Abstract
Shear wave velocity has numerous applications in geomechanical, petrophysical and geophysical studies of hydrocarbon reserves. However, data related to shear wave velocity isn’t available for all wells, especially old wells and it is very important to estimate this parameter using other well logging. Hence, lots of methods have been developed to estimate these data using other available information of reservoir. In this study, after processing and removing inappropriate petrophysical data, we estimated petrophysical properties affecting shear wave velocity of the reservoir and statistical methods were used to establish relationship between effective petrophysical properties and shear wave velocity. To predict (VS), first we used empirical relationships and then multivariate regression methods and neural networks were used. Multiple regression method is a powerful method that uses correlation between available information and desired parameter. Using this method, we can identify parameters affecting estimation of shear wave velocity. Neural networks can also be trained quickly and present a stable model for predicting shear wave velocity. For this reason, this method is known as “dynamic regression” compared with multiple regression. Neural network used in this study is not like a black box because we have used the results of multiple regression that can easily modify prediction of shear wave velocity through appropriate combination of data. The same information that was intended for multiple regression was used as input in neural networks, and shear wave velocity was obtained using compressional wave velocity and well logging data (neutron, density, gamma and deep resistivity) in carbonate rocks. The results show that methods applied in this carbonate reservoir was successful, so that shear wave velocity was predicted with about 92 and 95 percents of correlation coefficient in multiple regression and neural network method, respectively. Therefore, we propose using these methods to estimate shear wave velocity in wells without this parameter.
Highlights
Natural complexity of hydrocarbon reservoirs system is an important challenge in earth sciences
Compare the relationship between shear wave velocity and other parameters and petrophysical logs (GR, LLS, LLD, VP, NPHI, RHOB) showed that there is a close relationship between velocity of compressional and shear waves, especially in carbonate rocks (Figure 3 and Figure 4)
Empirical relationships are used to estimate shear wave velocity which are defined based on different lithologies and a few number of petrophysical parameters such as porosity and compressional wave velocity
Summary
Natural complexity of hydrocarbon reservoirs system is an important challenge in earth sciences. Classical dada processing tools and physical models were sufficient to solve relatively simple geology issues, but today we are dealing with more complex problems and relying on existing techniques, which are based on common methods. They are less satisfactory [1]. Shear wave velocity is one of the most important parameters in exploratory studies of petroleum and gas industry which hasn’t been measured in most wells due to high costs For this reason, numerous methods have been presented to estimate these parameters from other well logging data that are recorded in most wells. Numerous empirical relationships have been presented for calculating shear waves velocity but, in most cases, the results of these relationships aren’t desirable in different areas due to following reasons: 1) Various parameters affect the shear wave velocity, and all of them aren’t included in empirical relationships; 2) Mentioned relationships belong to a particular area or reservoir rock (with specific lithology and fluid) and using these relationships in other areas doesn’t present a good response because the rock and fluid properties change; 3) Most of performed studies in order to measure the shear wave velocity have been about sandstones and little studies have examined the carbonate rocks, while most of Iran reservoirs are in carbonate type and further studies is required on petrophysical parameters of carbonate rocks
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