scholarly journals Use of apparent thickness for preprocessing of low-frequency electromagnetic data in inversion-based multibarrier evaluation workflow

2018 ◽  
Author(s):  
Saad Omar ◽  
Dzevat Omeragic
Keyword(s):  
Low Frequency ◽  
Electromagnetic Data ◽  
Apparent Thickness

scholarly journals Geomagnetic anomaly associated with Fukushima earthquake on February 13th, 2021

2021 ◽  
Vol 331 ◽  
pp. 07012
Author(s):  
Cipta Ramadhani ◽  
Bulkis Kanata ◽  
Abdullah Zainuddin ◽  
Rosmaliati ◽  
Teti Zubaidah
Keyword(s):  
Data Processing ◽  
Geomagnetic Field ◽  
Field Data ◽  
Low Frequency ◽  
Earthquake Precursors ◽  
Polarization Ratio ◽  
Magnetic Polarization ◽  
Central Frequency ◽  
Electromagnetic Data ◽  
Geomagnetic Anomaly

In this study, we performed research on electromagnetic anomalies related to earthquakes as early signs (precursors) that occurred in Fukushima, Japan on February 13th, 2021. The research focused on the utilization of geomagnetic field data which was derived from the Kakioka (KAK), Kanoya (KNY), and Memambetsu (MMB) observatories, particularly in the ultra-low frequency (ULF) to detect earthquake precursors. The method of electromagnetic data processing was conducted by applying a polarization ratio. In addition, we improved the methodology by splitting the ULF data (which ranged from 0.01-0.1 Hz) into 9 central frequencies and picking up the highest value from each central frequency to get the polarization ratio. The anomaly of magnetic polarization was identified 2-3 weeks before the mainshock in a narrowband frequency in the range of 0.04-0.05 Hz.

Amplitude and phase correction of helicopter EM data

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. F119-F126 ◽  
Author(s):  
Yusen Ley-Cooper ◽  
James Macnae
Keyword(s):  
Half Space ◽  
Low Frequency ◽  
Earth Model ◽  
Data Sets ◽  
High Frequencies ◽  
Electromagnetic Data ◽  
Historic Data ◽  
Case Data ◽  
Best Fit ◽  
Deep Sediments

We aim to develop a quantitative method for recalibration of historic helicopter electromagnetic data sets. Recent research has shown that frequency-domain helicopter electromagnetic data collected over a conductive half-space such as calm seawater can be used to correct system calibration errors. However, most historic surveys consist only of data collected over land, where the conductive half-space assumption is rarely justified. We estimate the required recalibration parameters by analyzing systematic misfits in the inversion of statistically chosen measures of historic data. Our method requires the identification, within the survey area, of a zone of conductive responses that are reasonably uniform. From this zone, a set of altitude-corrected median responses are estimated. These are inverted using geologically specifiedconstraints to obtain a best-fit layered earth model. Systematic inconsistencies between the median measured altitude and the inverted depth to surface are attributed to altitude error. Remaining frequency-dependent fitting errors are assumed to be the calibration errors. We tested the method with partial success on helicopter electromagnetic data sets collected over uniform deep sediments where seawater data were also available and two different inland surveys over multiple lithologies in one general area. At high frequencies, our method works reliably. Recalibration of low-frequency data is not possible if the area used as a reference consists of moderate or poor conductors. In this case, data amplitudes are small and are greatly affected by imperfect drift and magnetic susceptibility corrections. Historic helicopter electromagnetic data may require amplitude rescaling up to 20%–30%, with phase shifts of up to 3°.

Decomposition of electromagnetic fields into upgoing and downgoing components

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. G211-G223 ◽  
Author(s):  
Lasse Amundsen ◽  
Lars Løseth ◽  
Rune Mittet ◽  
Svein Ellingsrud ◽  
Bjørn Ursin
Keyword(s):  
Synthetic Data ◽  
Low Frequency ◽  
Real Data ◽  
Sea Surface ◽  
Linear Phase ◽  
Electric Permittivity ◽  
The Real ◽  
Electromagnetic Data ◽  
Electromagnetic Measurements ◽  
Em Field

This paper gives a unified treatment of electromagnetic (EM) field decomposition into upgoing and downgoing components for conductive and nonconductive media, where the electromagnetic data are measured on a plane in which the electric permittivity, magnetic permeability, and electrical conductivity are known constants with respect to space and time. Above and below the plane of measurement, the medium can be arbitrarily inhomogeneous and anisotropic. In particular, the proposed decomposition theory applies to marine EM, low-frequency data acquired for hydrocarbon mapping where the upgoing components of the recorded field guided and refracted from the reservoir, that are of interest for the interpretation. The direct-source field, the refracted airwave induced by the source, the reflected field from the sea surface, and mostmagnetotelluric noise traveling downward just below the seabed are field components that are considered to be noise in electromagnetic measurements. The viability and validity of the decomposition method is demonstrated using modeled and real marine EM data, also termed seabed logging (SBL) data. The synthetic data are simulated in a model that is fairly representative of the geologic area where the real SBL were collected. The results from the synthetic data study therefore are used to assist in the interpretation of the real data from an area with [Formula: see text] water depth above a known gas province offshore Norway. The effect of the airwave is seen clearly in measured data. After field decomposition just below the seabed, the upgoing component of the recorded electric field has almost linear phase, indicating that most of the effect of the airwave component has been removed.

