Rock Physics Based Seismic Forward Modeling for Channel-Like Feature Detection
Abstrak
In the oil and gas industry, rock physics-based forward modeling has become an essential tool that allows geoscientists to better interpret the subsurface and understand the behavior of rocks under different conditions (Avseth et al., 2005). Forward modeling aims to simulate the seismic response of a given geological model, taking into consideration the elastic properties of the rocks and the seismic acquisition parameters. This approach has been widely used in the industry to gain insights into subsurface geology and unlock potential challenging and complex reservoirs, as noted by Landro (2001) in his work on seismic attribute analysis. In recent years, there has been an increasing interest in stratigraphic traps and reservoirs, mainly channelized facies, which are commonly indicative of potential hydrocarbon reservoirs (Weber, 1986). However, these features can be very tricky and challenging to detect in seismic data due to the complexity of the subsurface geology and the limitations of seismic data. To overcome these challenges, rock physics-based forward modeling can be an ideal tool to provide a more detailed understanding of the seismic responses caused by different rock types, porosities and fluid contents (Bachrach et al., 2000). The purpose of this study is to investigate the use of rock physics-based forward modeling in detecting "Channel-like" features in seismic data. During the seismic horizon interpretation phase, a clear pattern of a "pull-up/pull-down" seismic feature was observed in channelized facies as seen in Figure 1, which may indicate the presence of a hydrocarbon reservoir (Dvorkin et al., 2014). However, it is essential to understand the underlying causes of this feature, whether it is related to geological aspects or seismic artifacts, as noted by Xu and White (1995) in their work on velocity models for clay-sand mixtures.
Penulis (1)
A. Alkhunaizi
Akses Cepat
- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- CrossRef
- DOI
- 10.2118/227394-ms
- Akses
- Terbatas