Identification of shallow geohazard channels based on discontinuity seismic attributes in the South Caspian Sea

Abstract

Identification of geomorphological features in seismic data is a key element of seismic interpretation. Channels in the shallow subsurface are potential geohazards. At deeper levels, they can be the actual targets for (horizontal) drilling. Either way, it is important to optimally delineate these features prior to well location positioning and drilling. We have studied a poststack 3D seismic data from the South Caspian Sea featuring shallow channels that are considered potential geohazards for drilling operations. In the first step, we attenuate the acquisition footprints along the inline direction using a geostatistics approach based on factorial kriging. To better visualize channels in the presence of stratigraphic dips, we create a dense set of horizons using an inversion-based flattening algorithm. In the next step, we compare various discontinuity attributes such as semblance, similarity, curvature, and the relatively new attribute based on the multiscale and multidirectional shearlet transformation to determine which one best images our features of interest. Curvature attributes clearly image channel levies (positive curvature) and channel centers (negative curvature). Lateral changes in the curvature magnitude infer sedimentation from the north. Similarity, semblance, and shearlet transform attributes also successfully delineate channel edges, but these attributes do not contain additional geologic information. In the final step, we qualitatively analyze channel thickness variations by the red-green-blue blending of three spectral components based on short window Fourier transforms.

Extensional Faulting Around Kolumbo Volcano, Aegean Sea—Relationships Between Local Stress Fields, Fault Relay Ramps, and Volcanism

“…We first calculated a “dip steering” volume, which contains local reflection dip and azimuth information at every trace position (e.g., Tingdahl & De Rooij, 2005). This dip steering volume was used to calculate “dip‐steered similarity,” where the algorithm uses the local dip around each trace to find trace segments to compare, rather than simply comparing trace segments horizontally (e.g., Karbalaali et al., 2018). This approach can enhance the imaging of discontinuities within 3D data.…”

Characterization of reservoir sands using 3D seismic attributes in the coastal swamp area of Niger Delta Basin

“…Figure 2 a and b shows the display of geomorphology of sands A and B respectively using coherence attribute. Geomorphological features identification is an important element in seismic interpretation (Karbalaali et al 2018). This is because these features control hydrocarbon accumulation in a reservoir by serving as hydrocarbon traps and/or seals.…”

“…Seismic attributes describe these reservoir properties by giving derivatives of quantities extracted from the seismic data (Chen and Sidney 1997) to relate the seismic wave's event directly or indirectly to geology. As such, seismic attributes analyze subsurface heterogeneity by describing its geomorphology (Chen et al 2020;Fengming et al 2018;Karbalaali et al 2018;Schneider et al 2016), facies changes (Bueno et al 2014;Chinwuko et al 2015;Wang et al 2017) and physical properties (Dupucy et al 2016;Ogiesoba et al 2019;Nawaz et al 2020) in terms of quality, quantity, and area extent. Seismic attributes analysis has been efficient, over the years, for geomorphology analysis (Bailey et al 2016;Karbalaali et al 2018) qualitative and quantitative interpretation (Torrado et al 2014;Ngoc et al 2014;Bhattacharya and Verma 2020;Malik et al 2020) of hydrocarbon fields.…”

“…As such, seismic attributes analyze subsurface heterogeneity by describing its geomorphology (Chen et al 2020;Fengming et al 2018;Karbalaali et al 2018;Schneider et al 2016), facies changes (Bueno et al 2014;Chinwuko et al 2015;Wang et al 2017) and physical properties (Dupucy et al 2016;Ogiesoba et al 2019;Nawaz et al 2020) in terms of quality, quantity, and area extent. Seismic attributes analysis has been efficient, over the years, for geomorphology analysis (Bailey et al 2016;Karbalaali et al 2018) qualitative and quantitative interpretation (Torrado et al 2014;Ngoc et al 2014;Bhattacharya and Verma 2020;Malik et al 2020) of hydrocarbon fields. The application and efficiency of seismic attributes for stratigraphic features characterization is emphasized by the works of Marfurt (2005, 2008), Cuesta et al (2009), Vohs et al (2015), Roden et al (2016), Zhao et al (2016), Jie et al (2017), Othman et al (2018), Xing et al (2019, Adekunle et al (2020) among others.…”

Geological Structure Interpretation of Coalbed Methane Enrichment Area based on VMDC and Curvature Attributes

“…Hunt et al [27] focused on the window size and filtering methods for seismic curvature estimates. Karbalaali et al [28] pointed out that the positive curvature attribute can clearly image channel levies, and the negative curvature can clearly image channel centers. The above methods mainly focus on the curvature attribute algorithm and its application.…”