Fast Imaging of TDEM data based on S-inversion

Tartaras, Efthimios; Zhdanov, Michael S.; Wada, Kazushige; Saitô, Akira; Hara, Toshiaki

doi:10.1016/s0926-9851(99)00030-0

Cited by 40 publications

(15 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A transform that seams to hold great potential for accurate and real-time interpretation of TDEM data is the S-layer transform, whereby a conductance and depth is calculated for every time channel that is used by the TDEM system. This transform is discussed by Tartaras et al (2000) and although very elegant in its simplicity, its effectiveness is limited by the fact that a first-and second-order numerical differentiation are required in the algorithm, as discussed in Section 1.3. This is but one of many different schemes for obtaining conductivity-depth sections.…”

Section: Interpretation Of Tdem Datamentioning

confidence: 99%

“…These are summarised by Tartaras et al (2000) as: 0 ) is the parameter that has to be determined through numerical differentiation. This value is used to calculate both cumulative conductance (S) and depth (d) of an equivalent S-layer, for each time channel and noise generated by differentiation will be consequently introduced into both these numbers.…”

Section: The S-layer Differential Transformmentioning

confidence: 99%

“…The specific numerical differentiation implemented by Tartaras et al (2000) is described only as ''ya numerical differentiation scheme that computes a first-order derivative for the provided TDEM data using polynomial interpolation.'' This is unfortunately not clear enough to reconstruct with confidence and an exact comparison of this method with the other methods is not included in this paper.…”

Section: Description Of Three Polynomial-based Numerical Differentiatmentioning

confidence: 99%

“…This is unfortunately not clear enough to reconstruct with confidence and an exact comparison of this method with the other methods is not included in this paper. Tartaras et al (2000) also applied smoothing of data ''yprior to and following differentiation''. This is a commonly used technique applied to reduce noise, but ultimately alters data.…”

Section: Description Of Three Polynomial-based Numerical Differentiatmentioning

confidence: 99%

“…(16) various stages of the differentiation process. Smoothing of data before and after the numerical differentiation is an accepted method of reducing the noise in data (Tartaras et al, 2000). However, any smoothing applied to the data will change the data and influence the final interpretation.…”

Section: Construction Of the Integration Matrixmentioning

confidence: 99%

See 4 more Smart Citations

Analysis of numerical differentiation methods applied to time domain electromagnetic (TDEM) geophysical data in the S-layer differential transform

Combrinck

2009

Computers & Geosciences

View full text Add to dashboard Cite

a b s t r a c tThe S-layer differential transform produces subsurface conductivity-depth images from Time Domain Electromagnetic (TDEM) data. It is a very fast method, but suffers from high noise levels due to the implementation of two consecutive numerical differentiations that are performed in the algorithm. In this paper, twelve numerical differentiation strategies are compared in order to find the most efficient differentiation scheme, specifically for TDEM data and the S-layer differential transform. The twelve strategies are made up through combinations of three differentiation methods, optional smoothing of data and optional resampling of data to equally spaced intervals. Comparisons are made on analytical, synthetic and field data.

show abstract

Section: Interpretation Of Tdem Datamentioning

confidence: 99%

Section: The S-layer Differential Transformmentioning

confidence: 99%

Section: Description Of Three Polynomial-based Numerical Differentiatmentioning

confidence: 99%

Section: Description Of Three Polynomial-based Numerical Differentiatmentioning

confidence: 99%

Section: Construction Of the Integration Matrixmentioning

confidence: 99%

See 3 more Smart Citations

Analysis of numerical differentiation methods applied to time domain electromagnetic (TDEM) geophysical data in the S-layer differential transform

Combrinck

2009

Computers & Geosciences

View full text Add to dashboard Cite

show abstract

Research on Transient Electromagnetic Response of Magnetic Source in Borehole

Xiao

Dang

Guo

et al. 2011

Chinese J of Geophysics

View full text Add to dashboard Cite

The transient electromagnetic exploration in borehole is a full space geophysical problem. The Gaver‐Stehfeest inverse Laplace transform is used to theoretically calculate the transient electromagnetic response in the receiver loop. And the effects of the parameters of the borehole mud, metal casing, the cement sheath and the formation on electromagnetic logging responses are analyzed. The response curves of different electrical conductivity of the borehole mud indicate that the borehole mud has little effect on the electromagnetic responses. The numerical results of different geometry of the casing pipe show that the inner radius and the thickness of casing have an obvious effect on the logging responses, moreover the abnormality of transient response appears where the casing thickness suddenly increases or decreases. The simulation results of different magnetic permeability of the casing pipe show that it has an important effect on transient response in borehole and the higher the magnetic permeability, the more difficult the electromagnetic signals transmitting through the casing. Results of different parameters of the cement sheath reflect that the high conductive cement sheath can generate large measurement error for low conductive formation. It is also found that the effect of the thickness of the cement sheath can be ignored for high conductive formation.

show abstract