Publications

This paper addresses the challenge of declining oil and gas production in Indonesia's sedimentary basins by focusing on optimizing the potential of Low Resistivity Pay (LRP), an area with hydrocarbon potential where traditional characterization methods may fall short. Through over 20 case studies, the paper emphasizes best practices for LRP characterization, employing petrophysical and petrographic analyses as preferred methodologies to complement traditional well-log data. The studies involve estimating the presence of clay and conductive minerals responsible for low resistivity readings, utilizing techniques such as XRD or SEM analysis. The reassessment of water saturation (Sw) is crucial, often revealing significant changes that require a re-evaluation of productive interval selection. Sophisticated logging tools such as image log, triaxial resistivity, nuclear magnetic resonance, pulsed neutron, carbon-oxygen logs, and production logging are suggested for more effective LRP characterization and could be integrated with available data. Geophysical data sources, including seismic inversions and Artificial Intelligence technologies, aid in identifying these zones accurately. The paper explores novel LRP characterization and development technology methods, such as weighting and MAINE methods, unique to specific fields. By collecting data from various case studies, the paper conducts identification to determine effective LRP presence using MoSCoW Prioritization Classification. This classification approach integrates cutting-edge technologies and adaptive exploration strategies to navigate the complexities associated with LRP. The study aims to assist researchers and professionals in developing targeted strategies to optimize exploration efforts specifically in LRP, contributing to Indonesia's efforts to increase oil and gas production while addressing the challenge of declining rates in the industry.