Deepwater lobes constitute a significant volume of submarine fans and are primarily believed to exhibit a simple sheet geometry. However, recent studies interpret the geometries of these deep-marine lobes as distinct with respect to the complexity of the facies and their distribution. Hence, a conceptual model of deep-marine sediments is essential to discuss the deep-marine sediments associated with the fan and lobe architecture. The present study highlights the facies heterogeneity and distribution of various lobe elements at a multiscale level by considering a case study of the West Crocker Formation of Sabah in northwest Borneo. The formation was logged on a bed-to-bed scale from recently well-exposed sections, with a total vertical thickness of more than 300 m. The lithological characteristics, bed geometry, sedimentary textures and structures of individual beds were used to categorize the rock units into nine sedimentary lithofacies: five sandstone lithofacies (S1–S5), one hybrid bed facies (H), two siltstone facies (Si1 and Si2) and one shale or mudstone facies (M). These facies were grouped into four facies associations (FA1–FA4), which were interpreted as lobe axis (FA1), lobe off-axis (FA2), lobe fringe (FA3) and distal fringe to interlobe (FA4) facies associations. This study is applicable for the distribution of lobes and their subseismic, multiscale complexities to characterize the potential of hydrocarbon intervals in deep-marine sand-shale system around the globe.

3D-seismic data have increasingly shifted seismic interpretation work from a horizons-based to a volume-based focus over the past decade. The size of the identification and mapping work has therefore become difficult and requires faster and better tools. Faults, for instance, are one of the most significant features of subsurface geology interpreted from seismic data. Detailed fault interpretation is very important in reservoir characterization and modeling. The conventional manual fault picking is a time-consuming and inefficient process. It becomes more challenging and error-prone when dealing with poor quality seismic data under gas chimneys. Several seismic attributes are available for faults and discontinuity detection and are applied with varying degrees of success. We present a hybrid workflow that combines a semblance-based fault likelihood attribute with a conventional ant-tracking attribute. This innovative workflow generates optimized discontinuity volumes for fault detection and automatic extraction. The data optimization and conditioning processes are applied to suppress random and coherent noise first, and then a combination of seismic attributes is generated and co-rendered to enhance the discontinuities. The result is the volume with razor sharp discontinuities which are tracked and extracted automatically. Contrary to several available fault tracking techniques that use local seismic continuity like coherency attributes, our hybrid method is based on directed semblance, which incorporates aspects of Dave Hale’s superior fault-oriented semblance algorithm. The methodology is applied on a complex faulted reservoir interval under gas chimneys in a Malaysian basin, yet the results were promising. Despite the poor data quality, the methodology led to detailed discontinuity information with several major and minor faults extracted automatically. This hybrid approach not only improved the fault tracking accuracy but also significantly reduced the fault interpretation time and associated uncertainty. It is equally helpful in detecting any seismic objects like fracture, chimneys, and stratigraphic features.