Hermite distributed approximating functionals and simple moving average to upscale and identify the productive layer from well-log data

Pair Correlation Function (PCF) approximation method takes into account the effect of scattering by considering the interactions between any two points of a random heterogeneous medium. In a random heterogeneous media, the amplitude of the fluctuations of the correlation function will be higher if the properties of the inclusions are drastically different from the matrix and consequently, the PCF has numerous applications like solving the upscaling problems, detecting heterogeneity etc. In clastic sediments, the heterogeneity will be maximum when the inclusions are filled with oil or gas. This is considered a very useful property in differentiating the productive from the non-productive layer. In this study Hermite Distributed Approximating Functionals (HDAFs) and Simple Moving Average (SMA) are used as the averaging or upscaling methods for calculating the amplitude of the fluctuations from well log data to detect the productive layer for frequencies ranging from 30 Hz to 1000 Hz. The results show that to detect the productive layers at lower frequencies that corresponds to seismic data, HDAF gives better results. Presentation Date: Wednesday, September 27, 2017 Start Time: 11:25 AM Location: 351D Presentation Type: ORAL