Fault attribute

Quality control. Gives the purchaser the right to conduct checks on the quality of the services being delivered. The cost is usually assigned to the purchaser unless errors or faults attributable to the provider are uncovered. 

The set test assume command can be used to get an estimate of fault coverage. This allows the user to perform analysis of the improvements in fault coverage by initializing the RAM to different states. TC does not verify these values and the user must ensure that the RAM is initialized to that state. In addition, for each of the above approaches, a test dont fault attribute should be placed on the RAM cell. This prevents the inclusion of faults associated with the RAM cell in the fault coverage calculation. 

We would also like to point the attention towards the chapter [10] of Pedersen, Skov, Randen, and Spnneland, presenting a very attractive further processing step beyond the fault attributes for extracting the faults as surfaces in 3D. 

Fig. 19. Gaussian dip-guided layer-parallel smoothing result (b). Observe how the continuity of the seismic signal has been enhanced. Fault attribute cubes corresponding to the data in (a) and (b) can be seen in figures (c) and (d), respectively. The improved fault mapping is clearly observed.

Main Uses Increasing fault attribute continuity. 

Fig. 20. Gaussian dip-guided layer-orthogonal smoothing result. The seismic image (left) is used for computing the dip and azimuth, and then the projected principal gradient fault attribute (Subsection 5.2) (middle) is smoothed along short layer-orthogonal traces by a Gaussian filter to yield the result to the right.

Fig. 1. A fault attribute is generated from seismic data. The ant tracking algorithm extracts surfaces from the attribute, and the human interpreter works with them in the structural editing tool. The surfaces are then exported as interpreted surfaces or written to a cube to produce an enhanced fault attribute.

Extraction of surfaces from fault attributes is nontrivial due to the noisy nature of these attributes. The surfaces usually appear more like trends than well-defined, continuous surfaces. In the fault extraction step, only features that are continuous and likely to be faults are extracted. This is achieved by using the principles of swarm intelligence. 

Figure 3 and Figure 4 show some results from applying ant tracking to fault attributes. Note how noisy responses from chaotic layers in the attributes have been removed and how the fault surfaces have been made sharper and more continuous. 

Fig. 3. (a) Time slice of a fault attribute (variance) with (b) corresponding ant tracking results. 

In order to obtain a consistent fault interpretation, human interaction is required. This interaction is provided through a fault analysis tool. The most important role of this tool is to provide the interpreter with functionality to validate the extracted surfaces. Since the fault attributes do not only enhance events due to faulting, surfaces that are not faults will be extracted and have to be deleted. Second, the analysis tool must provide the interpreter with... 

Fig. 5. The fault surfaces can be displayed as 2D lines on seismic or attributes, or as 3D patches by double clicking on the 2D lines. A seismic section and a fault attribute slice from the main field example are displayed together with the fault surfaces.

Fig. 9. Edited faults from the rotated fault block displayed with a seismic inline and a fault-attribute time shce (left). Pole plot of the edited internal faults in the rotated fault block (right).

Kinematic Texture Attributes. The geometrical tensor is used as an input to other processes, in particular kinematic texture attributes and some discontinuity and fault attributes. 

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