In this paper a workflow is presented where seismic inversion facies probability trends along with facies classification from Heterogeneous Rock Analysis (HRA) have been integrated to model the submarine channels to slope fan lobe systems. The slope fans (which were dominantly showing a mix system i.e. sand – shale) and submarine channels were extremely heterogeneous in terms of facies classification. In addition both these depositional systems represented highly variable geomorphology, where fluvial channels ranged from minimum of 5 meters thickness to maximum 15 meters (which represented both amalgamated / stacked channels). The slope fans ranged from few 100's of meter spatial spread to 2 km with sand thickness ranging from 10 – 30 meters.

The challenge in this depositional setting was to map the channels and slope fans both on seismic dataset and then later on to accurately delineate their dimensions and geomorphology. In order to establish the realistic sand thickness parameters using simple geostatistical variograms along with trends maps were not enough therefore, seismic inversion fluvial channel probability cubes were used to determine both the vertical and spatial spread of these depositional patterns.

The petrophysical rock classes derived from the Heterogeneous Rock Analysis method captured the facies variation within these depositional systems very effectively. The HRA classes integrated with the core results captured 4 main rock classes which were; Sand Channels, Channel Levee and Proixmal Slope fan facies (dominantly sands) to distal shalier fractions.

These 4 (Four) facies were then integrated with the inverted seismic results to check for consistency if these were good enough to be calibrated. The seismic inversion resulted in the contruction of several different probability guided trends to maps the fluvial channels and the slope fans. These geomorphological patterns helped in the quantitative delineation of the fluvial channels to the slope fans.

The next step was to analyze the geomorphological parameters of these depositional systems in context of the seismic probability trends. As a result several different orders of fan systems were observed, the largest being several km wide and 2 – 4 km in length while the smallest fan lobes were documented to be having 100 – 200 m spread to 400 – 500 m length. The dimensions of these geobodies were then extracted and integrated into the reservoir model which very effectively captured the facies variation and spatial distribution of these depositional bodies initially based on the seismic inversion results.

The resulting model suggested that only one half of the analyzed reservoir section contained the good quality sands which displayed better communication and connectivity. These sands were then targeted for further field development and lead to the successful testing of the newly drilled well in the area which also lead to opening of a new area for field development.

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