The industrial revolution 4.0 has required collaboration on the oil and gas industry sector. One of the problems is the technology transfer and the increasing of oil reserves supply. It needed to productivity analysis for reservoir rock characterization and subsurface profile that will determine technology transfer. This study was aimed to obtain the hydrocarbon reservoirs quality based on petrophysical parameters. The reservoir zone of JEONA_35 well in 1527.77 - 2067.21 ft. From NPHI and RHOB logs, there is a cross over in 1990-2020 ft that interpreted as oil fluid. The PHIE is 30 %, Sw is 20 % and Vclay is 10 %. Electrofacies analysis shows that the reservoir zone was located in Bekasap and Menggala Formations (1527.77 - 1889.25 ft). In Bekasap Formation, the gamma ray log pattern is a cylinder block shape and thick from the top until base formation, it deposited in the channel fill distribution with thin sandstones lithology. In Menggala Formation, gamma ray log pattern shows the uptrend bell shape that was deposited in the fluvial - delta distribution with thick sandstone. So, it can be concluded that JEONA_35 reservoir has a good quality with the water saturation is low relatively, so the oil saturation is high relatively.

Reservoir’s quality is very important in exploration of oil and gas. This quality can be used to determine the productive field including the reserve itself. To analyse the reservoir quality, net pay thickness needs to be determined. However, different quality of logging tools will affect the log reading and thickness interval. Therefore, it needs to be normalized in order to equalize the reading of minimum and maximum log values in interest zone. This study is intended to interpret the impact of gamma ray normalization on net calculation. The net pay calculation is carried out with and without normalization. To do normalization, cumulative percentile used are 3% and 93%. For instance, before normalization, the highest net pay in PE_35 is 12ft. After P93 and P3 normalization, the highest net pay value become 13.5ft and 51.5ft respectively. If the net pay value of PE_35 using P3 normalization is compared to the net pay value before normalized, then the normalized value is optimized more than 5%, which is a good amount of optimization. Thus, to obtain an optimistic net pay value, normalization must be done. To conclude this study, 3% cumulative percentile normalization method has shown the most optimistic net pay value increase.