Optimal combining of seismic data with different spectral characteristics

Authors

  • Yu. K. Tyapkin Yug-Naftogazgeologiya, Ukraine

DOI:

https://doi.org/10.24028/gzh.0203-3100.v41i5.2019.183637

Keywords:

combining seismic surveys, multichannel Wiener filter, optimal frequency-dependent weighted summation, optimal complementary signal

Abstract

When it comes to sharing overlapping seismic surveys and testing various energy sources, geophysicists have to deal with data having different spectral characteristics. It is very important to note that such data share the same information on the reflectivity of the medium, which is of interest to us. In order to combine such redundant data optimally and estimate the reflectivity of the medium more effectively, this article proposes using multichannel reverse Wiener filtering. To avoid the problems associated with a possible difference in the data acquisition systems of overlapping surveys, it is proposed to reduce the amount of information processed and to combine the final seismic images obtained from each of the independent surveys or from different sources. The theory of the optimal method is presented and the structure of the solution obtained is analyzed. It is shown that the method can be represented as a combination of the optimal frequency-dependent weighted summation of images with the subsequent single-channel inverse Wiener filtering (deconvolution) of the summation result. A theoretical comparison of the optimal method with simplified analogues wherein the first step is a simple unweighted summation without and with elimination of the wavelet phase spectra of images is performed. It is shown that the greater the difference between the spectra of the signal components of images at a given frequency, the greater the advantage of the optimal method of combining them over the simplified variants. The article stresses that since seismic exploration capabilities basically allow only signal parameters to be changed, the greatest effect from the optimal method can be achieved due to maximum mutual displacement (minimum mutual overlap) along the frequency axis of the spectra of the wavelets of combined images. This is theoretically confirmed by the calculation of the spectrum of the optimal complementary signal the addition of which to the existing set to participate in optimally combining ensures maximum efficiency of this procedure. The rationale is given that the optimal procedure should be performed only within the frequency interval where the signal averaged over the number of images prevails over the averaged noise. The method is tested on synthetic data. It is shown that its efficiency monotonously increases with increasing the input signal-to-noise ratio, the number of images involved in processing, and the mutual frequency shift of their spectra, i.e. as the degree of overlap of these spectra decreases. Moreover, the effectiveness of the method is confirmed on a field line from the Dnieper-Donets depression, which was independently worked out with dynamite and vibratory sources. It is shown that the optimal method provides the most regular and resolved reflections across the entire image, which significantly exceeds the results of independent single-channel deconvolutions of the images obtained with both types of sources and of their simplified combination.

References

Ampilov, Yu.P., Barkov, A.Yu., Yakovlev, I.V., Filippova, K.E., & Priyezzhev I.I. (2009). Almost everything about seismic inversion. Part 1. Tekhnologii seismorazvedki, 6(4), 3—16 (in Russian).

Kostrygin, Yu.P. (1991). Seismic surveys with complex sounding signals. Moscow: Nedra, 176 p. (in Russian).

Tyapkin, Yu.K. (1991). Optimum frequency range of the corrective filtering of seismic records. Geofizicheskiy zhurnal, 13(1), 62—69 (in Russian).

Tyapkin, Yu.K. (1994). Optimized estimates of a complicated multichannel seismic record model with statistical and deterministic regularization. Geologiya i geofizika, 35(1), 128—135 (in Russian).

Tyapkin, Yu.K. (1998). Increasing the resolving power of seismic method based on optimized use of records with different spectral characteristics. 1. Theory and method. Geofizicheskiy zhurnal, 20(1), 82—90 (in Russian).

Tyapkin, Yu.K., Prikhodchenko, D.F., & Nekrasov, I.A. (2005). Optimizing the process of extracting the signal from a multichannel seismic record. Geofizicheskiy zhurnal, 27(5), 718—729 (in Russian).

Tyapkin, Yu.K., & Silinskaya, E.A. (2007). Deconvolution of seismic records with the optimization of weighted normalized quadratic functionals. 2. Frequency domain. Geofizicheskiy zhurnal, 29(6), 32—44 (in Russian).

Tyapkin, Yu.K., Shatilo, A.P., & Starostenko, E.V. (1993). Iterative algorithms for optimum in L1 and L2 estimation of the phase characteristic of a seismic signal using the recording trispectrum. Geofizicheskiy zhurnal, 15(2), 85—92 (in Russian).

Carter, D., & Pambayuning, S. (2009). Extended bandwidth by a frequency domain merge of two 3D seismic volumes. The Leading Edge, 28(4), 400—406. doi: 10.1190/1.3112752.

Deplante, C. (2009). Spectral Fusion: a tool to merge low and high frequency datasets. International Petroleum Technology Conference, Paper 14078. doi:10.2523/IPTC-14078-MS.

Dittert, K.K. (1987). Method for filtering and combining seismic data having different spectral characteristics. US Patent no. 4,715,021.

Franks, L.E. (1969). Signal Theory. Prentice-Hall, Englewood Cliffs, NJ, 332 p.

Greer, S., & Fomel, S. (2018). Matching and merging high-resolution and legacy seismic images. Geophysics, 83(2), V115—V122. doi: 10.1190/geo2017-0238.1.

