GNGTS 2024 - Atti del 42° Convegno Nazionale

Session 3.1 GNGTS 2024 WIGGLE2SEGY is a code developed by Sopher in 2017 using Matlab. It is available to the scientfc community to convert scanned images of stacked refecton seismic data to the standard SEG-Y format. The code is designed to work directly on the image characteristcs and can recognize and eliminate the signal associated with tmelines and baselines. This code is partcularly useful in removing noise associated with paper data due to the storage and retenton of the data itself. Moreover, WIGGLE2SEGY applies a frequency flter to eliminate artfacts with frequencies outside the bandwidth of the data, as described in Butnelli et al. (2022). Before the applicaton of seismic atribute analysis, an AGC (automatc gain control) was applied to seismic data to bring up weak signals. The further step is the applicaton of seismic atributes to highlight and identfy some discontnuites in the seismic data that are helpful for fault and fracture characterizaton (Fig. 1). Fig. 1 - An example of vectorizaton results from the VIDEPI dataset, using the process described in this study. a) Scanned image of line FR-309-80. b) SEG-Y fle extracted from the scanned image in a), ploted with similar parameters to the original, c) same SEG-Y data as in b) ploted with a variable density display. d) applicaton of seismic atribute “semblance”; e) applicaton of seismic atribute “pseudo-relief”. Results Analysis of atributes integrated into the refecton seismic interpretaton, mainly for 2D and 3D seismic data, allowed beter detecton of faults and fractures of the carbonate reservoir in the project's area of interest. Some vintage 2D seismic lines were tested using several post-stack atributes, including semblance/coherence and pseudo-relief, using OpendTect sofware. This method has created a dataset of vectorized seismic profles that can be shared with the scientfc community. This helped with the structural interpretaton of the study area, improving the public structural isochrone maps available in the public database. In this case, we have used scientfc analyses like seismic atributes despite having only 2D seismic data. Seismic atributes can detect faults and fractures, stratgraphic discontnuites, and identfy hydrocarbon volumes. Our study displays the outcome of vectorizaton and enhancement of seismic data by applying atributes like automatc gain control and convolve and other seismic atributes such as coherence, curvature, and pseudo-relief, which are suitable for characterizing geothermal reservoir structures (Fig. 2). Thanks to the new digitalized and vectorized dataset and the applicaton of seismic atributes analysis, it has been possible to a beter defniton and interpretaton of the interface between