Abstract
Seismic attributes can be important predictors, either qualitative or quantitative, of reservoir geometries when they are correctly used in reservoir characterization studies. This paper discusses seismic attribute analyses and their usefulness in seismic geomorphology study of Moragot field of Pattani Basin, Gulf of Thailand. Early to Middle Miocene fluvial channel and overbank sands are the reservoirs in Pattani Basin. Due to their limited horizontal and vertical distribution, it is not always possible to predict the geometry and distribution of these sands based on the conventional seismic interpretation. This study utilized various seismic attributes, e.g., RMS amplitude analysis, spectral decomposition, semblance and dip-steered similarity, RGB blending to image the geometry and the spatial distribution of sand bodies in horizon and stratal slices at different stratigraphic intervals. Attribute analyses reveal, at shallow stratigraphic levels, RMS and semblance can successfully identify channel-shaped sand bodies and mud-filled channels associated with channel belts. On the other hand in deeper stratigraphic intervals, sand distribution can be imaged more effectively by using spectral decomposition and dip-steered similarity volumes. High-frequency spectral decomposition slices can image thin sands, and low-frequency slices can image thick sands quite effectively in deeper intervals. RGB blending of different frequency slices is particularly useful in delineating channel systems of various dimensions at deeper intervals. These images show the distribution of sands and mud-filled channels at various stratigraphic levels. The width of channel belts varies from 200 m to 3 km. These channel belts are N–S or NW–SE oriented. From the channel pattern and their dimensions, depositional environments can be predicted. Mud-filled channels identified in the horizon slices will act as a connectivity barrier between sand bodies at either side of the channel. They can also act as lateral and up-dip seal to form stratigraphic traps. The seismic attribute analyses clearly show the geometry and spatial distribution of sand bodies. Hence, this method for predicting sand body geometry might help in field development planning as well as in reducing exploration risk.
Highlights
Recent development of three-dimensional (3D) seismic datasets enables geologists to visualize and analyze buried lands and seascapes revealed by subsurface geophysical data in a manner resembling surface geomorphology (Miall 2002; Davies et al 2007)
Seismic attribute analysis can extract information from seismic data that is otherwise hidden in the data and has been used to identify prospects, ascertain depositional environments, detect and enhance faults and fracture sets to unravel structural history, and even provide direct hydrocarbon indicators (Burnett et al 2003; Castagna et al 2003; Chopra and Marfurt 2007; Farfour et al 2012)
To study seismic geomorphology in each period, several stratal and horizon this method as high amplitude conforms to high semblance slices were generated from the interpreted seismic horizons. value
Summary
Recent development of three-dimensional (3D) seismic datasets enables geologists to visualize and analyze buried lands and seascapes revealed by subsurface geophysical data in a manner resembling surface geomorphology (Miall 2002; Davies et al 2007). The seismic attribute technique should allow us to increase ability of geological interpretation of a formation, in the thin-bed reservoir environments (Farfour and Yoon 2014). Seismic attributes typically provide information relating to the amplitude, shape, and position of seismic waveform. Seismic attribute analysis can extract information from seismic data that is otherwise hidden in the data and has been used to identify prospects, ascertain depositional environments (e.g., fluvial or deep-water channels, carbonate buildups), detect and enhance faults and fracture sets to unravel structural history, and even provide direct hydrocarbon indicators (Burnett et al 2003; Castagna et al 2003; Chopra and Marfurt 2007; Farfour et al 2012)
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