s pulse‐time. The process proves to have added usefulness as the Cole-Cole forward solution proves an excellent basis for quantifying noise in the measured decay.

A special circumstance of airborne induced‐polarization measurements

Geophysics ◽  
1996 ◽  
Vol 61 (1) ◽  
pp. 66-73 ◽  
Author(s):  
Richard S. Smith ◽  
Jan Klein
Keyword(s):  
Time Domain ◽  
Eddy Currents ◽  
High Arctic ◽  
Induced Polarization ◽  
Laboratory Measurements ◽  
Dielectric Polarization ◽  
Special Circumstance ◽  
Polarization Measurements ◽  
Airborne Electromagnetic

Airborne induced‐polarization (IP) measurements can be obtained with standard time‐domain airborne electromagnetic (EM) equipment, but only in the limited circumstances when the ground is sufficiently resistive that the normal EM response is small and when the polarizability of the ground is sufficiently large that the IP response can dominate the EM response. Further, the dispersion in conductivity must be within the bandwidth of the EM system. One example of what is hypothesized to be IP effects are the negative transients observed on a GEOTEM® survey in the high arctic of Canada. The dispersion in conductivity required to explain the data is very large, but is not inconsistent with some laboratory measurements. Whether the dispersion is caused by an electrolytic or dielectric polarization is not clear from the limited ground follow‐up, but in either case the polarization can be considered to be induced by eddy currents associated with the EM response of the ground. If IP effects are the cause of the negative transients in the GEOTEM data, then the data can be used to estimate the polarizabilities in the area.

METHODS TO QUANTITATE ATRIAL ELECTRICAL ACTIVITY USING ELECTROGRAMS ACQUIRED DURING ATRIAL FIBRILLATION

2014 ◽  
Vol 26 (06) ◽  
pp. 1430001
Author(s):  
Edward J. Ciaccio ◽  
Angelo B. Biviano ◽  
Hasan Garan
Keyword(s):  
Atrial Fibrillation ◽  
Electrical Activity ◽  
Frequency Domain ◽  
Time Domain ◽  
Periodic Pattern ◽  
Spectral Parameters ◽  
Domain Method ◽  
Frequency Domain Methods ◽  
Atrial Electrograms ◽  
Fractionated Electrograms

Herein, commonly used quantitative bioengineering methods that have been developed to analyze fractionated electrograms recorded from the surface of the atria during atrial fibrillation (AF) are described. Techniques were categorized as time-domain and frequency-domain methods. The main time-domain method is peak counting. Its variations based on preprocessing and thresholding are discussed. The main frequency-domain method is spectral analysis. Two spectral estimators, the discrete Fourier transform (DFT) and the new spectral estimator (NSE) are described. The ability of each estimator to detect the main periodic component of fractionated atrial electrograms is compared. Several spectral parameters that are used for analysis of atrial electrograms including the dominant frequency (DF), dominant amplitude (DA) and mean spectral profile (MP) are defined. Mean values of these parameters are compared in paroxysmal versus persistent AF fractionated electrograms based upon the results of several studies. Time-domain methods are shown to work best for analysis with deterministic, not fractionated atrial electrograms. For fractionated atrial electrograms, frequency-domain methods are often used. The DF, DA and MP spectral parameters are significantly different in paroxysmal versus longstanding persistent AF recordings. The DF and the DA are significantly higher, and the MP is significantly lower, in persistent AF electrogram recordings. The higher DF and DA parameter values reflect substrate remodeling in persistent AF, which increases the stability of the electrical activation pattern. The lower MP value in persistent AF reflects the lower spectral noise floor, indicative of a less complex and more periodic pattern of electrical activity.

scholarly journals Photosynthesis dynamics and regulation sensed in the frequency domain

2021 ◽  
Author(s):  
Ladislav Nedbal ◽  
Dušan Lazár
Keyword(s):  
Experimental Data ◽  
Frequency Domain ◽  
Time Domain ◽  
Fluorescence Emission ◽  
Plant Responses ◽  
Wide Range ◽  
Harmonic Modulation ◽  
Photosynthetic Regulation ◽  
Time Domain Response ◽  
Changing Light

