Introduction

 

fltcont
Figure 1 Top: A synthetic seismic section with a fault. Bottom: an idealized fault contour map showing slip distributions along the fault surface.

A lot of useful information can be gained by understanding the slip distribution along a fault surface. Factors governing the slip distribution include the stress field, proximity to other faults, rock strength, tectonic history, and loading rates. If the slip distribution were easily and quickly obtained, it could be added to interpretation and processing workflows ().

A present, seismic fault contours are generated by tediously interpreting many horizons and calculating the slip as shifts between those horizons. As a result, only the interpreted data is used in calculating slips, and the process is very labor intensive and time consuming. In poor data quality areas, this method may be all that works. However, in areas where seismic image quality allows, automatic data-based methods would save time and, in some cases, increase the accuracy of the result.

In this paper, I describe a robust method for calculating the fault slip distributions from seismic data in order to bring the power of fault contours to bear on a number of problems. Figure  shows a synthetic 2D seismic section with an interpretted fault and a cartoon of fault contours. I create a cross-correlagram by placing windowed cross-correlations side-by-side. Then a non-linear line fitting program is used to fit a smooth line to the cross-correlagram. he lag values of this line remove most of the deformation of the fault in a model example.