Spectral inversion is a promising tool to accelerate the project
https://doi.org/10.7868/S2587739920040060
Abstract
This article reveals the possibilities of applying the results of spectral inversion on the example of a field in Eastern Siberia and shows the advantages of this approach over standard methods.
About the Authors
V. A. Fagereva
Gazpromneft NTC LLC
Russian Federation
Russian Federation
Saint-Petersburg
P. P. Emelianov
Gazpromneft NTC LLC
Russian Federation
Russian Federation
Saint-Petersburg
A. V. Butorin
Gazpromneft NTC LLC
Russian Federation
Russian Federation
Saint-Petersburg
F. V. Krasnov
Gazpromneft NTC LLC
Russian Federation
Russian Federation
Saint-Petersburg
R. A. Oshmarin
Gazpromneft NTC LLC
Russian Federation
Russian Federation
Saint-Petersburg
References
1. Butorin A.V., Krasnov F.V. Benchmarking of spectral inversion methods exemplified by model traces. Geofizika [Russian geophysics]. 2016, no. 4. pp. 42–47. (In Russ.)
2. Lukovenkova O.O. Comparing the methods of thin approximation exemplified by signals of geoacoustic emission. Vestnik KRAUNС. Physics and Mathematic Sciences. 2014, vol. 9, no. 2, pp. 59–67.
3. Yagola A.G., Van Yanfey, Stepanova I.E., Titarenko V.N. Obratnye zadachi i metody ikh resheniya. Prilozheniya k geofizike [Inverse problems and their solution methods. Attachments to geophysics]. Moscow, BINOM, Laboratoria Znaniy, 2014. 216 p.
4. Castagna J. P., Sun S., Siegfried R.W. Instantaneous spectral analysis: Detection of low frequency shadows associated with hydrocarbons. The Leading Edge. 2003, vol. 22, pp. 120–127.
5. Castagna J. P., Sun S. Comparison of spectral decomposition methods. First break. 2006, vol. 24, no. 3, pp. 75–79.
6. Chakraborty A., Okaya D. Frequency-time decomposition of seismic data using wavelet based methods. Geophysics. 1995, vol. 60, pp. 1906–1916.
7. Cohen, L. Time frequency analysis. Prentice Hall PTR, 1995.
8. Giroldi L., Alegria F. Using spectral decomposition to identify and characterize glacial valleys and fluvial channels within the Carboniferous section in Bolivia. The Leading Edge. 2005, vol. 24, pp. 1152–1159.
9. Liu J., Marfurt K. Instantaneous spectral attributes to detect channels. Geophysics. 2007, vol. 72, P23-P31.
10. Mallat S., Zhang Z. Matching pursuit with time-frequency dictionaries. Technical Report 619, IEEE Transactions in Signal Processing. 1992, vol. 41, pp. 3397–3415.
Review
For citations:
Fagereva V.A., Emelianov P.P., Butorin A.V., Krasnov F.V., Oshmarin R.A. Spectral inversion is a promising tool to accelerate the project. PROneft. Professionally about Oil. 2020;(4):46-50. (In Russ.) https://doi.org/10.7868/S2587739920040060
Views:
111
Email this article 