Abstract: A method for determining from measured reflection data on a plurality of trace positions, a plurality of subsurface parameters. The method includes the steps of: preprocessing the measured reflection data into a plurality of partial or full stacks; specifying one or more initial subsurface parameters defining an initial subsurface model; specifying a wavelet or wavelet field for each of the partial or full stacks of the measured reflection data; calculating synthetic reflection data based on the specified wavelets and the initial subsurface parameters; optimizing an objective function, including the weighted difference between measured reflection data and synthetic reflection data for a plurality of trace positions simultaneously; and outputting the optimized subsurface parameters. A device for implementing this method is also included.

Abstract: A method for determining from measured reflection data on a plurality of trace positions, a plurality of subsurface parameters. The method includes the steps of: preprocessing the measured reflection data into a plurality of partial or full stacks; specifying one or more initial subsurface parameters defining an initial subsurface model; specifying a wavelet or wavelet field for each of the partial or full stacks of the measured reflection data; calculating synthetic reflection data based on the specified wavelets and the initial subsurface parameters; optimizing an objective function, including the weighted difference between measured reflection data and synthetic reflection data for a plurality of trace positions simultaneously; and outputting the optimized subsurface parameters. A device for implementing this method is also included.

Abstract: A method for determining from measured reflection data on a plurality of trace positions, a plurality of subsurface parameters. The method includes the steps of: preprocessing the measured reflection data into a plurality of partial or full stacks; specifying one or more initial subsurface parameters defining an initial subsurface model; specifying a wavelet or wavelet field for each of the partial or full stacks of the measured reflection data; calculating synthetic reflection data based on the specified wavelets and the initial subsurface parameters; optimizing an objective function, including the weighted difference between measured reflection data and synthetic reflection data for a plurality of trace positions simultaneously; and outputting the optimized subsurface parameters. A device for implementing this method is also included.

Abstract: A method for classification of a subsurface includes the steps of: inputting at least two seismic drive layer property data sets; inputting data defining one or more zones of interest in the classification input data sets; inputting analysis data sets with data types corresponding to that of the classification input data sets; inputting data defining a subset of interest in the analysis data sets; defining in the subset of interest within the data type space one or more data type subspaces that characterize subsurface features; selecting at least one data type subspace to be used for classification; determining which data points in the zone of interest fall within the selected data type subspaces; and typifying these data points to so classify these data points of the classification input data.

Abstract: A method for reducing noise and for deriving new data from seismic and seismic derived rock property data includes determining a rate of change and direction of rate of change of amplitudes of seismic and seismic derived rock property cubes along microlayer horizons and filtering this data long the microlayer horizons. To facilitate this determination, microlayer horizons can be locally rotated around each microlayer horizon definition point. The data determined for the microlayer horizons are sequentially organized in time whereupon a display of the microlayer horizons can be sequentially stepped through to view the output data of each microlayer horizon.

Abstract: Disclosed is a method to estimate elastic and compositional parameters by the inversion of multiple seismic and echo-acoustic data full or partial stacks. The method utilizes the information in the amplitudes of the input seismic data sets and differences between the amplitudes in the different input data sets. The method further makes use of the contrast of the reflectivity and/or the elastic and compositional parameters and may make use of a background trend model, relationships between the parameters, control on the lateral rate of change of the parameters and constraints on the parameters or functions of parameters to enhance the results. Additionally, corrections may be made for differential time shifts between the input data sets. The method can be applied to seismic data acquired to analyze the subsurface and to echo-acoustical data acquired for medical and material analysis purposes.