TY - JOUR

T1 - Prediction of the Shear Wave Velocity from Compressional Wave Velocity for Gachsaran Formation

AU - Parvizi, Saeed

AU - Kharrat, Riyaz

AU - Asef, Mohammad R.

AU - Jahangiry, Bijan

AU - Hashemi, Abdolnabi

N1 - Publisher Copyright: © 2015 Parvizi et al.

PY - 2016/12/17

Y1 - 2016/12/17

N2 - Shear and compressional wave velocities, coupled with other petrophysical data, are very important for hydrocarbon reservoir characterization. In situ shear wave velocity (Vs) is measured by some sonic logging tools. Shear velocity coupled with compressional velocity is vitally important in determining geomechanical parameters, identifying the lithology, mud weight design, hydraulic fracturing, geophysical studies such as VSP, etc. In this paper, a correlation between compressional and shear wave velocity is obtained for Gachsaran formation in Maroon oil field. Real data were used to examine the accuracy of the prediction equation. Moreover, the genetic algorithm was used to obtain the optimal value for constants of the suggested equation. Furthermore, artificial neural network was used to inspect the reliability of this method. These investigations verify the notion that the suggested equation could be considered as an efficient, fast, and cost-effective method for predicting Vs from Vp.

AB - Shear and compressional wave velocities, coupled with other petrophysical data, are very important for hydrocarbon reservoir characterization. In situ shear wave velocity (Vs) is measured by some sonic logging tools. Shear velocity coupled with compressional velocity is vitally important in determining geomechanical parameters, identifying the lithology, mud weight design, hydraulic fracturing, geophysical studies such as VSP, etc. In this paper, a correlation between compressional and shear wave velocity is obtained for Gachsaran formation in Maroon oil field. Real data were used to examine the accuracy of the prediction equation. Moreover, the genetic algorithm was used to obtain the optimal value for constants of the suggested equation. Furthermore, artificial neural network was used to inspect the reliability of this method. These investigations verify the notion that the suggested equation could be considered as an efficient, fast, and cost-effective method for predicting Vs from Vp.

KW - compressional wave velocity

KW - DSI log

KW - MATLAB software

KW - shear wave velocity

KW - sonic log

UR - http://www.scopus.com/inward/record.url?scp=84947265338&partnerID=8YFLogxK

U2 - 10.1515/acgeo-2015-0048

DO - 10.1515/acgeo-2015-0048

M3 - Article

AN - SCOPUS:84947265338

VL - 63.2015

SP - 1231

EP - 1243

JO - Acta Geophysica

JF - Acta Geophysica

SN - 1895-6572

IS - 5

ER -