Hesthammer, J., & Lokkebo, S.M. (1997). Combining seismic surveys to improve data quality. First Break, 15(4), 103—115. doi: 10.3997/1365-2397.1997010.

Horn, R.A., & Johnson, C.R. (1985). Matrix Analysis. Cambridge Univ. Press.

Kumar, R., Al-Saeed, M.A., Lipkov, Y., & Roth, J. (2011). Seismic source comparison for shallow targets in north Kuwait field: 81st SEG Annual Meeting, Expanded Abstracts (pp. 102—106). doi: 10.1190/1.3627380.

Mohan, T.R.M., Yadava, C.B., Kumar, S., Mishra, K.K., & Niyogi, K. (2007). Prestack merging of land 3D vintages — A case history from Kavery Basin, India: 77th SEG Annual Meeting, Expanded Abstracts (pp. 437—441). doi: 10.1190/1.2792458.

Navarro, J., Thiessen, J., Zoch, H.-J., Janie, H., & Fischer, K. (1999). Depth imaging in the Heide-Buesum transition zone area: 61st EAGE Conference and Exhibition, Extended Abstracts, Paper 1-03. doi: 10.3997/2214-4609.201407600.

Pipping, J.C.P., Wever, A., Bachmann, R., Smirnov, V., & Deneuvillers, S. (2019). K18-Golf Field seismic and reservoir modeling challenges. First Break, 37(5), 59―65.

Potter, G., Mann, A., Jenkerson, M., & Rodriguez, J.-M. (1997). Comparison of marine vibrator, dynamite and airgun sources in the transition zone: 59th EAGE Conference and Exhibition, Extended Abstracts, Paper B018.

Robinson, E.A. (1967). Multichannel Time Series Analysis with Digital Computer Programs. Holden-Day, San Francisco.

Suarez, G.M. & Stewart, R.R. (2009). Seismic source comparison for compressional and converted-wave generation at Spring Coulee, Alberta: 79th SEG Annual Meeting, Expanded Abstracts (pp. 99—103). doi: 10.1190/1.3255919.

Tyapkin, Y.K. (2001). Optimum primary and supplementary signals optimizing the seismic data resolution. Journal of Applied Geophysics, 46(3), 175—187. doi: 10.1016/S0926-9851(01)00037-4.

Tyapkin, Y., & Silinskaya, E. (2007). Seismic data resolution enhancement by optimizing the generalized radius of gyration: 69th EAGE Conference and Exhibition, Extended Abstracts, Paper P268. doi: 10.3997/2214-4609.201401917.

Tyapkin, Yu., & Ursin, B. (2005). Optimum stacking of seismic records with irregular noise. Journal of Geophysics and Engineering, 2(3), 177―187. doi: 10.1088/1742-2132/2/3/001.

Werner, H., & Krey, Th. (1979). Combisweep — a contribution to sweep techniques. Geophysical Prospecting, 27(1), 78—105. doi: 10.1111/j.1365-2478.1978.tb00960.x.

White, R.E. (1977). The performance of optimum stacking filters in suppressing uncorrelated noise. Geophysical Prospecting, 25(1), 165—178. doi: 10.1111/j.1365-2478.1977.tb01158.x.

Wiggins, R.A., & Robinson, E.A. (1965). Recursive solution to the multichannel filtering problem. Journal of Geophysical Research, 70(8), 1885—1991. doi: 10.1029/JZ070i008p01885.

Yassi, N., & Kaba, A. (2013). Seismic source comparison in Surat Basin, Queensland: 23rd ASEG-PESA International Geophysical Conference, Abstracts. doi: 10.1071/PVv2013n165p55.

Yordkayhun, S., Ivanova, A., Giese, R., Juhlin, C., & Cosma, C. (2009). Comparison of surface seismic sources at the CO2SINK site, Ketzin, Germany. Geophysical Prospecting, 57(1), 125—139. doi: 10.1111/j.1365-2478.2008.00737.x.

Zafiropoulos, G., Tziolas, C., Dimitrakopoulos, D., & Economou, A. (1996). Field comparison of seismic sources for coal exploration: 58th EAGE Conference and Exhibition, Extended Abstracts, Paper PO22. doi: 10.3997/2214-4609.201408794.

Ziolkowski, A., (1993). Determination of the signature of a dynamite source using source scaling, Part 1: Theory. Geophysics, 58(8), 1174—1182. doi: 10.1190/1.1443501.

Ziolkowski, A., & Lerwill, W.E. (1979). A simple approach to high resolution seismic profiling for coal. Geophysical Prospecting, 27(2), 360—393. doi: 10.1111/j.1365-2478.1979.tb00975.x.

Ziolkowski A.M., Lerwill W.E., March D.W., & Peardon L.G. (1980). Wavelet deconvolution using a source scaling law. Geophysical Prospecting, 28(6), 872—901. doi: 10.1111/j.1365-2478.1980.tb01266.x.

Published

2019-11-15

How to Cite

Tyapkin, Y. K. (2019). Optimal combining of seismic data with different spectral characteristics. Geofizicheskiy Zhurnal, 41(5), 27–46. https://doi.org/10.24028/gzh.0203-3100.v41i5.2019.183637

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Articles