NSISONG ISUK

Reservoir heterogeneity, characterized by spatial variation in rock properties such as porosity and permeability, is a defining feature of petroleum reservoirs that influences fluid flow behavior and hydrocarbon recovery. Traditional methods to quantify heterogeneity rely mainly on static petrophysical measurements and indices such as the Dykstra-Parsons coefficient, which provide numerical expressions of permeability variation but often lack dynamic insights into fluid connectivity and migration pathways. Recent advances have demonstrated the value of integrating geochemical techniques, notably Strontium Residual Salt Analysis (Sr-RSA), with permeability data to reveal subtle compartmentalization, fluid discontinuities, and internal flow barriers that directly impact sweep efficiency during secondary and tertiary recovery processes. This integrated approach facilitates a multidimensional characterization of reservoir architecture, enabling better prediction of fluid displacement patterns and optimization of injection and production strategies. Such insights are critical for improving hydrocarbon recovery efficiency and maximizing asset value. This study assesses the extent and impact of reservoir heterogeneity on sweep efficiency, employing both traditional petrophysical metrics and advanced geochemical fingerprinting to provide a comprehensive understanding of reservoir behavior. The findings aim to support enhanced reservoir characterization and guide strategic decisions in field development and enhanced oil recovery operations.

This project investigates the effect of key drilling parameters on Rate of Penetration (ROP) using real-world field data from a selected well. The parameters analyzed include Weight on Bit (WOB), Rotational Speed (RPM), and mud properties such as Plastic Viscosity, Yield Point, and Gel Strength. The study aims to understand how variations in these parameters influence ROP and to identify combinations that could
enhance drilling efficiency. Microsoft Excel was used for organizing, calculating, and analyzing the data, with additional tools such as Solver applied for basic optimization. By focusing on a practical, data-driven approach, this work contributes to ongoing efforts in optimizing drilling operations, especially in regions where advanced software and models may be inaccessible. The findings provide insight into the practical relationships between operational parameters and ROP, and highlight opportunities for performance improvement in similar field environments