Continuous Wavelet Transform Based Spectral Decomposition of 3d Seismic Data for Reservoir Characterization in Oyi Field, se Niger Delta

Abstract

Continuous Wavelet Transform (CWT) is one of the most used wavelet transform based spectral decomposition methods in the direct detection of hydrocarbons and as an indicator of stratigraphic variability due to its optimal time-frequency resolution and variable time window requirements. CWT based spectral decomposition was applied on a 3D Post Stack Time Migrated (PSTM) seismic data acquired over a producing field using morlet wavelet and a time varying analysis window. Frequency amplitude slices of 10 Hz to 50 Hz were extracted from a 1625 ms HD1 seismic horizon and analyzed for possible hydrocarbon indications and stratigraphy. Hydrocarbon filled reservoir sands were delineated as low frequency high amplitude spectral anomalies between 20 Hz to 30 Hz frequency band coincident with the locations of producing wells in the field. Also, high frequency high amplitude spectral anomaly were delineated at predominantly 50 Hz frequency indicating a thin-bed with probable hydrocarbon saturation particularly gas, suspected to be a bypass hydrocarbon zone. Result also shows amplitude diminution with increasing frequency attributed to local variations in lithology. Therefore, appropriate application of this method will improve reservoir characterization and enhanced bed thickness definition, de-risk prospects and minimize dry well drilling in the field.

Seismic amplitudes and spectral attribute analysis in reservoir characterisation, ‘MUN’ onshore Niger delta field

“…Spectral attribute slices were extracted along H4 horizon within the seismic bandwidth (5 to 60 Hz) of the seismic data. The attribute slices delineated channel sand-like structure by high-amplitude low-frequency anomaly, characteristic of hydrocarbon saturation (Othman et al 2016;Ehirim and Akpan 2017). The structure trends NE-SW, broadening towards the southwest and bounded by major growth faults similar to the result of the seismic amplitudes.…”

“…Stratigraphic units within the channel structure were adequately resolved and characterised by amplitude brightening at low and high frequencies, dominated mostly by the yellow and purple colours, respectively. This suggests hydrocarbon presence of saturating thick and thin reservoir sands, respectively (Partyka et al 1999;Chopra and Marfurt 2013;Ehirim and Akpan 2017;Wei et al 2019). The wells are located on and along the channel sands to the southwest.…”

“…Previous studies have independently demonstrated the effectiveness of seismic reflection amplitudes and spectral attribute analysis as direct hydrocarbon indicators (DHI), mapping of stratigraphic units and structures and evaluation of reservoir properties (Partyka et al 1999;Marfurt and Kirlin 2001;Othman et al 2016;Ehirim and Akpan 2017). However, seismic amplitude is encumbered by ambiguity due to acquisition footprints, processing and imaging errors, surface conditions and geologic factors, which can lead to amplitude interpretation pitfalls during reservoir characterisation if not validated (Houk 1999;Harilal 2010).…”

“…The reflection amplitude is a function of frequency in fluid-saturated media. Hydrocarbons produce a brightening effect (high amplitude) on a low-frequency section characteristic of a porous and thick hydrocarbonsaturated reservoir (Ehirim and Akpan 2017).…”