Automated method for determination of geological horizons nonconformity according to three-dimensional seismic data
In complicated geological media mapping of faults according to wave seismic field often becomes difficult. In algorithm of preliminary processing of seismic data spatial summation of traces is present that leads to «corrosion» of exact location of the fault. Automated method is proposed for identification of faults in three-dimensional body of seismic data of logarithmic decrements of fading (LDF) obtained solving of inverse problem of seismic. Resolvability of LDF data is comparable with resolving ability of initial seismic records.
As a result, the analysis is conducted not only taking into account reflecting features of the medium but also with its absorbing properties.
Abrupt change of absorption in minor spatial interval is a good identifying attribute of the presence of non-conformable lean-vertical occurrence of geological horizons. Deep and spatial distribution of identified fault structures is an additional argument supporting their existence.
We used as an example the materials of detailed seismic mapping of МОГТ 3D conducted by «Ukrgeophysisc» in thin-layer mining field of «Krasnolimanskaya» mine. Geological section of this area is specific by its complexity because of the presence of thrust-shear geological structures related to tension and subsequent compression of these territories that lead to appearance of large amount of deep faults and local fissures.
In consolidated geological medium gradient of change of logarithmic gradient of fading will become minor and function of absorption mainly consists of low-speed harmonics. The presence of shear faults leads whereas to abrupt change of absorbing properties of the medium and to appearance of local high-speed oscillations. It is possible to find out the presence of such low-amplitude non-stationary processes in harmonic functions using wavelet analysis. Therefore the paper presents a method that makes possible to find out fault-related decompaction zones in three-dimensional data 3D CDP of the mine field «Krasnolimanskaya 5,25 km2 consisting of almost 27,5 million values reflecting different physical properties of the medium.
Full Text:PDF (Українська)
Astafyeva, N. M. (1996). Wavelet Analysis: Basic Theory and Some Application. Uspekhi fizicheskikh nauk, 166(11), 1145―1170. doi.org/10. 3367.UFNr.0166.199611a.1145 (in Rusian).
Vehelyanska, N. V., & Provotvorova, O. V. (2009). Features of the geological structure of individual coal seams of the Krasnoarmeysk coal-mining district (as an example of the Krasnolimansk mine). Tektonika i stratyhrafiya, (36), 54—59 (in Ukrainian).
Verhelska, N. V. (2012). Features of the structure of the l3 formation of the Krasnoarmeysk coal-mining district of the Donetsk basin. Zbirnyk naukovykh prats Instytutu heolohichnykh nauk NAN Ukrayiny, (5), 206—2 08 (in Ukrainian).
Volkova, T. P., & Sharina, O. S. (2016). Patterns of distribution of natural gas content in the mines of the Krasnoarmeysky coal-industrial region. Visti Donetskoho hirnychoho instytutu, (2), 3—9 (in Russian).
Gryn, D. M. (2001a). Basis functions, spectral correction and bypass seismic lines. Geofizicheskiy zhurnal, 23(3), 95—105 (in Ukrainian).
Gryn, D. M. (2001b). Logarithmic decrement and other features attenuation of seismic waves. Geofizicheskiy zhurnal, 23(4), 91—102 (in Ukrainian).
Gryn, D. M. (2019). Methods for determination of spatial distribution of minor-amplitude faults and fissures in thin-layer coal-bearing geological medium. Geofizicheskiy zhurnal, 41(5), 190—205 (in Ukrainian).
Gryn, D. M., & Gryn, M. E. (2003). Difference operators for extracting target waves. Geofizicheskiy zhurnal, 25(4), 84—97 (in Ukrainian).
Ivanov, M. A. (2004). Application of wavelet transforms in image coding. Novyye informatsionnyye tekhnologii v nauke i obrazovanii, (24), 157―175 (in Russian).
Korol, V. I., & Skobenko, A. V. (2013). Acoustic method for forecasting gas-dynamic phenomena in coal mines. Dnepropetrovsk: National Mining University Edition, 181 p. (in Russian).
Levkovich-Maslyuk, L., & Pereberin, A. (1999). Introduction to wavelet analysis: Training course. Moscow: Graficon’99, 120 p. (in Russian).
