Deriving global parameters for velocity-based pore pressure predictions in a complex overpressure origins regime is normally difficult and nonrobust. Applying large variations in Eaton’s exponent is an unsatisfactory work practice for velocity-based pore pressure prediction. This study investigates an alternative potential method to reduce the variation of Eaton’s exponent values in an environment of mixed disequilibrium compaction and fluid expansion overpressure mechanisms. Using 25 input wells, the fluid expansion components are estimated using velocity-vertical effective stress plot and then subtracted from the pressure measurements to obtain the disequilibrium compaction components. Eaton’s exponents are then derived only from the disequilibrium compaction components. The spatial variation of Eaton’s exponent is greatly reduced from the range of 1–5 to the range of 1–1.9 after removing the fluid expansion components from the raw overpressure data set. A constant Eaton’s exponent of 1.44 is used throughout the field to predict the disequilibrium compaction components and the fluid expansion components are predicted from gridding of the well data. The two components are combined to produce a final pore pressure prediction profile, which yields less uncertainty than the traditional Bowers method.
This paper focuses on the application of pre-stack seismic inversion to delineate gas reservoirs for development well targeting of the Muda Field in the Malay Basin. A comprehensive development well targeting workflow was established to integrate information from all related disciplines and convert them into an optimized well design. One of the key tasks in this workflow was to select an appropriate seismic attribute to identify the distribution of reservoir sands in this area. These reservoirs are generally characterized by thin sands inter-bedded with coals. Relative Poisson's Ratio (RPR) was used to identify reservoir targets prior to development drilling. Drilling results later indicated that a high proportion of the proposed anomalies (87%) correspond to gas sands. The remaining (13%) are related to highly saturated sands, Additional Zones of Interest (AZIs) or shale. Preliminary results therefore demonstrate that the RPR attribute can be used as an effective tool in development well targeting.
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