Το έργο με τίτλο Detection of gas in sandstone reservoir using AVO analysis in Prinos basin από τον/τους δημιουργό/ούς Choustoulakis Emmanouil διατίθεται με την άδεια Creative Commons Αναφορά Δημιουργού 4.0 Διεθνές
Βιβλιογραφική Αναφορά
Emmanouil Choustoulakis, "Detection of gas in sandstone reservoir using AVO analysis in Prinos basin", Master Thesis, School of Mineral Resources Engineering, Technical University of Crete, Chania, Greece, 2015
https://doi.org/10.26233/heallink.tuc.61648
This thesis was focused on an integrated approach of gas detection in the sandstone reservoir of Prinos oil field, located in the northern Aegean Sea between the island of Thasos and city of Kavala on the mainland. The rock properties variation with depth in the study area, were inferred from suite of quality controlled well seismic logs, while the geological structure of the model was based on an East-West 2D geological plan of Prinos basin. Furthermore, the top layer of the reservoir was considered to be 50% saturated with gas, so, its elastic parameters were accordingly adjusted. The above information were given as input to a synthetic data simulator (Applied Geophysics Laboratory of the Technical University of Crete) in order to build low frequency synthetic seismograms. Additionally, a signal processing graphical interface was build, in order to properly process the synthetic data before the application of the AVO analysis. The GUI can support the whole preprocessing scheme prior to the AVO analysis, from the commissioning of the SGY data, until the generation of the stacked and migrated sections, while the results can be represented graphically at any point. Finally, an analytical AVO analysis flow was adapted for the processed seismic data which successfully detected the presence of gas in the shallow gas saturated layer. The AVO analysis flow included rock physics analysis, intercept-gradient crossplots, far versus near stack attributes, detailed investigation of distance to amplitude analysis and AVO inversion for the elastic parmetres of the model.