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Deconvolution negates these effects to an extent and thus increases the resolution of the seismic data. Seismic data, or a seismogram, may be considered as a convolution of the source wavelet, the reflectivity and noise. [5] Its deconvolution is usually implemented as a convolution with an inverse filter.
The primary method for creating a receiver function is based on analyzing the product of waves that pass from the mantle through the Moho boundary. The large compositional differences between the crust and the mantle cause large differences in seismic waves as they pass through the discontinuity. [ 5 ]
Deconvolution maps to division in the Fourier co-domain. This allows deconvolution to be easily applied with experimental data that are subject to a Fourier transform. An example is NMR spectroscopy where the data are recorded in the time domain, but analyzed in the frequency domain. Division of the time-domain data by an exponential function ...
For land acquisition, different types of sources may be used depending on the acquisition settings. Explosive sources such as dynamite are the preferred seismic sources in rough terrains, in areas with high topographic variability or in environmentally sensitive areas e.g. marshes, farming fields, mountainous regions etc. [4] Such type of sources needs to be buried (coupled) into the ground in ...
Semblance analysis is a process used in the refinement and study of seismic data. The use of this technique along with other methods makes it possible to greatly increase the resolution of the data despite the presence of background noise. The new data received following the semblance analysis is usually easier to interpret when trying to ...
The seismic data is then carefully processed to preserve seismic amplitudes and accurately determine the spatial coordinates of each sample. This allows a geophysicist to construct a group of traces with a range of offsets that all sample the same subsurface location in order to perform AVO analysis.
A form of migration is one of the standard data processing techniques for reflection-based geophysical methods (seismic reflection and ground-penetrating radar) The need for migration has been understood since the beginnings of seismic exploration and the very first seismic reflection data from 1921 were migrated. [5]
Seismic, well logs and other input data are each represented as a probability density function (PDF), which provides a geostatistical description based on histograms and variograms. Together these define the chances of a particular value at a particular location, and the expected geological scale and composition throughout the modeled area.