Submarines Lobe Geometry and the Average Grain Size Distribution Prediction based on Its Channel System
Vicky Ruliansatri, ..
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Submarine lobes are one of the favorable reservoir targets for hydrocarbon exploration and production. However, predicting the lobes geometry in the subsurface remains uncertain due to their complex geometries and limitation of existing subsurface data sets to define the internal architecture and the facies distribution of submarine lobes deposits. An analytical model, so-called Sediment Budget Estimator-Lobe (SBE-Lobe), is developed to predict the geometry of submarine lobes and the average grain-size distribution along their long axis. Lobes architecture is quantified based on the vertical grain size stratification, the velocity structure and the channel feeding configuration. The model development is started by integrating the Rouse Equation on to the SBE-Channel module, a process-based turbidity current model developed by Eggenhuisen et al. (2019a), to obtain complete series of concentration profile for all grain size classes. Subsequently, lobe geometry is predicted using the advection length approach. The modeling result is displayed in 2D. Validation of the model against the laboratory experiment suggests that this model can be used as the first-order prediction of lobe geometry. The model can locate the depositional area of the fine sand and very fine sand grain size class. It also provides a relatively good estimation of lobe thickness in the middle and distal areas. This model can be compared against bed and lobe element geometries that comprise of weakly compensational beds. Application of the SBE-Lobe to the ancient turbidite deposit has shown its consistency in predicting the sediment budget and its ability to predict the submarine lobe geometry and the average grain-size distribution based on the channel system within the amplitude of field data. Therefore, this tool potentially can be applied to the subsurface evaluation for predicting the gross reservoir volume, localize the potential area, and defining the reservoir boundary. However, the model still has limitations in predicting apex lobe geometry. The model appears to overestimate the lobe thickness in the proximal region and underpredict the sediment transport distance of the coarser particles. Future research should, therefore, aim to improve the model by incorporating the dynamic process that occurs in the channel lobe transition zone (CLTZ) into the model and coupling the effect of the temporal and spatial evolution of the flow velocity.