In an oil producing S-field within Malay basin, the existence of heterolithic and thinly laminated reservoirs are common. Standard resolution logging tools are incapable to separate inter-bedded sand-shale layers due to their low vertical resolutions and the conventional petrophysical workflow was not robust enough in capturing the actual properties of the laminated sand shale (LSS) reservoirs in S-field. As a result, the estimated permeability did not match the core permeability and required a significantly high multipliers in the dynamic model and the calculated saturation failed to match the Dean-Stark saturation. This paper explains the limitation of the conventional analysis in LSS reservoir and highlights the use of PETRONAS Thin Bed Analysis (TBA) module to estimate the actual reservoir properties in S-field.
The case study in this paper shows the best practice to construct the robust fieldwide evaluation of reservoir properties, integrating core to production data and advance logs information, to determine reservoir properties. In LSS reservoirs, the conventional petrophysics outputs are often pessimistic compared to core data. Reservoir Enhancement Modeling and Reservoir Fraction Modeling (REM-RFM) is an in-house PETRONAS TBA methodology for evaluating LSS reservoirs. REM-RFM workflow is designed to obtain the net sand fraction and the actual reservoir properties to describe the reservoirs storage and flow capacity. Sand-shale lamination was quantified by digital core analysis, core UV light binning against the borehole image logs. The triaxial resistivity logs were used as inputs for the Thomas-Stieber method to determine the net sand fraction and the hydrocarbon saturation. Nuclear Magnetic Resonance (NMR) data was also incorporated to confirm the hydrocarbon pore volume on well level.
The REM-RFM workflow resulted in the improved reservoir properties compared to the conventional evaluation and were better matched to the core. In the laminated sands, the enhanced shale volume was comparable to the sand streaks seen in UV fluorescence core photo and image logs data, as well the enhanced porosity and permeability were matching well with the core data. Moreover, the water saturation was matching to the saturation from dean-stark core analysis result, comparable to saturation height function model and NMR data, and REM-RFM output were comparable to Thomas-Stieber results. Once the REM-RFM was calibrated in the key wells, the parameters were then applied to the whole field.
The in-house REM-RFM module discussed in this paper is an excellent addition to other industry methodologies. This module is basically a continuation of the innovative effort to characterize the conventional clastic reservoirs model performed earlier. It has been proven by applying robust evaluation, the conventional outputs are significantly improved that led to the optimizes the obvious volume of hydrocarbon estimated. In addition to that, the results can be used for reducing the risks in monetizing the opportunities from the heterolithics and laminated sands.