scholarly journals Documentation for a web site to serve ULF-EM (Ultra-Low Frequency Electromagnetic) data to the public

2011 ◽  
Author(s):  
Danny A. Neumann ◽  
Selwyn McPherson ◽  
Simon L. Klemperer ◽  
Jonathan M.G. Glen ◽  
Darcy K. McPhee ◽  
...  
Keyword(s):  
Web Site ◽  
Low Frequency ◽  
The Public ◽  
Electromagnetic Data

scholarly journals Criticality features in ultra-low frequency magnetic fields prior to the 2013 M6.3 Kobe earthquake

2016 ◽  
Vol 59 (3) ◽  
Author(s):  
Stelios M. Potirakis ◽  
Konstantinos Eftaxias ◽  
Alexander Schekotov ◽  
Hiroki Yamaguchi ◽  
Masashi Hayakawa
Keyword(s):  
Low Frequency ◽  
Horizontal Component ◽  
Time Analysis ◽  
Electromagnetic Data ◽  
Ionospheric Perturbation ◽  
Kobe Earthquake ◽  
Specific Analysis ◽  
Natural Time ◽  
Natural Time Analysis ◽  
Significant Phenomenon

<p>The nonlinear criticality of ultra-low frequency (ULF) magnetic variations is investigated before a particular earthquake (EQ) occurred in Kobe on April 12, 2013, by applying the “natural time” analysis on a few ULF parameters: <em>F</em><span><em><sub>h</sub></em></span>, <em>F</em><span><em><sub>z</sub></em></span> and <em>D</em><span><em><sub>h</sub></em></span>. The first two refer to radiation from the lithosphere, and the last parameter corresponds to depression of horizontal component as a signature of ionospheric perturbation. A recent paper of our team has indicated, using the same data as in this paper but by means of conventional statistical analysis, a clear effect of depression in the horizontal component as an ionospheric signature. But there seems to be no convincing signature of lithospheric ULF radiation according to the specific analysis, so this paper aims at extending our study on the electromagnetic data recorded prior to the specific EQ by trying to find any significant phenomenon in ULF effects (both lithospheric radiation and the depression of horizontal component) using the critical, natural time analysis. The natural time analysis has yielded that criticality at Shigaraki (SGA), as the station closest to the EQ epicenter, is reached on March 27-29 for <em>F</em><span><em><sub>h</sub></em></span> and March 27 to April 1 for <em>F</em><span><em><sub>z</sub></em></span> (about two weeks before the EQ). But, the criticality for <em>D</em><span><em><sub>h</sub></em></span> was not observed at SGA probably due to high noise, on the other hand such criticality was observed at Kanoya (KNY) because of its known property of a wider range of detection of ULF depression.</p>

scholarly journals ANOMALY IDENTIFICATION FROM SUPER-LOW FREQUENCY ELECTROMAGNETIC DATA FOR THE COALBED METHANE DETECTION

2016 ◽  
Vol XLI-B8 ◽  
pp. 449-452
Author(s):  
S. S. Zhao ◽  
N. Wang ◽  
J. Hui ◽  
X. Ye ◽  
Q. Qin
Keyword(s):  
Coalbed Methane ◽  
Random Noise ◽  
Estimation Method ◽  
Low Frequency ◽  
Least Square ◽  
Electromagnetic Signal ◽  
Gaussian Component ◽  
Observation Data ◽  
Electromagnetic Data ◽  
Class B

Natural source Super Low Frequency(SLF) electromagnetic prospecting methods have become an increasingly promising way in the resource detection. The capacity estimation of the reservoirs is of great importance to evaluate their exploitation potency. In this paper, we built a signal-estimate model for SLF electromagnetic signal and processed the monitored data with adaptive filter. The non-normal distribution test showed that the distribution of the signal was obviously different from Gaussian probability distribution, and Class B instantaneous amplitude probability model can well describe the statistical properties of SLF electromagnetic data. The Class B model parameter estimation is very complicated because its kernel function is confluent hypergeometric function. The parameters of the model were estimated based on property spectral function using Least Square Gradient Method(LSGM). The simulation of this estimation method was carried out, and the results of simulation demonstrated that the LGSM estimation method can reflect important information of the Class B signal model, of which the Gaussian component was considered to be the systematic noise and random noise, and the Intermediate Event Component was considered to be the background ground and human activity noise. Then the observation data was processed using adaptive noise cancellation filter. With the noise components subtracted out adaptively, the remaining part is the signal of interest, i.e., the anomaly information. It was considered to be relevant to the reservoir position of the coalbed methane stratum.

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