Extrapolation of Reservoir Properties From Wells Using Depositional Environment Information From 3-D Seismic Data

Abstract

Data from wells and 3D seismic surveys are complementary sources for geological information to derive formation properties across reservoirs. Well logs provide direct information about reservoir properties in depth at a resolution down to a few inches. Due to the measurement along the well bore, however, well log information from individual wells is limited locally. Using data from several wells, lateral variations of depositional environments can be derived down to 3rd order depositional cycles. 3D seismic data provide an almost continuous 3D data set that can interpreted into continuous depositional environments. However, seismic data record acoustic impedance contrasts in time, which requires conversion to depth and calibration to reservoir properties. Furthermore, the minimum wavelength of the seismic wavelet limits the vertical resolution of seismic data, which corresponds to 1st order depositional cycles. This limitation means that the resolution of seismic data is restricted to individual depositional cycles. When calibrated with well data, interpreted seismic data are not only calibrated to selected reservoir properties but the vertical resolution in reservoir modelling can be improved since we can derive better seismic trends, which in turn enables the mapping of depositional environments down to 2nd order depositional cycles. Using this approach reservoir properties can be extrapolated away from the well locations in a sedimentologically correct fashion. The approach is demonstrated in clastic shelf and slope reservoirs of Upper Paleocene age. Specifically, the Forties Sandstone turbidite channel complex in the Sele Formation in the UK North Sea, where a number of wells are used to calibrate RGB blended 3D seismic data to delineate depositional features and lithofacies.

AAPG Datapages/Search and Discovery Article #90291 ©2017 AAPG Annual Convention and Exhibition, Houston, Texas, April 2-5, 2017