Singularity spectrum of hydrocarbon fluids in synthetic seismograms

Abstract

Oil and gas exploration is the quest for hydrocarbon deposits trapped underneath the earth surface. Seismic is one of the hydrocarbon exploration tools. Significant efforts have been directed, in seismic processing and interpretation, to the development of methods such as spectral decomposition used for tuning hydrocarbon reservoirs and delineating it. In addition, statistical techniques are required to analyze variations in seismic traces. This research work is an alternative technique based on singularity spectrum analysis for detecting and delineating hydrocarbon reservoir. Singularity spectrum captures the singularities occurring in a signal. The technique is applied on synthesized seismograms and three attributes of the singularity spectrum namely width, correlation dimension and alphapeak are determined. Results show that by using these attributes the reservoir fluids are detected and delineated. Singularity spectrum analysis will potentially improve the performance of oil & gas industry by reducing drilling uncertainties, producing accurate geological models of 2D seismic data and for correct production estimates of reservoirs.