Wavelet Transform Applications in Reservoir Data Characterization

The main goal of reservoir characterization is to estimate the spatial distribution of reservoir properties such as porosity, permeability, and oil saturation. For reservoir management the accurate estimation of reservoir properties is essential. One of the key ideas in reservoir characterization is data scaling up. The objective of the scaling up is to reduce the number of cells from the main models without losing the important flow behavior of the fine models. Wavelet analysis is a multi resolution framework and, thus, it is well suited for upscaling rock and flow properties in a multi scale heterogeneous reservoir. The large family of wavelets provides a flexible way to control the smoothness of the resulted upscaling properties but in this case all mother wavelets are not suitable. This paper addresses the problems of data analysis and scale change by introducing wavelet transform approach that is amenable to analysis and scaling of nonstationary data. This paper is the extension to the work of M.N.Panda et al. on Reservoir Property Estimation. For comparing the impact of mother wavelet shapes on output data, some another type of wavelet shapes are used on Panda’s data.

Wavelet Transform Applications in Reservoir Data Characterization Keywords:

Wavelet Transform , Reservoir Characterization , Permeability data , Scale up , Denoising