AbstractFoundations of photosynthesis research have been established mainly by studying the response of plants to changing light, typically to sudden exposure to a constant light intensity after a dark acclimation or to light flashes. This approach remains valid and powerful, but can be limited by requiring dark acclimation prior to time-domain measurements and often assumes that rate constants determining the photosynthetic response do not change between the dark- and light-acclimation.We present experimental data and a mathematical model demonstrating that these limits can be overcome by measuring plant responses to sinusoidally modulated light of varying frequency. By its nature, such frequency domain characterization is performed in light-acclimated plants with no need for prior dark acclimation. Amplitudes, phase shifts and upper harmonic modulation extracted from the data for a wide range of frequencies can target different kinetic domains and regulatory feedbacks. The occurrence of upper harmonic modulation reflects non-linear phenomena, including photosynthetic regulation. To support these claims, we present a frequency and time domain response in chlorophyll fluorescence emission of the green alga Chlorella sorokiniana in the frequency range 1000 – 0.001 Hz. Based on these experimental data and on numerical as well as analytical mathematical models, we propose that the frequency domain measurements can become a versatile new tool in plant sensing.One sentence summaryIt is proposed to characterize photosynthesis in the frequency domain without the need for dark adaptation and, thus, without assumptions about the dark-to-light transition.

scholarly journals Innovative Multi-Site Photoplethysmography Analysis for Quantifying Pulse Amplitude and Timing Variability Characteristics in Peripheral Arterial Disease

2018 ◽  
Author(s):  
Michael Bentham ◽  
Gerard Stansby ◽  
John Allen
Keyword(s):  
Peripheral Arterial Disease ◽  
Frequency Domain ◽  
Time Domain ◽  
Domain Analysis ◽  
Arterial Disease ◽  
Timing Variability ◽  
Wide Range ◽  
Healthy Control ◽  
The Time Domain ◽  
Peripheral Arterial

Photoplethysmography (PPG) is a simple-to-perform vascular optics measurement technique that can detect changes in blood volume in the microvascular tissue bed. Beat-to-beat analysis of the PPG waveform enables the study of the variability of pulse features such as amplitude and pulse arrival time (PAT), and when quantified in the time and frequency domains, has considerable potential to shed light on perfusion changes associated with peripheral arterial disease (PAD). In this pilot study innovative multi-site bilateral finger and toe PPG recordings from 43 healthy control subjects and 31 PAD subjects were compared (recordings each at least 5 minutes, collected in a warm temperature-controlled room). Beat-to-beat normalized amplitude and PAT variability was then quantified in the time-domain using SD and IQR measures and in the frequency-domain bilaterally using Magnitude Squared Coherence (MSC). Significantly reduced normalized amplitude variability (healthy control 0.0384 (IQR 0.0217-0.0744) vs PAD 0.0160 (0.0080-0.0338) (p<0.001) and significantly increased PAT variability (healthy control 0.0063 (0.0052-0.0086) vs PAD 0.0093 (0.0078-0.0144) (p<0.001) was demonstrated in PAD using the time-domain analysis. Frequency-domain analysis demonstrated significantly lower MSC values across a range of frequency bands for PAD patients. These changes suggest a loss of right-to-left body side coherence and cardiovascular control in PAD. This study has also demonstrated the feasibility of using these measurement and analysis methods in studies investigating multi-site PPG variability for a wide range of cardiac and vascular patient groups.

scholarly journals An Adaptive Spectral Kurtosis Method Based on Optimal Filter

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Yanli Yang ◽  
Ting Yu
Keyword(s):  
Fault Diagnosis ◽  
Frequency Domain ◽  
Time Domain ◽  
Experimental Results ◽  
Bearing Fault ◽  
Spectral Kurtosis ◽  
Bearing Fault Diagnosis ◽  
The Core ◽  
Factors Influencing ◽  
The Time Domain

As a useful tool to detect protrusion buried in signals, kurtosis has a wide application in engineering, for example, in bearing fault diagnosis. Spectral kurtosis (SK) can further indicate the presence of a series of transients and their locations in the frequency domain. The factors influencing kurtosis values are first analyzed, leading to the conclusion that amplitude, not the frequency of signals, and noise make major contribution to kurtosis values. It is helpful to detect impulsive components if the components with big amplitude are removed from composite signals. Based on this cognition, an adaptive SK algorithm is proposed in this paper. The core steps of the proposed SK algorithm are to find maxima, add window around maxima, merge windows in the frequency domain, and then filter signals according to the merged window in the time domain. The parameters of the proposed SK algorithm are varying adaptively with signals. Some experimental results are presented to demonstrate the effectiveness of the proposed algorithm.

