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GCRecognizing Faults in Previous HitSeismicNext Hit Previous HitDataNext Hit*

By

Alistair Brown1

Search and Discovery article #40073

*Adapted for online presentation from the Geophysical Corner column in AAPG Explorer June, 2001, entitled “Is It a Subtle Fault, or Just Noise?,” and prepared by the author. Appreciation is expressed to the author, to R. Randy Ray, Chairman of the AAPG Geophysical Integration Committee, and to Larry Nation, AAPG Communications Director, for their support of this online version.

 1Consulting reservoir geophysicist, Dallas, Texas. 

General Statement

Long gone are the days when faults appeared only as steps on vertical Previous HitseismicNext Hit sections. If we use today's better Previous HitdataNext Hit and exploit modern workstation tools available, we should do a much better job of recognizing and understanding faults in 3-D Previous HitseismicNext Hit Previous HitdataNext Hit. Faults cause breaks in continuity of Previous HitseismicNext Hit horizons. These discontinuities generate diffraction patterns and, before the days of Previous HitseismicNext Hit migration, diffraction patterns were what the Previous HitseismicNext Hit interpreter sought as an indication of faulting.

 

Migration in 2-D will collapse diffractions to some extent, whereas migration in 3-D should do much better. Major faults are still recognized on vertical sections and their throw estimated by offset in character correlation. For this, double-gradational color is the best mode of Previous HitdisplayNext Hit. Spatial patterns of faulting are revealed on time slices (or depth slices). These horizontal sections must be used in conjunction with vertical sections to establish sensible fault geometries.

 

Composite and chair displays are established ways of combining these orthogonal sections together. In a chair Previous HitdisplayNext Hit, one looks at a horizontal slice where it intersects a vertical section. You are able to see the map pattern of a fault along with its offset in a cross-section view. Various other kinds of volumetric Previous HitdisplayNext Hit also help to study and visualize faults.

 

Much of the science of fault detection concerns the recognition of subtle faults. On a normal vertical section a single-gradational color scheme, such as gradational gray (Figure 1), is usually best, as this type of Previous HitdisplayNext Hit enhances the terminations of low amplitude events. The detection of subtle faults, however, is highly dependent on good Previous HitdataNext Hit quality and high signal-to-noise ratio. Some extra care and attention in Previous HitdataNext Hit collection and processing is always beneficial.

 

uGeneral statementf

uFigure captions

uCoherence & fault recognition

uFinal statement

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uGeneral statementf

uFigure captions

uCoherence & fault recognition

uFinal statement

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uGeneral statementf

uFigure captions

uCoherence & fault recognition

uFinal statement

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure Captions

Figure 1. Single-gradational color improves the visibility of subtle faults on vertical sections. Black is at one extremity of the color bar and white the other.

Figure 2. Coherence (above) is here compared with normal amplitude (below) for a time slice through a salt dome.

 

Figures 3. Dip Previous HitdisplayNext Hit (3a) and residual (3b) for a horizon in the Cooper Basin of South Australia. The graben is about 100m across.

 

Figure 4. Edge Previous HitdisplayNext Hit showing two distinct styles of faulting in the Neuquen Basin of Argentina. 

 

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Coherence and Fault Recognition

 

Coherence is an invention of five years ago that has had a beneficial impact on fault recognition. The coherence transformation suppresses the continuity of Previous HitseismicNext Hit reflections and emphasizes discontinuities such as faults. Coherence Previous HitdataNext Hit are best viewed as time slices or as a whole coherence cube. In good quality Previous HitdataNext Hit, faults can be strikingly evident and spatial patterns of faulting can be clearly discerned.

 

Figure 2 is a time slice through a salt dome showing the common pattern of radial faults. The upper half of the time slice is in coherence and the lower half is the normal time slice Previous HitdisplayNext Hit in amplitude. Note how the faults are more clearly visible in coherence. Coherence is of less benefit in poor Previous HitdataNext Hit and can sometimes be quite ambiguous. Different algorithms from various vendors can give different results. Certain versions are designed to overcome particular Previous HitdataNext Hit problems such as high dip and poor signal-to-noise ratio.

 

Once the major faults have been recognized and the tectonic framework established, machine autotracking should be used to complete horizon surfaces. The autotracker follows the crest of an identified peak or trough with very high precision. The resultant time (or depth) values contain information on subtle faults -- but also noise. An important part of fault recognition is then scrutinizing these horizon surfaces in an attempt to distinguish geology from noise.

 

Time-derived horizon attributes are used for this purpose. Several of these are available on modern workstations and the most important are dip, azimuth, edge and residual. Figure 3a and Figure 3b show dip and residual for the same horizon. Dip is the magnitude of dip of the local surface dip vector. Residual is the difference between the horizon surface and its spatially-smoothed equivalent. We look at these attributes in map form and judge what appears geologic. In Figure 3, pairs of brown anomalies in Figure 3a correspond to blue anomalies in Figure 3b. The strength of the anomalies over background noise and the arcuate pattern support the interpretation of a graben.

 

The edge map of Figure 4 clearly distinguishes the short north-south faults from the long arcuate one. The arcuate fault is about seven kilometers long and looks impressive on the edge map -- however, it has negligible throw and is barely visible on any vertical Previous HitseismicNext Hit section. It was first recognized on this edge Previous HitdisplayNext Hit and appears to be caused by an igneous intrusion.

 

As shown, the use of time-derived attributes can be a primary method of fault recognition. We do not have to observe a clear break on a vertical section. However, the interpreter typically looks at an appropriately oriented vertical section and may see a minor interruption at the anomaly position. Commonly this was not recognized during the mainstream of the interpretation. 

Final Statement

 Distinguishing subtle faults from various kinds of noise is always a value judgment, so experience is useful. Interpreters tend to look at more than one type of time-derived attribute and seek the same feature on each as cross-validation. 

The two panels of Figure 3 show the graben on both the dip and residual displays; some of the minor wiggly features, probably noise, occur on only one. Three-dimensional Previous HitseismicNext Hit Previous HitdataNext Hit today typically contains an enormous amount of geologic detail. Faults are clearly an important part of this information. 

The modern interpreter must use all the interpretation tools available to find and understand the faults affecting the reservoir. With practice and experience, one can extract the subtle but valuable details inherent in the Previous HitdataTop.

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