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SEISMIC ATTRIBUTES IN THE INTERPRETATION OF CHANNEL GEOMETRIES: THE CASE STUDY OF THE CONGO BASIN C. Giorgetti1, A. Corrao2, M. Ercoli1, M. Porreca1, M.R. Barchi1

1 Dipartimento di Fisica e Geologia, Università di Perugia, Italy2 ENI spa Upstream & Technical services

Introduction. Seismic attributes are commonly used in the oil & gas industry to improve the interpretability of seismic data (Taner et al., 1979; Chopra and Marfurt, 2008). The application of this technique to enhance the presence of geological features like channelized systems and faults may be helpful to extrapolate additional information from data, therefore improving the seismic interpretation potential. It may also help to identify and optimize study’s techniques for further processes of seismic interpretation.

We applied this technique to geological features of the lower Congo Basin. The geological framework of the area is the Angolan Passive Continental Margin. In this area the channelized systems of Zaire River and the wide fan of the Congo Basin develop with a length of about 800 km westward and a width of more than 400 km from Gabon to Angolan margins. The study region is characterised by turbidite systems within the Miocene deposits of the Malembo Formation, in a framework of extensional tectonics (Sikkema et al., 2000; Savoye et al., 2009).

Throughout the application of attributes that enhances local signal variations, changes in amplitude, phase and frequency, it was possible to highlight acoustic impedance contrasts,

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reflectors continuity/discontinuity and different local frequency contents. The use of multi-attribute display on the new attribute images enhances the possibility to detect different geophysical signatures reflecting variations of geological features.

Data and Methods. The dataset used in this work is an offshore Pre-Stack-Time Migration (PSTM) 3D seismic volume.

The seismic attributes selected and computed were the Root Mean Square (RMS), Spectral Decomposition and Coherence.

The RMS is an amplitude-based attribute that provides a scaled estimate of the trace envelope and so it measures the reflectivity, therefore highlighting variations in acoustic impedance. It is computed in a sliding tapered window of N samples as the square root of the sum of all the trace values divided by the number of N samples. Generally, the higher are the acoustic impedance variation, the higher are the RMS values. High RMS values in channels may result from a high acoustic impedance contrast of channel fill with the surrounding lithologies.

The Spectral Decomposition is a frequency-based attribute that transforms the seismic data into the frequency domain via the discrete Fourier transform; the amplitude spectra delineate temporal bed thickness variability, while the phase spectra indicate lateral geologic discontinuities (Partika et al., 1999; Puryear et al., 2012). It is a useful tool to push the seismic interpretation to a “below resolution” level, commonly used for sand thickness estimation, and particularly useful to enhance channelized structures. The Coherence attribute is a measure of the similarity between seismic traces in a specified window that gives an indication of the traces continuity for example along a picked horizon (Gersztenkorn and Marfurt, 1999). It gives information on lateral changes in waveform. It can be used to map the lateral extent of a formation, as well as used to improve faults visualization, channels boundaries or other discontinuous features.

In our workflow, these attributes were computed along seven horizons, each one over an area of 375 km2 and 60 milliseconds (TWT) of interdistance, to investigate about 550 m of the 3D volume (using a mean velocity of 2800 m/s). The attributes were mostly applied on such horizons but, in some cases, also on the seismic inlines/crosslines and time-slices in order to compare the geometries and the relationships of complex reflections.

Results. The results obtained after the application of the three attributes are related to the specific characteristic of each attribute computed. RMS amplitude allowed inferring variation of lithologies along the channels in accordance with the acoustic impedance contrasts, in particular from the channel fill and the levees (Fig.1). Coherence attribute enhanced the lateral

Fig. 1 - Crossline with RMS attribute applied on horizon. The blue arrows indicates the areas of the horizon and seismic line where there is an high value of acoustic impedance contrast.

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discontinuities of the horizons, therefore allowing to better identifying channels geometries, fractures and faults (Fig. 2). Combining Coherence with other attributes, it was also possible to display how extensional tectonics affected the area by disrupting the channel features. The

identification of these complex channels patterns was also aided by the Spectral Decomposition attribute, by introducing a chromatics visualization that emphasize their visualization, otherwise unclear in the standard seismic sections and time-slices (Fig. 3). Lateral changes of seismic facies and thickness variations were strongly enhanced by Red Green and Blue (RGB) colour blending, which provides effective “maps” of the inner channels geometries.

The simultaneous use of different attributes and their comparison allowed to discriminate geological elements and their linkage.

The multiple combination of attributes, made it possible to analyse the channels geometrical characteristics like width, length and variations with depth, calculating “Sinuosity Index” (Leopold and Wolman 1957; Brice, 1974), ranging from straight (Is=1) to meandering channels (Is>1.5). The results highlighted in this work, through the identification of morphologic,

Fig. 2 - Coherence attribute applied both on horizon and on the seismic line to enhance the visualization of structural features.

Fig. 3 - Horizons with the application of attributes of: a) RMS; b) Spectral Decomposition.

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sedimentary and structural elements are fundamental in the characterization of the study area, to help further processes of seismic interpretation and to improve the geological knowledge of this region.Acknowledgments. Thanks to ENI spa Upstream & Technical services (GEOS unit) for the opportunity given to develop this project.

ReferencesBrice J. C.; 1974: Evolution of meander loops. Geological Society of America Bulletin, 85(4), 581-586.Gersztenkorn A. and Marfurt K. J.; 1999: Eigenstructure-based coherence computations as an aid to 3-D structural

and stratigraphic mapping. Geophysics, 64(5), 1468-1479.Leopold L. B. and Wolman M. G.; 1957: River channel patterns: braided, meandering, and straight. US Government

Printing Office.Partyka G., Gridley J. and Lopez J.; 1999: Interpretational applications of spectral decomposition in reservoir

characterization. The Leading Edge, 18(3), 353-360.Puryear C. I., Portniaguine O. N., Cobos C. M. and Castagna J. P.; 2012: Constrained least-squares spectral analysis:

Application to seismic data. Geophysics, 77(5), V143-V167.Savoye B., Babonneau N., Dennielou B. and Bez M.; 2009: Geological overview of the Angola–Congo margin, the

Congo deep-sea fan and its submarine valleys. Deep Sea Research Part II: Topical Studies in Oceanography, 56(23), 2169-2182.

Sikkema W. and Wojcik K. M.; 2000: 3D visualization of turbidity systems, Lower Congo Basin, offshore Angola. In Deep-Water Reservoirs of the World, Gulf Coast Section Society of Economic Palaeontologists & Mineralogists Foundation, 20th Annual Conference of Deep-Water Reservoirs of the World Proceedings, December (Vol. 3, No. 6, pp. 928-939).

Taner M. T., Koehler F. and Sheriff R. E.; 1979: Complex seismic trace analysis. Geophysics, 44(6), 1041-1063.