Regularity Analysis Applied to Well Log Data

Fedi, Maurizio; Fiore, Donato; Manna, Mauro La

doi:10.1007/3-540-26536-8_4

Cited by 9 publications

(9 citation statements)

References 17 publications

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“…The results obtained by the two wavelet approaches confirm the robustness of Bianchi's algorithm in yielding accurate H values. However, the H values estimated by the proposed algorithm are smaller than those obtained by Fedi (Fedi 2003;Fedi et al 2005) using a multiscale analysis, Fig. 3 Results obtained by the application of Bianchi's algorithm to sonic measurements at the pilot borehole a1 P-wave velocity (Vp(z)) a2 S-wave velocity (Vs(z)) b1 Vp(z)'s Hurst function (Hp(z)) b2 Vs (z)'s Hurst function (Hs(z)) c a lithologic sketch modified from http:// icdp.gfz-potsdam.de/html/ktb Blue line contacts with faults; gray line lithological changes and the discrepancy of the estimations is explained by the choice of the analyzing (Morlet) wavelet parameters (Gaci et al 2010).…”

Section: Application To Ktb Sonic Log Datacontrasting

confidence: 53%

Heterogeneities characterization from velocity logs using multifractional Brownian motion

Gaci

Zaourar

2010

Arab J Geosci

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Well logs provide additional information from the borehole that cannot be derived from other subsurface investigations. Their analysis may bring supplementary features about the earth's heterogeneities. In previous researches, the logs were modeled using fractional Brownian motions indexed by Hurst (or Hölder) exponents quantifying their global regularity degrees. Indeed, these monofractal models, characterized by the same Hurst exponent, do not allow to study the depth-evolution of the local Hurst parameter. In order to overcome this problem, we propose to model the logs using multifractional Brownian motions and suggest an algorithm, developed previously for financial time series, to estimate the local Hurst exponent function. First, the potential of this algorithm is assessed through its application on synthetic sonic log data simulated by the successive random additions method. We note that the estimated Hurst functions (or regularity profiles) are very close to the theoretical Hurst functions. Second, this analysis is extended to sonic logs data from the KTB pilot borehole (Germany). Using the resulted regularity profiles, we carry out a lithological segmentation and fault identification on the geological layers crossed by the well. We derived also a correlation between the Hurst value variation and the lithological changes.

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Section: Application To Ktb Sonic Log Datacontrasting

confidence: 53%

Heterogeneities characterization from velocity logs using multifractional Brownian motion

Gaci

Zaourar

2010

Arab J Geosci

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“…4b). On the other hand, the multiscale analysis performed by Fedi (2003) and Fedi et al (2005) showed an interval of Hurst values from 0.3 to 0.45 for all the analyzed logs.…”

Section: Resultsmentioning

confidence: 99%

“…4a). While Fedi (2003) and Fedi et al (2005) attributed to this lithology, Hurst values varying from 0.25 to 0.3 for density and magnetic susceptibility logs, and from 0.45 to 0.7 for self-potential and selfresistivity logs.…”

Section: Resultsmentioning

confidence: 99%

“…The implementation of both approaches evidenced a correspondence between the Hölder exponents and the lithological strata traversed by the well. Fedi et al (2005) extended the regularity analysis to other KTB main borehole measurements (density, electrical resistivity, self-potential). He revealed that an important correlation exists between the various regularity profiles estimated for the well logs.…”

Section: Introductionmentioning

confidence: 99%

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تطبيق تحليل الانتظام على بيانات صوتية مسجلة في بئر: دراسة حالة من بئر KTB

Gaci

Zaourar²,

Briqueu³

et al. 2010

Arab J Geosci

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Borehole logs provide in situ information about the fluctuations of petrophysical properties with depth and thus allow the characterization of the crustal heterogeneities. A detailed investigation of these measurements may lead to extract features of the geological media. In this study, we suggest a regularity analysis based on the continuous wavelet transform to examine sonic logs data. The description of the local behavior of the logs at each depth is carried out using the local Hurst exponent estimated by two (02) approaches: the local wavelet approach and the average-local wavelet approach. Firstly, a synthetic log, generated using the random midpoints displacement algorithm, is processed by the regularity analysis. The obtained Hurst curves allowed the discernment of the different layers composing the simulated geological model. Next, this analysis is extended to real sonic logs data recorded at the Kontinentales Tiefbohrprogramm (KTB) pilot borehole (Continental Deep Drilling Program, Germany). The results show a significant correlation between the estimated Hurst exponents and the lithological discontinuities crossed by the well. Hence, the Hurst exponent can be used as a tool to characterize underground heterogeneities

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“…The value of scaling exponent is found to be close to 1.6 (Fig. ), and earlier studies have found a value of 1.4‒1.6 (Leonardi and Kumpel ; Fedi, ; Fedi et al ., ; Bansal et al . ) which are in close agreement within the error limits.…”

Section: Scaling Distribution Of Sourcesmentioning

confidence: 99%

Modelling of magnetic data for scaling geology

Bansal

Dimri

2013

Geophysical Prospecting

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Interpretation of magnetic data can be carried out either in the space or frequency domain. The interpretation in the frequency domain is computationally convenient because convolution becomes multiplication. The frequency domain approach assumes that the magnetic sources distribution has a random and uncorrelated distribution. This approach is modified to include random and fractal distribution of sources on the basis of borehole data. The physical properties of the rocks exhibit scaling behaviour which can be defined as P(k) = Ak−β, where P(k) is the power spectrum as a function of wave number (k), and A and β are the constant and scaling exponent, respectively. A white noise distribution corresponds to β = 0. The high resolution methods of power spectral estimation e.g. maximum entropy method and multi‐taper method produce smooth spectra. Therefore, estimation of scaling exponents is more reliable. The values of β are found to be related to the lithology and heterogeneities in the crust. The modelling of magnetic data for scaling distribution of sources leads to an improved method of interpreting the magnetic data known as the scaling spectral method. The method has found applicability in estimating the basement depth, Curie depth and filtering of magnetic data.

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Regularity Analysis Applied to Well Log Data

Cited by 9 publications

References 17 publications

Heterogeneities characterization from velocity logs using multifractional Brownian motion

Heterogeneities characterization from velocity logs using multifractional Brownian motion

تطبيق تحليل الانتظام على بيانات صوتية مسجلة في بئر: دراسة حالة من بئر KTB

Modelling of magnetic data for scaling geology

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