Leveraging IoT (Internet of Things) for Reservoir Evaluation in the Oil and Gas Industry

College of Engineering, Department of Petroleum Engineering, Knowledge University 44001 Erbil, Iraq

^* Sivar Qays Ali: Siver.kais@knu.edu.iq

Abstract

Using IoT (Internet of Things) in reservoir evaluation can significantly enhance the efficiency and accuracy of data collection, monitoring, and analysis in the oil and gas industry. Determining the shale volume distribution is one of the most crucial factors to take into account when evaluating the formation, Since the presence of shale lowers the reservoir’s effective porosity and permeability. The volume and distribution of shale and the effective porosity of the formation are estimated utilizing wireline well log data along with Techlog software. The Lower Jurrasic formations are composed of four formations (starting from top to bottom) which are Alan, Mus, Adaiyah and Butmah. In this study, the only studied reservoir formations are Alan, Mus and Adaiyah as provided in the dataset. Shale volume has been calculated by using the gamma ray, the combinations of Neutron-Density and Neutron-Sonic logs were utilized in order to calculate the effective porosities. According to the results, it was concluded that the top of Mus and Adaiyah formations can provide the best reservoir quality and results in comparison with other formations and zones due to the low shale volume and higher effective porosity.