Local structural discontinuity attribute robustness on 3-D seismic data to identify subtle faults

Limited seismic data quality and complex tectonics make for less than ideal interpretation conditions. However, modern geometric attributes including coherency has shown to be effective in showing the lateral extents of subtle and small-scale geologic features not usually visible in conventional seismic sections. This geometric attributes are better suited than some older generation seismic attributes as they work on the full data volume and eliminate the need for pre-picked horizons for them to be implemented. Coherency attributes applied to 3D seismic data volume have confirmed to be an effective method for imaging geological discontinuities such as fault and stratigraphic features. These geological features are significant since they are often associated with the formation of subsurface traps in which petroleum might accumulate. Coherence calculations can help with the problems mentioned above. 3-D Seismic coherency provides interpreters a different view, revealing subtle features not easily seen in the seismic data. It calculates the local waveform similarity in both In-line and X-line direction and estimates lateral discontinuity caused by variation in structure, stratigraphy, lithology, porosity, and the presence of hydrocarbons. Small regions of seismic traces cut by a fault surface generally have a different seismic character than the corresponding regions of neighboring traces. This results in a sharp discontinuity in local trace-to-trace coherency. Calculating coherency for each grid point along a time slice results in lineaments of low coherency along faults. When this process is repeated for a series of time slices, these lineaments become fault surfaces, even though fault plane reflections have not been recorded. Stratigraphic boundaries generate similar discontinuities. The technique may be employed to produce coherency horizon slice maps, or to transform a reflection amplitude 3-D data volume into an entirely new volume or “cube” of coherence coefficients. Map views of coherency data afford the opportunity to see stratigraphic changes more clearly. For example, the channel features that are readily apparent to laymen in the coherency time slice are very difficult to see in a traditional amplitude time slice.
Conventional amplitude time slices are often useful for viewing faults that run perpendicular to strike. However, when faults run parallel to strike, they become more difficult to see because the fault lineamentsbecome superimposed on bedding lineaments. The coherence calculation suppresses laterally consistent features, in effect removing the bedding. Because of this, the 3-D coherence algorithm reveals faults in any orientation equally well.
Until recent years, most 3-D surveys covered relatively small areas. But the success of the technique and falling costs have caused surveys to becomelarger. Now some vast spec 3-D surveys cover hundreds of square kilometers and run to tens of millions of traces. Sorting through that amount of information is a daunting task. However, since calculating coherence is an non interpretive process, it can quickly provide the geoscientist with a view of regional faulting.
The first generation coherence algorithm, cross correlates each trace with its in-line and cross-line neighbor and then combines the two results after normalizing by the energy. Since this approach deals with only three traces, it is computationally very efficient but may lack robustness, especially when dealing with noisy data. The second generation coherency algorithm uses a multi-trace semblance measure. Using more traces in the coherency computations results in greater stability in the presence of noise. The third generation algorithm is also a multi-trace coherency measure. However, it is based on the Eigen-structure of the covariance matrix formed from the traces in the analysis cube.
In this paper, an analysis method is developed for the robust and efficient estimation of 3D seismic local structural entropy, which is a measure of local discontinuity of 3D seismic data to identify its subtle faults. This method avoids the computation of large covariance matrices and eigenvalues, associated with the eigenstructure-based and semblance-based coherency estimates. We introduce a number of local discontinuity measures, based on the relations between subvolumes (quadrants) of the analysis cube. The scale of the analysis is determined by the type of geological feature that is of interest to the interpreter. By combining local structural entropy volumes using various scales, we obtain a higher lateral resolution and better discrimination between incoherent and coherent seismic events. Furthermore, the method developed is computationally much more efficient than the eigenstructure-based coherency method. Its robustness is demonstrated by synthetic and real data examples. To study the robustness of the algorithm and the effective parameters, three synthetic geological model containing faults generated and the best values for these parameters were suggested. This local attributes was applied on real 3D seismic data of a faulted gas field. Results show the robustness of this algorithm in revealing subtle faults. In this algorithm local similarity in both In-line and X-line direction and in depth direction was calculated based on the relations between sub-volumes (quadrants) of the analysis cube and estimates the lateral and vertical discontinuity. The scale of the analysis cube is determined by the type of geological feature that is of interest to the interpreter.
Not only is this method robust to noise than original three-trace cross-correlation-based algorithm but also is computationally efficient because it avoids the computation of large covariance matrixes and Eigen-values, associated with the Eigen-structure-based and semblance-based coherency estimates.