- Home
- A-Z Publications
- Geophysical Prospecting
- Previous Issues
- Volume 43, Issue 2, 1995
Geophysical Prospecting - Volume 43, Issue 2, 1995
Volume 43, Issue 2, 1995
-
-
A joint inversion algorithm to process geoelectric and sutface wave seismic data. Part I: basic ideas1
More LessAbstractFor the exploration of near‐surface structures, seismic and geoelectric methods are often applied. Usually, these two types of method give, independently of each other, a sufficiently exact model of the geological structure. However, sometimes the inversion of the seismic or geoelectric data fails.
These failures can be avoided by combining various methods in one joint inversion which feads to much better parameter estimations of the model than the independent inversions.
A suitable seismic method for exploring near‐surface structures is the use of dispersive surface waves: the dispersive characteristics of Rayleigh and Love surface waves depend strongly on the structural and petrophysical (seismic velocities) features of the near‐surface Underground.
Geoelectric exploration of the structure Underground may be carried out with the well‐known methods of DC resistivity sounding, such as the Schlumberger, the radial‐dipole and the two‐electrode arrays.
The joint inversion algorithm is tested by means of synthetic data. It is demonstrated that the geoelectric joint inversion of Schlumberger, radial‐dipole and two‐electrode sounding data yields more reliable results than the single inversion of a single set of these data. The same holds for the seismic joint inversion of Love and Rayleigh group slowness data. The best inversion result is achieved by performing a joint inversion of both geoelectric and surface‐wave data.
The effect of noise on the accuracy of the solution for both Gaussian and non‐Gaussian (sparsely distributed large) errors is analysed. After a comparison between least‐square (LSQ) and least absolute deviation (LAD) inversion results, the LAD joint inversion is found to be an accurate and robust method.
-
-
-
Bootstrap statistics for velocity tomography: application of a new information criterion1
Authors Osamu Nishizawa and Harufumi NeroAbstractA new information criterion, the extended information criterion (EIC) was applied in order to determine an optimum solution in simultaneous iterative reconstruction technique (SIRT) P‐wave velocity tomography. The EIC is derived from information theory and statistics, and it measures the goodness‐of‐fit between the true (unknown) data distribution and the observed data distribution: the former gives the probability of data realization from the true (unknown) model, whereas the latter gives a probability of data realization calculated from a particular model of which parameters are estimated. The EIC is calculated using bootstrap statistics, a numerical technique for calculating statistical estimators. Bootstrap statistics enables us to obtain the bias between the log likelihood and the expected log likelihood, and then to obtain the expected log likelihood from the log likelihood. Since the EIC is obtained numerically, we can use it for most problems of model parameter estimation without employing the maximum likelihood method. Taking weak anisotropy into account, we reconstructed the P‐wave velocity structure of a rock sample during water infiltration under differential stress loading conditions. The results indicate that we can remove unrealistic solutions sometimes encountered when too many iterations are made. In spite of much computation time, the EIC is a promising technique for the near future, prompted by the rapid progress in current computer technology.
-
-
-
Determination of a shallow velocity–depth model from seismic refraction data by coherence inversion1
Authors Evgeny Landa, Shemer Keydar and Alex KravtcovAbstractSeismic refractions have different applications in seismic prospecting. The travel‐ times of refracted waves can be observed as first breaks on shot records and used for field static calculation. A new method for constructing a near‐surface model from refraction events is described. It does not require event picking on prestack records and is not based on any approximation of arrival times. It consists of the maximization of the semblance coherence measure computed using shot gathers in a time window along refraction traveltimes. Time curves are generated by ray tracing through the model. The initial model for the inversion was constructed by the intercept‐time method. Apparent velocities and intercept times were taken from a refraction stacked section. Such a section can be obtained by appling linea moveout corrections to common‐shot records. The technique is tested successfully on synthetic and real data. An important application of the proposed method for solving the statics problem is demonstrated.
-
-
-
Effect of mining subsidence on seismic velocity monitored by a repeated reflection profilel1
Authors S.Y.S. Al‐Rawahy and N.R. GoultyAbstractWe have monitored changes in seismic velocity due to longwall coal‐mining in the Selby coalfield, Yorkshire, England by. ten repeated surveys of a surface seismic reflection profile. The direction of face advance in the Barnsley Seam, at 550 m depth, was parallel to the orientation of the profile. The traveltime of a strong reflection event from an anhydrite bed at 150 m depth was measured after processing the data with standard techniques. As the face advanced, the traveltime increased by about 4% overall. In detail, the progressive increase in traveltime correlates well with empirical calculations of differential subsidence between the surface and the anhydrite. However, the magnitude of the change must principally be accounted for by a decrease in seismic velocity, which we attribute to a reduction in the vertical effective stress.
-
-
-
Effective filtering of artifacts for implicit finite‐difference paraxial wave equation migration1
By C. BunksAbstractImplicit finite‐difference implementations of the paraxial wave equation are widely used in industrial prestack and post‐stack migration programs for imaging and velocity analysis. This type of implementation gives rise to numerical artifacts which, in general, do not degrade image quality but which do impede effective velocity analysis. This paper reviews the artifacts generated by the paraxial approximation and a post‐extrapolation, spatially varying filtering scheme is described which completely eliminates these artifacts. The method is illustrated with numerous examples.
