Turning-wave amplitude inversion

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science

Reexamination Certificate

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C367S047000

Reexamination Certificate

active

06278950

ABSTRACT:

FIELD OF THE INVENTION
This invention relates to the field of seismic prospecting. More particularly, the invention is a method for compensating for amplitude variations in seismic records due to shallow attenuation anomalies such as gas clouds or gas-charged channels, or inconsistencies in the data acquisition system such as variations in source strength.
BACKGROUND OF THE INVENTION
When gas accumulations or other attenuation anomalies exist at shallow depths, they produce two detrimental effects on seismic data. One is the amplitude loss due to attenuation, and the other is wavefront distortion due to severe lateral velocity contrasts. As a result, the amplitudes of reflections from subsurface horizons below gas clouds or other anomalies are usually very low, making it difficult to identify such reflections. Such amplitude attenuation also diminishes or destroys the value of seismic amplitudes as an attribute for estimating reservoir properties.
One way to mitigate the problem of low amplitude is to apply automatic gain control (AGC) that almost equalizes the reflection amplitude. Although AGC is a powerful tool for revealing attenuated seismic reflections particularly when the reflection amplitude varies significantly), AGC destroys the amplitude integrity of the reflections thereby making attribute analysis meaningless.
Another class of amplitude compensation methods is based on a priori information. For example, if the reflection coefficient of a particular horizon below a shallow anomaly is known to be constant, but the reflection amplitudes from the horizon vary due to the anomaly, then one can generate scale factors that will force the amplitudes of reflections from the horizon to be constant and apply them to the seismic traces to correct the amplitudes of reflections from other horizons affected by the anomaly. However, this approach requires a priori knowledge about the reflection coefficient of a particular horizon. Otherwise, the method will blindly make the reflection amplitudes constant along the horizons, making the amplitudes unsuitable for amplitude analysis.
Without invoking any a priori assumptions about the amplitudes of reflections from a horizon, Brzostowski and McMechan discuss a way of estimating near-surface attenuation that could be used to mitigate amplitude variations caused by near-surface heterogeneities. (Brzostowski, M. A. and McMechan, G. A., “3-D tomographic imaging of near-surface seismic velocity and attenuation,”
Geophysics,
57, 393-406 (1992)). Unfortunately, their method requires a near-surface velocity profile to estimate the attenuation. Also, the method would be unstable if the ratio of observations to unknowns is low, which usually will be the case if one attempts to determine the attenuation for each cell for a near-surface volume. The authors qualitatively compare their attenuation model to near-surface geologic features, but the accuracy and resolution are insufficient to be used to correct any amplitude variations due to the near-surface heterogeneities.
Thus, there is a need for a method for determining surface-consistent attenuation scale factors without requiring either a near-surface velocity profile or any a priori assumptions about the amplitudes of reflections from horizons below shallow attenuation anomalies. The present invention satisfies this need.
SUMMARY OF THE INVENTION
In one embodiment, the present invention is a method for compensating for amplitude loss in a set of seismic traces, where the amplitude loss is caused by shallow attenuation anomalies. The method comprises the steps of (a) determining first-arrival amplitudes for long-offset seismic data traces; (b) inverting the first-arrival amplitudes to determine attenuation scale factors; and (c) using the attenuation scale factors to adjust the amplitudes of all later-arriving seismic traces of whatever offset in the data set. The offset in step (a) above must be sufficiently large that a turning wave (which will be the first arrival) that arrives at the receiver will pass completely through the shallow layer containing attenuation anomalies, following a nearly vertical path.
In another embodiment, the invention is extended to better treat situations where the shallow attenuation may be frequency dependent. A bank of band-pass filters is first applied to the seismic traces to separate the data into a series of filtered data traces having different frequency content, and then the previously described inventive method is applied to each set of band pass filtered seismic traces, which are then recombined after being scaled by the appropriate frequency-dependent attenuation scale factor.
In a third embodiment, the invention is extended to also include the effects of inconsistencies in the data acquisition system. In addition to inverting the first arrival amplitudes for long offsets to obtain attenuation scale factors to compensate for shallow attenuation anomalies, the same first arrival amplitudes can be used to simultaneously invert for fluctuations in the acquisition system. For example, the present invention in this embodiment can be used to estimate variations in source strength or receiver variations. As in the first embodiment described above, the estimates for source strength variations or changes in the gain of the recording system can be used to remove the effects of these inconsistencies in the acquisition system from the seismic data.


REFERENCES:
R. E. Sheriff and L. P. Geldart,Exploration Seismology, Second Edition, Cambridge University Press, Cambridge, MA, 1995, p. 98.
A. van der Sluis and H. A. van der Vorst, “SIRT- and CG-Type Methods for the Iterative Solution of Sparse Linear Least-Squares Problems”,Linear Algebra and its Applications, 130, New York, NY, 1990, pp. 257-303.
J. E. Dennis, Jr. and Robert B. Schnabel, Numerical Methods for Unconstrained Optimization and Nonlinear Equations, The Society for Industrial and Applied Mathematics, Philadelphia, PA, 1996, pp. VII-X.
Dave Hale, N. Ross Hill and Joseph P. Stefani, “Imaging Salt with Turning Seismic Waves”, SEG 61st Annual Meeting, 1991, pp. 1171-1174.
Christopher C. Paige and Michael A. Saunders, “LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares”,ACM Transactions on Mathematics Software, vol. 8 No. 1, Mar. 1982, pp. 44-56, 58-63, 65, 68, 70, 71.
Matthew A. Brzostowski and George A. McMechan, “3-D tomographic imaging of near-surface seismic velocity and attenuation”,Geophysics, vol. 57 No. 3, Mar. 1992, pp. 396-403.

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