Porosity prediction of lower cretaceous unconventional resource play, south Indus Basin, Pakistan, using the seismic spectral decomposition technique

2018 ◽  
Vol 11 (10) ◽  
Author(s):  
Muhammad Tayyab Naseer ◽  
Shazia Asim
2013 ◽  
Vol 868 ◽  
pp. 150-153 ◽  
Author(s):  
Xu Tao Li

Seismic attributes analysis were used to predict the sand distribution in this paper. Spectral decomposition technique was carried out in frequency domain. Spectral seismic attributes made an identification of target geological-mass from time domain to frequency domain in Lower U sandstone of HMO 3D area. The 40hz frequency attribute was the best attribute to predict sand distribution. Seismic waveform classification for Lower U sandstone with the time window from-7ms to +7ms of Lower U sandstone had a good relationship with the sandstone distribution. With the comprehansive analysis of borehole oil and gas distribution and seismic attributes characteristics, a prospective oil and gas area target was determined.


Author(s):  
Oyelowo Gabriel Bayowa ◽  
Theophilus Aanuoluwa Adagunodo ◽  
Adeola Opeyemi Oshonaiye ◽  
Bisola Stella Boluwade

2019 ◽  
Vol 94 (3) ◽  
pp. 319-327 ◽  
Author(s):  
Perveiz Khalid ◽  
Jahanzeb Qureshi ◽  
Zia Ud Din ◽  
Sami Ullah ◽  
Javed Sami

2021 ◽  
Vol 10 (1) ◽  
pp. 1-7
Author(s):  
O.K. Olaleye ◽  
P.A. Enikanselu ◽  
M.A. Ayuk

Spectral Decomposition Technique based on Short-Window Discrete Fourier Transform (SWDFT) was applied to threedimensional (3D) seismic data obtained from ‘Reigh’ field, onshore Niger Delta with a view to enhancing stratigraphic interpretation for geological features which are beyond seismic resolution. Two sands units from the study area were studied to produce spectrally decomposedsurfaces. The result of the study revealed thin bed layer at the centre of the field on sand unit ‘A’. Sand-filled meandering channel wasdetected and highlighted in the northern part of sand unit ‘B’ based on Red-Green-Blue frequency modulation of spectral  decomposition. The study has enhanced geologic understanding of the field by improving thin bed resolution, highlighting geologic features and displaying bed thickness variation of studied sand units in the study area. Keywords: geologic features, Niger Delta, seismic data, spectral decomposition


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