TITLE:
Assessment of the Spectral Decomposition Techniques in the Evaluation of Hydrocarbon Potential of “BOMS” Field, Coastal Swamp Niger Delta, Nigeria
AUTHORS:
Charles Chibueze Ugbor, Onyebuchi Samuel Onyeabor
KEYWORDS:
Amplitude, Hydrocarbon Evaluation, Spectral Analysis, Reservoir Sand, Basic Pursuit, Convolution
JOURNAL NAME:
International Journal of Geosciences,
Vol.14 No.7,
July
31,
2023
ABSTRACT: This study employs the different approaches of the spectral decomposition
techniques to evaluate the hydrocarbon potential of the reservoir and analyse
to determine the most efficient spectral decomposition technique with better
resolution using the “BOMS” Field, coastal swamp depobelt Niger Delta, Nigeria. A good number of
drilled wells have failed both in the Niger Delta Basin and other basins due to
a poor understanding of the reservoir properties in advance of drilling and
identifying the best approach will help to minimize this risk. Seismic and well
logs data together with the Hampson Russel 10.3 software were used for the
study. The target reservoirs were identified from the suite of well logs at the
horizons with low gamma ray, high resistivity, and low acoustic impedance
between TVD (ft) of 10,350 - 10,450 ft. The analysis of the amplitude spectrum
of the seismic data revealed that the distortion of interest lies between 5 -
60 Hz. Seismic data were then spectrally decomposed into several frequencies
such as low frequency (15 Hz), mid-frequency (31 Hz), and high frequency (46
Hz) where distortions were observed. Time- frequency
slices of 15 Hz and 23 Hz provided clearer events (potential hydrocarbon sand)
indicated by high amplitude envelope (2200 - 2400) and amplitude anomalies.
While the amplitude dropped in the mid-frequency (31 Hz), the high amplitude
envelope and the high energy completely disappeared in the high (46 Hz)
time-frequency slice. A comparison of the Short- time
Fourier transform and the Basic Pursuit algorithm revealed that the Basic
Pursuit provided a better resolution of the reservoir characteristics than the
former. The Red, Green and Blue (RGB) colour blending model indicated that the
channel was consistent with the low-frequency section and amplitude anomaly.