Increasing The Resolution of Seismic Imaging With Spectral Blueing, Spectral Decomposition RGB And HSV Blending to Delineate The Fluvial Facies on Fluvio Deltaic Environment

Abstract

The common issue that arises in geological modeling is the limited ability of the data to describe the spatial and vertical circumstances of facies and subsurface sediment deposits. Vertically, well data is high-resolution data that can describe one-dimensional objects in detail. On the other hand, seismic data can describe three-dimensional conditions but has a resolution bandwidth that is distant below the well data. Therefore, this study offers an integration method that can increase the seismic frequency to approach the ideal frequency to separate geological facies events vertically and laterally. The method used is Spectral Blueing, which will then be visualized using RGB and HSV Blending from the input data in the form of Spectral Decomposition. Spectral Blueing aims to increase the dominance of Blue Spectrum by analyzing the slope spectrum of the well data, bandpassing, and analyzing the deconvolution operator. In this method, the spectrum of the well data is used to examine the slope of the blue spectrum component, which is absent in the seismic data. This process produces a deconvolution operator that plays a part in increasing the blue spectrum area. Thus, geological events in the red, green, and blue spectrum are not muted or dominant. The entire frequency range of seismic data can maximally indicate geological anomalies and separate thin layers. The results are then analyzed on the AOI Horizon for specific spectral decomposition. Using the Continuous Wavelet Transform (CWT) method, several seismic energy cubes from the spectral decomposition are generated. Specific frequencies include 34, 42, 56, 63, 75, and 80 Hz. Each of these specific spectra carries different geological information. The separation of these anomalies aims to obtain specific and accurate dominant frequencies in each formation. The six dominant frequencies obtained from the spectrogram analysis will be input parameters for the graphic visualization process using RGB and HSV blending. The RGB method will provide an overview of geological features, while the HSV method will produce visualizations that still show the energy effects of seismic data. Several combinations of color blending visualizations of six specific frequencies are used to map and define the distribution of geological event anomalies printed in real terms and printed in the form of shadows. It is recorded right in the formation and zone of interest. While printed in a shadow is a pseudo-event anomaly, noise, or multiple events that are also recorded not in the actual formation. The final result of this method is a facies model with a more reasonable level of confidence and has been filtered using geological and geophysical concepts based on seismic data with an even dominance in each frequency range. The characterizations of facies found using this method include channel sand, point bar and point bar scroll, overbank or floodplain, chute channel, and abandoned channel. The results have also been validated using well data and local, and regional geology.