Automating the pre-processing of time-domain induced polarization data using machine learning

2020 ◽  
Author(s):  
Adrian S. Barfod* ◽  
Jakob Juul Larsen
Keyword(s):  
Machine Learning ◽  
Time Domain ◽  
Induced Polarization ◽  
Geophysical Data ◽  
Neural Net ◽  
Earth System ◽  
Polarization Data ◽  
The Earth ◽  
Time Modeling ◽  
Wide Range

<p>Exploring and studying the earth system is becoming increasingly important as the slow depletion of natural resources ensues. An important data source is geophysical data, collected worldwide. After gathering data, it goes through vigorous quality control, pre-processing, and inverse modelling procedures. Such procedures often have manual components, and require a trained geophysicist who understands the data, in order to translate it into useful information regarding the earth system. The sheer amounts of geophysical data collected today makes manual approaches impractical. Therefore, automating as much of the workflow related to geophysical data as possible, would allow novel opportunities such as fully automated geophysical monitoring systems, real-time modeling during data collection, larger geophysical data sets, etc.</p><p>Machine learning has been proposed as a tool for automating workflows related to geophysical data. The field of machine learning encompasses multiple tools, which can be applied in a wide range of geophysical workflows, such as pre-processing, inverse modeling, data exploration etc.</p><p>We present a study where machine learning is applied to automate the time domain induced polarization geophysical workflow. Such induced polarization data requires pre-processing, which is manual in nature. One of the pre-processing steps is that a trained geophysicist inspects the data, and removes so-called non-geologic signals, i.e. noise, which does not represent geological variance. Specifically, a real-world case from Grindsted Denmark is presented. Here, a time domain induced polarization survey was conducted containing seven profiles. Two lines were manually processed and used for supervised training of an artificial neural network. The neural net then automatically processed the remaining profiles of the survey, with satisfactory results. Afterwards, the processed data was inverted, yielding the induced polarization parameters respective to the Cole-Cole model. We discuss the limitations and optimization steps related to training such a classification network.</p>

scholarly journals Spectral induced polarization: frequency domain versus time domain laboratory data

2021 ◽  
Vol 225 (3) ◽  
pp. 1982-2000
Author(s):  
Tina Martin ◽  
Konstantin Titov ◽  
Andrey Tarasov ◽  
Andreas Weller
Keyword(s):  
Data Quality ◽  
Frequency Domain ◽  
Time Domain ◽  
Numerical Models ◽  
Laboratory Data ◽  
Induced Polarization ◽  
Frequency Range ◽  
Relaxation Time Distribution ◽  
Spectral Content ◽  
Test Circuit

SUMMARY Spectral information obtained from induced polarization (IP) measurements can be used in a variety of applications and is often gathered in frequency domain (FD) at the laboratory scale. In contrast, field IP measurements are mostly done in time domain (TD). Theoretically, the spectral content from both domains should be similar. In practice, they are often different, mainly due to instrumental restrictions as well as the limited time and frequency range of measurements. Therefore, a possibility of transition between both domains, in particular for the comparison of laboratory FD IP data and field TD IP results, would be very favourable. To compare both domains, we conducted laboratory IP experiments in both TD and FD. We started with three numerical models and measurements at a test circuit, followed by several investigations for different wood and sandstone samples. Our results demonstrate that the differential polarizability (DP), which is calculated from the TD decay curves, can be compared very well with the phase of the complex electrical resistivity. Thus, DP can be used for a first visual comparison of FD and TD data, which also enables a fast discrimination between different samples. Furthermore, to compare both domains qualitatively, we calculated the relaxation time distribution (RTD) for all data. The results are mostly in agreement between both domains, however, depending on the TD data quality. It is striking that the DP and RTD results are in better agreement for higher data quality in TD. Nevertheless, we demonstrate that IP laboratory measurements can be carried out in both TD and FD with almost equivalent results. The RTD enables a good comparability of FD IP laboratory data with TD IP field data.

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