Identifying Deep Sweetspots: Seismically Constrained Reservoir Quality Prediction Offshore Brunei

Gelinsky, Stephan (Shell International E&P) | Kho, Sze-Fong (Shell International E&P) | Espejo, Irene (Shell International E&P) | Keym, Matthias (Shell Malaysia) | Näth, Jochen (BSP) | Lehner, Beni (BSP) | Setiana, Agus (BSP) | Esquito, Bench (SDB) | Jäger, Günther (SDB)



Prospects below or near shallower producing fields can be economically attractive yet also risky since reservoir presence may be uncertain, reservoir quality can be poor, and high overpressure and temperature can make drilling and logging deeper prospects difficult. Systematic integration of relevant subsurface data from thin section to basin scale allows to seismically identify reservoir presence, and to predict reservoir quality for applicable rock types via burial histories. On an intermediate well log to seismic scale, a predictive rock physics modeling approach links reservoir and seal rock properties to seismic amplitude data to polarize the prospect's geologic ‘probability of success'. Particular challenges in the offshore Brunei study were very fine-grained deposits and non-vertical tectonic stresses associated with compressional settings. Both make porosity predictions that leverage complex burial histories rather than relying on extrapolated depth trends quite challenging - yet the integrated approach remains the best option to identify deep reservoir quality sweetspots that a favorable stress and temperature history may have preserved for certain reservoir rock types in certain locations.

The prolific petroleum system offshore Brunei features two major sediment fairways, the Baram and Champion river systems, and a variety of depositional environments, ranging from high NtG topsets inboard over shallow marine slope settings to deepwater turbidites outboard (Gartrell et al., 2011). Across Brunei Darussalam, the systematic ‘Earth-Model’ study, jointly undertaken by BSP and SDB, defined gross depositional environments (GDE maps) and calibrated a 3D basin model. The study leveraged newly reprocessed Broadband seismic data that over large areas had improved imaging of the subsurface. Complementing this regional geologic evaluation with the goal to assess deep reservoir quality, in the here presented study multiple reservoir and bounding mudrock facies were identified and their composition and texture determined from thin sections. Present day porosity and cement volumes were then calibrated and blind tested with burial histories from the basin model. The reservoir quality calibrations will be applied to predict expected present-day prospect reservoir quality. In parallel, sand and shale acoustic properties were calibrated for applicable rock types to allow for quantitative seismic interpretation of reservoir-seal reflectors and to establish the regional ‘amplitude floor'.