Abstract

 Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate estimates of shear wave velocity with correlation coefficient of about unity than other currently available methods.
Highlights
In many developed hydrocarbon fields, only compressional wave velocity (Vp) may be available through the borehole compensated sonic tool logs (BHC logs) or seismic survey
Vs could be applied in seismic technology used for reservoir characterization, (Castagna, 1985)
DATA ANALYSIS AND METHODOLGY: This study presents multivariate regression analysis using SPSS softwarethat is used to develop new correlation to predict shear waves and among effective petrophysical properties of a productive carbonate section of South East Iraq (Amara field – Khasib formation)
Summary
In many developed hydrocarbon fields, only compressional wave velocity (Vp) may be available through the borehole compensated sonic tool logs (BHC logs) or seismic survey. Many research efforts have been made in investigating empirical relationships to estimate Vs prediction in previous decades, such as given by (Carroll, 1969;Castsgna, et al, 1993;Eskandari, et al, 2004;Brocher, 2005;Ameen, et al, 2009; Al-Kattan, 2015). All these Vs estimation models take Vp as input. Most of previous attempts to predict the Vs of a field case consider the determination coefficient as a sufficient criterion to evaluate the accuracy of the empirical model, which may not always capture the total variation of rock independent variables. An attempt is made to predict accurate Vs for Amara oil field, this field is selective due to its drilling stability and production problem
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
