Using Singularity Spectrum Attributes for Analyzing Homogeneity/Heterogeneity of Reservoir

Abstract

Over the last decade, spectral decomposition techniques have greatly improved seismic interpretation in the exploration of hydrocarbons. Significant efforts have been directed to the development of such methods for tuning hydrocarbon reservoirs, thin beds and channel estimation. Geological and geophysical changes of the earth formation manifest as discontinuities in a seismic trace. These discontinuities also called singularities thus carry most of the information in the trace. Statistical techniques are required to analyze these discontinuities in order to ascertain the variation in the fluid flow. This paper discusses a technique for detecting reservoir homogeneity/heterogeneity based on singularity spectrum attributes. Singularity spectrum determined from multifractal analysis, can globally describe the singularity content of a signal. Obtaining the singularity spectrum of signals also helps in the identification and classification of different state changes in a signal. The developed technique is applied on synthesized seismograms and two attributes of the singularity spectrum namely correlation dimension and width are determined. Results show that by using these attributes the heterogeneity or homogeneity of the reservoir can be evaluated. Such attributes can increase the reliability of suspected hydrocarbon zones; hence unravelling drilling uncertainties and is potentially useful for reservoir fluid flow modelling.