Publications

In subsurface analysis, efficiency is crucial. An accurate depiction of structural discontinuities from the seismic data is necessary for fault and fracture characterization. Currently, the conventional structural attribute methods are lacking in precision to provide a real and detailed picture of the distribution of faults and fractures in seismic data, as they only provide a qualitative visual representation and are difficult to be quantified. Full Azimuth Inversion (FAI) methods provide a more precise depiction, although they do require a lot of time, storage, specialized equipment, and cost to perform the analysis. This study presents a more efficient method for describing faults and fractures. The method is an integration and improvement on Fault Likelihood (FL) and Fault Thinning (FT), which helps to get an overview of the Fault Intensity (FI). The conventional fault attribute is upgraded to a Continuous Fault Probability (Fault Likelihood) by using a spherical scanning disc. The spherical disc scans seismic data in all 360 degrees azimuth directions and fault dip from 30 to 90 degrees (Sven et al., 2019), resulting in a better detection of the seismic discontinuities. Data suitable for the scanning disc method includes the conventional structural attributes, including Variance, Chaos, Coherency and Similarity (Bahorich et al. 1995; Gibson et al., 2003) in post-stack seismic data. The scanning disc method is implemented as a disc that can be rotated in all directions to scan all the structural attribute values. In the final stage, an averaging process is performed to combine all the scanning results into a single Fault Plane attribute. Furthermore, the Fault Thinning method uses the steepest gradient searching and peak value collection to determine the position of the fault. Thus, the continuous fault plane will be transformed into discrete data that only represents the peak value of the fault plane. The Fault Intensity algorithm uses the Fault Plane and Fault Thinning as inputs to determine the level of density of the fault patch. The Fault Thinning is transformed into a Fault Index that has been filtered from noise data. Subsequently, the multi-counting process on the Fault Index is performed to get the initial Fault Intensity. To maintain geological constraints, the Fault Damage Zone (FDZ) creation process is carried out using the Fault Plane. The gaussian smoothing and histogram analysis are used to generate the Fault Damage Zone attribute with a zero-cut-off value. The combination of the initial Fault Intensity and Fault Damage Zone results in the True Fault Intensity (TFI). In the final stage, the Relative Geological Time (RGT) model is used to extract surface attributes from the seismic data, which is useful for monitoring and quality control purposes. The integration of several algorithms allows for a quick generation of Fault Intensity attribute using only post-stack seismic data. The accuracy of the extraction process is further improved by the spherical scanning process, which considers the fault geometry in all orientations. This process can significantly assist in Discrete Fracture Network (DFN) modelling by providing a Fracture Character Image (FCI) that cannot be generated conventionally.