<![CDATA[Low resistivity pay zones (LRPZ) are not the primary targets in most development fields. The challenge is to identify it and define its reservoir petrophysical properties besides the classic analysis of the genetics of the LRPZ. It is important to note that most LRPZ is caused by reasons directly linked to the petrophysical parameters as main constraints on defining the reservoir (petrophysical) properties. It has consequences that the petrophysical parameters for LRPZ should be defined separately from picking the parameters for normal high resistivity on the other part of the wells. This paper proposed simple methods to predict the LRPZ using the primary well logs data. It also shares some decisions made in South Sumatra, and Sanga Sanga Block results in a pretty successful story relatedly. The first method is a simple petrophysical analysis using primary wireline log data which is done by applying a particular cutoff that has been exercised on some wells in the basin-wise well test data to get field references in the same basin/subbasin (in this case is South Sumatra Basin). The second method is identifying and analyzing LRPZ using well-known MRGC (Multi-Resolution Graph-Based Clustering), commonly used on electro facies and rock type analysis and has never been used to define LRPZ. This study proved that these two methods performed well as LR pay zone prediction and significantly added new pay zones to increase the chance of getting additional reserves and production. Keywords: Low Resistivity Pay Zone, petrophysics analysis, Multi-Resolution Graph-Based Clustering (MRGC), South Sumatra Basin, Sanga Sanga Block]]>
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