-
-
-
The effects of source and receiver motion on seismic data1
Authors Gary Hampson and Helmut JakubowiczAbstractThe effects of source and receiver motion on seismic data are considered using extensions of the standard convolutional model. In particular, receiver motion introduces a time‐variant spatial shift into data, while source motion converts the effect of the source signature from a single‐channel convolution in time to a multichannel convolution in time and space. These results are consistent with classical Doppler theory and suggest that Doppler shifting can introduce distortions into seismic data even at relatively slow acquisition speeds. It is shown that, while both source and receiver motion are known to be important for marine vibroseis acquisition, receiver motion alone can produce significant artifacts in marine 3D data. Fortunately, the convolutional nature of the distortions renders them amenable to correction using simple deconvolution techniques. Specifically, the effects of receiver motion can be neutralized by applying an appropriate reverse time‐variant spatial shift, while those due to source motion can be addressed by introducing time‐variant spatial shifts both before and after standard, deterministic, signature deconvolution or correlation.
-
-
-
Tracking the amplitude versus offset (AVO) by using orthogonal polynomials1
Authors T.A. Johansen, L. Bruland and J. LutroAbstractInversion for S‐wave velocities from the amplitude variation with offset of P‐wave data is far from being a standard routine in the seismic processing sequence. However, the need for tracking the amplitude versus offset (AVO) occurs in several situations, for example in order to estimate the zero‐offset amplitude, to reveal areas with particular AVO characteristics, or to compress the AVO so that it is more easily obtainable at a later stage of the seismic processing. Furthermore, weak reflections can occasionally, due to the effect of the angle‐dependent reflectivity, have a polarity‐shift with offset, resulting in a very poor, or even vanishing, stack response. In such cases, the reflection event has to be represented by some other property than its mean amplitude or stack value.
We outline how the AVO of seismic data may be extracted and classified by the use of orthogonal polynomials. The main advantage of this method compared to a general polynomial fit is that the AVO may be classified by a unique Spectrum of polynomial coefficients. This is in analogy to Fourier coefficients where the orthogonal basis is harmonic functions. The set of orthogonal polynomials is constructed entirely from the set of offset coordinates, and these polyno‐mials are defined only on the offset window considered. Compared to a Fourier transform, this is a major advantage since there is no effect of a limited spatial bandwidth.
The AVO of normal‐moveout corrected data may be represented by a data gather where the orthogonal polynomial coefficients are given as time traces with each trace revealing a certain AVO characteristic. For instance, the stack is proportional to the zeroth‐order coefficient, the mean gradient is given by the firstorder coefficient, while the second‐order coefficient indicates whether the AVO increases and then decreases, or vice versa.
-
Volumes & issues
-
Volume 72 (2023 - 2024)
-
Volume 71 (2022 - 2023)
-
Volume 70 (2021 - 2022)
-
Volume 69 (2021)
-
Volume 68 (2020)
-
Volume 67 (2019)
-
Volume 66 (2018)
-
Volume 65 (2017)
-
Volume 64 (2015 - 2016)
-
Volume 63 (2015)
-
Volume 62 (2014)
-
Volume 61 (2013)
-
Volume 60 (2012)
-
Volume 59 (2011)
-
Volume 58 (2010)
-
Volume 57 (2009)
-
Volume 56 (2008)
-
Volume 55 (2007)
-
Volume 54 (2006)
-
Volume 53 (2005)
-
Volume 52 (2004)
-
Volume 51 (2003)
-
Volume 50 (2002)
-
Volume 49 (2001)
-
Volume 48 (2000)
-
Volume 47 (1999)
-
Volume 46 (1998)
-
Volume 45 (1997)
-
Volume 44 (1996)
-
Volume 43 (1995)
-
Volume 42 (1994)
-
Volume 41 (1993)
-
Volume 40 (1992)
-
Volume 39 (1991)
-
Volume 38 (1990)
-
Volume 37 (1989)
-
Volume 36 (1988)
-
Volume 35 (1987)
-
Volume 34 (1986)
-
Volume 33 (1985)
-
Volume 32 (1984)
-
Volume 31 (1983)
-
Volume 30 (1982)
-
Volume 29 (1981)
-
Volume 28 (1980)
-
Volume 27 (1979)
-
Volume 26 (1978)
-
Volume 25 (1977)
-
Volume 24 (1976)
-
Volume 23 (1975)
-
Volume 22 (1974)
-
Volume 21 (1973)
-
Volume 20 (1972)
-
Volume 19 (1971)
-
Volume 18 (1970)
-
Volume 17 (1969)
-
Volume 16 (1968)
-
Volume 15 (1967)
-
Volume 14 (1966)
-
Volume 13 (1965)
-
Volume 12 (1964)
-
Volume 11 (1963)
-
Volume 10 (1962)
-
Volume 9 (1961)
-
Volume 8 (1960)
-
Volume 7 (1959)
-
Volume 6 (1958)
-
Volume 5 (1957)
-
Volume 4 (1956)
-
Volume 3 (1955)
-
Volume 2 (1954)
-
Volume 1 (1953)