Processing Seismic Data to Enhance Resolntion of Fault Structures-Some Case Studies

摘要

Seismic data are very useful in mapping shallow faulting and associated structures that are important in civil and engineering geology decisions. One of the primary goals is to improve the resolution of the processed data by increasing the signal-to-noise ratio. A new approach applies statistically-derived amplitude factors to enhance the events in imaged seismic sections. Furthermore, applying this method to imaging many profiles of data prior to stacking leads to more accurate pictures of subsurface structures. The statistical factors are most easily determined and applied after the data are Fourier transformed. The basic steps are the following: (1) Identify existing noise in the data. (2) Statistically estimate the noise level in the data. (3) Statistically estimate the signal level in the data. (4) Determine statistical amplitude factors by minimizing the least squares difference between the noise and signal levels found in steps (2) and (3). These factors will depend on the dip, frequency, and spatial coordinates associated with the events in the data. (5) Determine an enhanced data set as follows: Enhanced Data = (statistical amplitude factors)*(original data). This approach can be applied to prestacked or stacked seismic data. The new method will be illustrated with a number of case studies. Improvements in the continuity and resolution of interpreted events, particularly faults, will be demonstrated even when the quality of the original data is rather poor. This approach helps reduce misinterpretations of shallow geological features mapped with seismic data.