Stratigraphic Forward Simulation of the Miocene Fan Delta in the South of Albert Basin, Uganda

Abstract

Abstract The Albert Basin of Uganda is located at the northern end of the western branch of the East African Rift System. It is a graben rich in oil and gas with a shallow research degree. In the south of the basin, a fan delta system controlled by the boundary fault is developed in the Miocene formation. Due to the few wells and poor quality of seismic data in this area, it is difficult to predict the spatial distribution of sedimentary reservoir sands. In this paper, sedimentary forward modeling coupled with 3D geological modeling is used to provide new ideas for reservoir prediction. Sedimentary facies analysis is based on core description, well logs, paleontology, heavy mineral content and grain size data. Quantitative analysis of accommodation space, source supply, and sediment transport parameters can help explain the main factors that controlled the sedimentation. Milankovitch cycle method was used to establish the time scale of the basin. The simulation results were combined with 3D geological modeling to quantify the characteristics of the sand body distributions. Sedimentary facies analysis shows that the Miocene formation in the south of Albert Basin deposited in a shallow lacustrine environment. A proximal fan delta deposition with subaqueous distributary channels was controlled by the east boundary faults. Firstly, the accommodation space was estimated according to the thickness of the stratum and the change of the ancient water depth. The source supply was estimated by the area of the project and formation thickness, and the transportation parameters were estimated according to the nonlinear transportation model based on the traction flow with a little gravity flow. Secondly, an astronomical stratigraphic framework of the Miocene strata in the south of Albert basin was established through the Milankovitch cycle stratigraphy, and it was used to restrain the process of stratigraphic forward modeling and to reproduce the sedimentary evolution process in the geological historical period. Thirdly, the stratigraphic forward modeling results were resampled into the geological model, a 3D reservoir probability distribution model is established from trend modeling to quantitatively characterize the spatial distribution of sand bodies. Finally, the sandstone distribution simulation results were transformed into quantitative control constraints for 3D geological facies modeling. Thus, the new approach significantly promotes the facies model quality and provides robust results for petrophysical property models. Integration of stratigraphic forward modeling with 3D geological modeling can effectively solve the problem of reservoir characterization in an early stage of oilfield development through the interaction of the dual model coupling. This method has unique advantages in the reservoir research in the area with fewer data and great variation of sand.