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Abstract Low contrast pay (LCP) reservoirs indicate low contrast between oil, shale and or water. The most common types of LCP include low resistivity oil (LRO) and high resistivity water (HRW). LCP are frequently accounted in delta front setting during the offshore hydrocarbon exploration of south China sea. The X20 oilfield is developed in a fault anticline structure with Paleogene delta front setting, which include channels, mouth bars, and distal sand bars and levee banks in Pearl River Mouth Basin offshore South China. Reservoir of levee bank sedimentary facies with high irreducible water saturation and high clay content leads to low contrast between low resistivity pay and dry zones. Overlook of LCP reservoir endues high risk in the reserves and production underestimation. Most low resistivity oil are related with very fine grain silty sandstone, siltstone or shaly siltstone, which have lower contrast with shale in the gamma and resistivity response. To improve the accurate identification of low resistivity oil, the integrated logging suites of NMR, borehole image log, core data and advanced mud gas analysis were deployed separately. The 2D NMR map Diffusivity vs T2 intrinsic spectrum together with grain size and resistivity were integrated for low contrast pay identification. Where oil signal is seen in low resistivity zone with dominant grain size below 50um can be identified as low contrast pay. Continuous grain size was obtained by NMR and calibrated to core, which is compared to mud log and conventional log. High resistivity water was identified by advanced mud gas analysis when no NMR log acquired. Water saturation index was calculated by advanced mud gas analysis via advanced processing of surface logging gases and fluid analysis, of which minimum data utilized are hydrocarbon gases from methane through pentane, total gas, gamma ray, hole size and rate of penetration (ROP). Sandstone beddings and shale beddings were picked from LWD borehole image logs and applied in different sedimentary facies, which help better understand the LCP reservoir distribution in regional scale. Finally, formation sample data and 2D NMR analysis are used to validate the entire analysis and the joint LCP identification model is established. The result show that water saturation index calculated by advanced mud gas analysis show higher contrast than Archie's water saturation, especially in dry zone and low resistivity pay zone. Two obvious changing steps are observed in grain size curve and water saturation index between dry zone, low resistivity pay zone and normal oil zone. Sedimentary facies are linked with LCP reservoirs in this study, and low resistivity pay reservoir is attributed to levee bank composed of shaly siltstone and silty fine sandstone with higher clay content, while high resistivity pay reservoir is attributed to distributary channel and mouth bar composed of medium sandstone with less clay content. Sandstone beddings picked from LWD density image were utilized for sedimentary facies analysis in two development wells, the result of which further confirmed the difference between low contrast pay and normal oil. The newly established LCP identification model aids more low resistivity pays discovery in offset development wells in timely manner with LWD NMR and LWD imaging. The joint identification of LCP reservoirs is proved to be more efficient and accurate, which is generalizable at more field's exploration and development stage.