Shear wave velocity prediction using seismic attributes and well log data

• Autorzy: Gholami, R. , Moradzadeh, A. , Rasouli, V. , Hanachi, J.
• Języki publikacji: EN

Abstrakty

EN

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data is not usually acquired during well logging, which is most likely for cost saving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this information is inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis (ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented.

Słowa kluczowe

PL

prędkość fali poprzecznej; atrybut sejsmiczny; analiza regresji; analiza składowych niezależnych

EN

shear wave velocity; seismic attributes; regression analysis; independent component analysis

• Czasopismo: Acta Geophysica
• Rocznik: 2014
• Tom: Vol. 62, no. 4
• Strony: 818--848
• Opis fizyczny: Bibliogr. 22 poz.

Twórcy

autor

Gholami, R.

• Department of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran,

autor

Moradzadeh, A.

• Department of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran

autor

Rasouli, V.

• Department of Petroleum Engineering, Curtin University, Perth, Australia

autor

Hanachi, J.

• Petroleum Geology, Tehran, Iran

Bibliografia

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Identyfikatory

DOI

10.2478/s11600-013-0200-7