3D geo-cellular static virtual outcrop model and its implications for reservoir petro-physical characteristics and heterogeneities
Muhammad Usman, Numair Ahmed Siddiqui, Shiqi Zhang, Manoj Mathew, Yaxuan Zhang, Muhammad Jamil, Xueliang Liu, Nisar Ahmed
Abstract
Geostatistical data plays a vibrant role for surface-based reservoir modeling through outcrop analogues, which is used to understand three-dimensional (3D) variability of petrophysical properties. The main purpose of this study is to improvise the surface-based 3D geo-modeling to demonstrate petrophysical characteristics and heterogeneities of Sandakan reservoirs, NW Borneo. We used point cloud data from Light Detection and Ranging (LiDAR) to build high-resolution virtual outcrop modeling (VOM) onto which we mapped 6 different lithofacies. Porosity and permeability of core plugs were measured to determine the average variance of petrophysical properties for each lithofacies. By utilizing the integration of VOMs analogues and petrophysical properties in Petrel™, we demonstrated the distribution and associations of all lithofacies in pseudo wells that have inherent thin beds heterogeneities in 3D geo-cellular model. The results concluded that the heterogeneity of thin beds in lithofacies is dependent on porosity and permeability with input dataset. According to the final model, cross-bedding sandstone (CBS), hummocky cross-stratified sandstone (HCSS) and trough cross-bedding sandstone (TCBS) show good reservoir quality due to high porosity ranging from: 25.6% to 20.4% and, 19.3%–14.5%, and permeability ranging from: 74.03 mD to 66.84 mD and, 64.86 mD to 21.01 mD. In contrast, massive to weak laminae sandstone (MWLS) and bioturbated sandstone (BS) show fair to poor reservoir quality, caused baffling of surrounding mud sediments in the reservoir lithofacies. Results also revealed that LiDAR based VOM with petrophysical properties can significantly reduce the risk and minimize the cost of reservoir modeling in petroleum industry.