Facies Model Building of Integrated Multiscale Data In Dn-Field, Onshore, Niger Delta, Nigeria

Abstract

This study employs 3D Post-Stack Time-Migrated seismic data from the DN-Field, within the Coastal Swamp depobelt of the Niger Delta in predicting lithofacies and fluvial facies of OVK-1 sand bodies in the Agbada Formation, as a tool to identify new drillable prospects. A lithofacies model for OVK-1 reservoir sand body was generated after upscaling using Most Of, as the averaging method. Calibrated by fluvio-facies at the well locations, channel sands were identified in OVK1 reservoir interval using Stochastic Sequential Indication Simulation (SSIS) algorithm. Based on lithofacies, fluvial facies and biofacies analyses, a terrigenous and shallow fluvio-deltaic fill within a lowstand system tract was evident. Petrophysical properties including porosity, volume of shale and effective porosity were upscaled, guided by facies model and then Stochastic Gaussian Simulation (SGS) algorithm was used to produce the model. Porosity model predicted sand layers having maximum porosity of 27.5% which implied very good reservoir potential. However, the volume of shale model with values from 0.45 to 0.50 incorporates silt and clay and indicates marginal reservoir potential. The study identifies four potential reservoir intervals with thickness ranging from 9.1 to 38.5 m. The effective porosity in OVK-1 ranges from 0.10 to 0.30 and identified fluvial facies such as floodplain, channel sand, levee and crevasse splay sand. Facies model show a good sand distribution with minor shale localized in the western part of the Field. The central part of the model has good reservoir qualities, evident by low volume of shale values and high porosities. This study helps to identify a potential unexplored drillable prospect on OVK-1 sand body south-west of DN-2 well. Successful drilling of the identified prospect could increase the reserve of the Field.