Fluvio-deltaic sedimentary systems are of great interest for explorationists because they can form prolific hydrocarbon plays. However, they are also among the most complex and heterogeneous ones encountered in the subsurface, and potential reservoir units are often close to or below seismic resolution. For seismic inversion, it is therefore important to integrate the seismic data with higher resolution constraints obtained from well logs, whereby not only the acoustic properties are used but also the detailed layering characteristics. We have applied two inversion approaches for poststack, time-migrated seismic data to a clinoform sequence in the North Sea. Both methods are recursive trace-based techniques that use well data as a priori constraints but differ in the way they incorporate structural information. One method uses a discrete layer model from the well that is propagated laterally along the clinoform layers, which are modeled as sigmoids. The second method uses a constant sampling rate from the well data and uses horizontal and vertical regularization parameters for lateral propagation. The first method has a low level of parameterization embedded in a geologic framework and is computationally fast. The second method has a much higher degree of parameterization but is flexible enough to detect deviations in the geologic settings of the reservoir; however, there is no explicit geologic significance and the method is computationally much less efficient. Forward seismic modeling of the two inversion results indicates a good match of both methods with the actual seismic data.

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 twodimensional 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 v P ) and bulk density, r, 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 A U T H O R SStefan Luthi is a professor in production geology and the head of the applied geology section at Delft University of Technology. He is also a senior technical advisor to Schlumberger Limited. Luthi holds a Ph.D. from the Swiss Federal Institute of Technology (ETH) in Zurich. During his career, he has worked on five continents and has published more than 50 articles in scientific journals. 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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Many important details of potential subsurface reservoirs that we wish to characterize are only indirectly present in the reflected wavefields measured at the Earth's surface. Therefore, the analysis of seismic data always presents an inversion problem. Instead of analyzing the data trace by trace, we propose an automated procedure that adjusts the parameters of a two-dimensional geological model by minimizing the mismatch between the simulated and measured seismic. This approach differs from standard inversion problems in that the size of the required details of the 2D geological reservoir model is far below the limits of the seismic resolution.