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The AAPG/Datapages Combined Publications Database
AAPG Bulletin, V.
Acoustic nonlinear full-waveform inversion on an outcrop-based detailed geological and petrophysical model (Book Cliffs, Utah) Daria Tetyukhina,1 Stefan M. Luthi,2 Dries Gisolf3
1Department of Geoscience and Engineering, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, Netherlands; present address: Shell Global Solutions International B.V., Rijswijk, Netherlands; [email protected]
2Department of Geoscience and Engineering, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, Netherlands; [email protected]
3Department of Physics, Delft University of Technology, Lorentzweg 1, 2628 CJ, Delft, Netherlands; [email protected]
Analog outcrops are commonly used to develop predictive reservoir models and provide quantitative parameters that describe the architecture and facies distribution of sedimentary deposits at a subseismic scale, all of which aids exploration and production strategies. The focus of this study is to create a detailed geological model that contains realistic reservoir parameters and to apply nonlinear acoustic full-waveform prestack seismic inversion to this model to investigate whether this information can be recovered and to examine which geological features can be resolved by this process.
Outcrop data from the fluviodeltaic sequence of the Book Cliffs (Utah) are used for the geological and petrophysical two-dimensional model. Eight depositional environments are populated with average petrophysical reservoir properties adopted from a North Sea field. These units are termed lithotypes here. Synthetic acoustic prestack seismic data are then generated with the help of an algorithm that includes all internal multiples and transmission effects. A nonlinear acoustic full-waveform inversion is then applied to the synthetic data, and two media parameters, compressibility (inversely related to the square of the compressional wave velocity vP) and bulk density, ρ, are recovered at a resolution higher than the shortest wavelength in the data. This is possible because the inversion exploits the nonlinear nature of the relationship between the recorded data and the medium contrast properties. In conventional linear inversion, these details remain masked by the noise caused by the nonlinear effects in the data. Random noise added to the data is rejected by the nonlinear inversion, contributing to improved spatial resolution. The results show that the eight lithotypes can be successfully recovered at a subseismic scale and with a low degree of processing artifacts. This technique can provide a useful basis for more accurate reservoir modeling and field development planning, allowing targeting of smaller reservoir units such as distributary channels and lower shoreface sands.
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