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 (
Saha, Sourav (Shell International Exploration and Production Inc) | Espejo, Irene (Shell International Exploration and Production Inc) | Gelinsky, Stephan (Shell International Exploration and Production Inc) | Keym, Matthias (Shell Global Solutions Malaysia Sdn. Bhd.) | Naeth, Jochen (Brunei Shell Petroleum) | Jäger, Günter (Shell Deepwater Borneo)
Prospects near existing infrastructure can be economically attractive; however, reservoir quality prediction is crucial to de-risk opportunities further from infrastructure including deeper, high pressure and high temperature (HPHT) opportunities. Understanding shallow reservoir properties is important and needs to be translated to predict the deeper reservoir quality where compaction and cementation often have a negative impact on reservoir quality.
The Baram and the Champion river systems deposited sediments offshore Brunei in various depositional environments, with multiple pairs of sandstone-siltstone reservoirs and bounding mudrock facies. The observed variation in the composition of reservoirs is an indication of a slight difference in provenance between the two river systems; however, the different is texture is an indication of length of sediment transport.
Qualitative and quantitative petrographic information was collected from a large number of thin sections from eight representative wells. Based on the overall sedimentary structures and textures observed in thin section, four (4) sandstone and three (3) siltstone petrofacies were described. Detailed point-count (300 counts per thin section) data was collected from these sandstones and siltstones for compaction and diagenetic modelling. Present day intergranular volume (IGV), macroporosity and cement types were quantified from thin sections. These parameters were subsequently calibrated for forward-modelling, using burial histories at each well location. The model was then blind-tested in order to verify the expected present day prospect porosity and permeability ranges. The resulting model was correlated with petrophysical well log data, to allow connecting rock properties to prospect seismic responses.
For the first time, a comprehensive offshore Brunei sedimentary petrology database was assembled covering major depositional environments from both dominant river systems. This database was compiled in a reservoir quality modelling software, which will allow for burial history-based reservoir quality predictions, both regionally and at prospect locations.