Moving faults while unfaulting 3D seismic images

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. IM25-IM33 ◽  
Author(s):  
Xinming Wu ◽  
Simon Luo ◽  
Dave Hale

Unfaulting seismic images to correlate seismic reflectors across faults is helpful in seismic interpretation and is useful for seismic horizon extraction. Methods for unfaulting typically assume that fault geometries need not change during unfaulting. However, for seismic images containing multiple faults and, especially, intersecting faults, this assumption often results in unnecessary distortions in unfaulted images. We have developed two methods to compute vector shifts that simultaneously move fault blocks and the faults themselves to obtain an unfaulted image with minimal distortions. For both methods, we have used estimated fault positions and slip vectors to construct unfaulting equations for image samples alongside faults, and we have constructed simple partial differential equations for samples away from faults. We have solved these two different kinds of equations simultaneously to compute unfaulting vector shifts that are continuous everywhere except at faults. We have tested both methods on a synthetic seismic image containing normal, reverse, and intersecting faults. We also have applied one of the methods to a real 3D seismic image complicated by numerous intersecting faults.

2016 ◽  
Vol 4 (2) ◽  
pp. T227-T237 ◽  
Author(s):  
Xinming Wu ◽  
Dave Hale

Extracting fault, unconformity, and horizon surfaces from a seismic image is useful for interpretation of geologic structures and stratigraphic features. Although others automate the extraction of each type of these surfaces to some extent, it is difficult to automatically interpret a seismic image with all three types of surfaces because they could intersect with each other. For example, horizons can be especially difficult to extract from a seismic image complicated by faults and unconformities because a horizon surface can be dislocated at faults and terminated at unconformities. We have proposed a processing procedure to automatically extract all the faults, unconformities, and horizon surfaces from a 3D seismic image. In our processing, we first extracted fault surfaces, estimated fault slips, and undid the faulting in the seismic image. Then, we extracted unconformities from the unfaulted image with continuous reflectors across faults. Finally, we used the unconformities as constraints for image flattening and horizon extraction. Most of the processing was image processing or array processing and was achieved by efficiently solving partial differential equations. We used a 3D real example with faults and unconformities to demonstrate the entire image processing.


Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. IM35-IM44 ◽  
Author(s):  
Xinming Wu ◽  
Dave Hale

In seismic images, an unconformity can be first identified by reflector terminations (i.e., truncation, toplap, onlap, or downlap), and then it can be traced downdip to its corresponding correlative conformity, or updip to a parallel unconformity; for example, in topsets. Unconformity detection is a significant aspect of seismic stratigraphic interpretation, but most automatic methods work only in 2D and can only detect angular unconformities with reflector terminations. Moreover, unconformities pose challenges for automatic techniques used in seismic interpretation. First, it is difficult to accurately estimate normal vectors or slopes of seismic reflectors at an unconformity with multioriented structures due to reflector terminations. Second, seismic flattening methods cannot correctly flatten reflectors at unconformities that represent hiatuses or geologic age gaps. We have developed a 3D unconformity attribute computed from a seismic amplitude image to detect unconformities by highlighting the angular unconformities and corresponding parallel unconformities or correlative conformities. These detected unconformity surfaces were further used as constraints for a structure-tensor method to more accurately estimate seismic normal vectors at unconformities. Finally, using detected unconformities as constraints and more accurate normal vectors, we could better flatten seismic images with unconformities.


Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. IM21-IM33 ◽  
Author(s):  
Xinming Wu ◽  
Dave Hale

Horizons are geologically significant surfaces that can be extracted from seismic images. Color coding of horizons based on amplitude or other attributes can help reveal ancient sedimentary environments and structural features. Extracted horizons are also used for building structure models and stratigraphic interpretations. We propose two methods for constructing seismic horizons aligned with reflectors in a 3D seismic image. The first method generates horizons one at a time; the second method generates an entire volume of horizons at once by first computing a relative geologic time volume from seismic normal vectors. Rather than gradually building a horizon by extending one or more seed points to a surface along seismic reflectors, both of our methods generate whole horizons at once by solving partial differential equations derived from seismic normal vectors. The most significant new aspect of both methods is the ability to specify, perhaps interactively during interpretation, a small number of control points that may be scattered throughout a 3D seismic image. Experiments revealed that with our method, control points enable the extraction of more accurate horizons from seismic images in which noise, unconformities, and faults are apparent. These points represent constraints that we implemented as preconditioners in the conjugate gradient method used to construct horizons.


2020 ◽  
Author(s):  
A. K. Nandakumaran ◽  
P. S. Datti

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