Novikov, L. V. (1999). Fundamentals of wavelet analysis of signals: a manual. St. Petersburg: Edition Institute of Analytical Instrumentation RAS, 152 p. (in Russian).
Priorov, A. L., Volokhov, V. A., & Apalkov, I. V. (2011). Signal processing based on wavelet transform: Methodological instructions. Yaroslavl: Edition of Yaroslavl State University, 44 p. (in Russian).
Bentaleb, Y., El Hajji, S., & Orhanou, G. (2010). A Wavelets Algorithm for the Seismic Waves Alignment. Contemporary Engineering Sciences, 3(4), 157―166.
Chakraborty, A., & Okaya, D. (1995). Frequency-time decomposition of seismic data using wavelet-based methods. Geophysics, 60(6), 1906―1916. https://doi.org/10.1190/1.1443922.
Chen, Y., Fomel, S., & Hu, J. (2014a). Iterative deblending of simultaneous-source seismic data using seislet-domain shaping regularization. Geophysics, 79(5), V179―V189. https://doi.org/10.1190/geo2013-0449.1.
Chen, Y., Liu, T., Chen, X., Li, J., & Wang, E. (2014б). Time-frequency analysis of seismic data using synchrosqueezing wavelet transform. Journal of Seismic Exploration, 23(4), 303―312.
Chui, C. K. (1992).Wavelets: A Tutorial in Theory and Applications (Wavelet Analysis and Its Applications). Academic Press; Later Printing edition, Texas A&M University, College Station, Texas, 723 p.
Fajardo, C., Reyes, O. M., & Ramirez, A. (2015). Seismic Data Compression Using 2D Lifting-Wavelet Algorithms. Ingeniería y Ciencia, 11(21), 221―238. http://dx.doi.org/10.17230/ingciencia.11.21.12.
Foufoula-Georgiou, E., & Kumar, P. (Eds.). (1994). Wavelets in Geophysics. Academic Press, Inc. San Diego, California, USA.
Innanen, K. (2013). Seismic processing with continuous wavelet transform maxima. CREWES Research Report, 25.
Liu, Y., & Fomel, S. (2013). Seismic data analysis using local time-frequency decomposition. Geophysical Prospecting, 61(3), 516―525. https://doi.org/10.1111/j.1365-2478.2012.01062.x.
Morlet, J., Arens, G., Fourgeau, E., & Glard, D. (1982a). Wave propagation and sampling theory ― part 1: Complex signal and scattering in multilayered media. Geophysics, 47(2), 203―221. https://doi.org/10.1190/1.1441328.
Morlet, J., Arens, G., Fourgeau, E., & Glard, D. (1982b). Wave propogation and sampling theory ― part 2: Sampling theory and complex waves. Geophysics, 47(2), 222―236, https://doi.org/10.1190/1.1441329.
Pawelec, I., Sava, P., & Wakin, M. (2019). Wavefield reconstruction using wavelet transform. SEG Technical Program Expanded Abstracts, 147―151. https://doi.org/10.1190/segam2019-3216535.1.
Rivera-Recillas, D. E., Lozada-Zumaeta, M. M., Ronquillo-Jarillo, G. & Campos-Enríquez, J. O. (2005). Multiresolution analysis applied to interprenation of seismic reflection data. Geofísica Internacional, 44(4), 355―368.
Roueff, A., Chanussot, J., Mars, J. I., & Nguyen, M.-Q. (2004). Unsupervised separation of seismic waves using the watershed algorithm on time-scale image. Geophysical Prospecting, 52(4), 287―300. doi: 10.1111/j.1365-2478.2004.00416.x.
Shuchong, L., & Xun, C. (2014). Seismic signals wavelet packet de-noising method based on improved threshold function and adaptive threshold. Computer Modeling and New Technologies, 18(11) 1291―1296.
Sinha, S., Routh, P. S., Anno, P. D., & Castagna, J. P. (2005). Spectral decomposition of seismic data with continuous-wavelet transform. Geophysics, 70(6), P19―P25. https://doi.org/10.1190/1.2127113.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Licensed under a Creative Commons Attribution 4.0 International License.