Low-resistivity pay (LRP) has been a challenging problem in formation evaluation for many years. This is because conventional petrophysical interpretations are unable to identify pay intervals in low-resistivity reservoirs. This paper lays out a robust workflow for identifying LRP in thinly laminated sands with silty and/or shaly layers. The workflow is essentially a two-step process which integrates data from gas while drilling (GWD), conventional logs and nuclear magnetic resonance (NMR) logs which identify potential pay intervals for further examination using wireline formation tester (WFT). This approach allows one not only to identify pay intervals but also their phase and their flow characteristics without the need of a conventional drill-stem-test (DST). It is common for LRP to have high water saturation (60-70%) computed by conventional petrophysical interpretation while producing sustained water-free oil for few years. A petrophysical study was undertaken to integrate core data analyses including conventional, NMR and mercury injection capillary pressure (MICP). Data from over 100 sidewall cores (SWC) were examined. This novel approach for estimating irreducible water saturation (Swi) was developed based on 1. A good relationship was recognized between Swi from capillary pressure data as compared to that estimated from NMR de-saturated core. 2. A correlation was established between Swi of de-saturated core and T2, LM . 3. A validation was performed for zones producing water-free oil to link between NMR-MICP core analysis and NMR logs, using the following two methods for estimating Swi from a. capillary pressure data that is computed with knowledge of the height above free water level (FWL), b. T2, LM of NMR logs using the correlation developed in Step 2. The benefits of this methodology are that it improves decision in well completion, predicts well performance accurately and reduces uncertainty in reserve estimation. In addition, it allows the user not only to identify zones of pay that would have been missed using conventional analysis, but also to estimate FWL elevations with higher accuracy from a saturation height model (SHM). Saturation profiles derived by this approach and those ones modeled from saturation height equations based on MICP capillary pressure data can be fitted better due to substantial reduction in uncertainties of log derived saturation data. Consequently the initialization of in-place volumes for hydrocarbons will be enhanced.
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