February 21, 2009
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Home / Issue Archive / 2009 / February #2 / Geotrace Technologies Increase Seismic Data Resolution

№ 2 (February 2009)

Geotrace Technologies Increase Seismic Data Resolution

Geotrace HFI™ and BE™ technologies were used to extend the high frequency band reflection spectrum of 2D and 3D stacked data acquired in a number of fields in Western and Eastern Siberia, and Kazakhstan.

By A.A. Bezhentsev, S.A. Deviashin

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The general task was to assess the effectiveness of these technologies in terms of increase of the seismic data vertical resolution and to reveal the ill-defined faults, and to forecast the trends of lateral variability of pay formations. As a result the higher quality imaging of the acquired data was achieved that in a number of cases gave a chance to detect previously invisible geomorphological details.

HFI™ (High Frequency Imaging)
Technology HFI™ technology designed by Geotrace was used to extend the spectrum of the stacked seismic data. This unique technology of seismic data frequency band extension makes it possible to resolve higher spectrum frequencies to compare with conventional methods. It is a widely known but seldom-used characteristic of seismic that the apparently narrow band trace contains higher-frequency information than an extracted wavelet would suggest. By recognizing that convolution is equivalent to polynomial multiplication, and polynomial division is its exact inverse, one can easily demonstrate this latent seismic characteristic.

A synthetic seismogram is constructed by convolving a spike series with a band-limited wavelet, the result being a band-limited trace containing, apparently, only those frequencies, which were included in the wavelet. However, by employing polynomial division, the spike series can be obtained from the synthetic seismic trace. In other words, all of the original high-frequency information is contained in the low-frequency trace. Unfortunately, polynomial division cannot be used in the real world, because even the smallest amount of noise introduced into the trace makes the process unstable.

HFI uses vector calculus, rather than polynomial mathematics, to solve the problem by viewing convolution as a vector rotation. The vector that represents the apparent low-frequency seismic is precisely determined, then rotated toward a white spectral position in the chosen vector space. The process is not sabotaged by ambient noise, and the resulting seismic is broadband with a higher signal-to-noise ratio. In one case, using the pre-STM data with 48 Hz maximum usable frequency as input, the HFI™ yields 110-Hz data on the high end increasing the usable band by 129 percent. Now, beds as thin as 10 meters could be resolved.

HFI™ is an accurate mathematical process requiring no evaluation of the wavelet shape to identify the rock reflectance. Additional calibration with synthetic seismograms by log or VSP ensures better results. The input data quality is an essential parameter affecting HFI™ successful application.

BE™ (Bandwidth Extension) Technology
We always think about needing HIGHER frequencies but LOWER frequencies are just as important – BE goes lower as well as higher Widess et al. [1] revealed that phase and amplitude variations result from the effect of reflectors beyond common extension. In 2007 Geotrace designed Bandwidth Extension (BE™) algorithm capable to recover this data more efficiently. The trace is optimized in terms of resolution. The uncertainty principle states that we cannot know the exact frequency at the exact time anywhere in the spectrum, but in the low end of the spectrum frequency resolution is more important than time resolution and at the high end of the spectrum just the opposite is true.  BE takes advantage of these characteristics.

BE utilizes the Continuous Wavelet Transform (CWT) to perform a time series analysis of the seismic trace that decomposes the trace into its respective amplitude and phase components in both frequency and time.

Using the fundamental frequencies at our disposal we predict their harmonics to extend the upper end of the spectrum and sub-harmonics to extend the lower end. If there is reflectivity present in the data that corresponds to the harmonic frequencies it will remain in the result. Any harmonic or sub-harmonic frequencies that do not correspond to reflectivity in the data fall out of the spectrum. The result is both broader band and more accurate than conventional methods such as whitening, well calibration whitening and colored inversion. Michael Smith et al [2] provide more details of BE™.

The results before and after BE™ application are shown in Fig. 1. The input data frequency is about 17-55 Hz and has good compliance with synthetic data (70 percent correlation). The resulting harmonic and sub-harmonic model added one extra data octave in terms both on the lower and higher side of the spectrum. Frequency band of data after BE™ application is 10-120 Hz.

This broader spectrum gives a chance to observe much richer low frequencies, as well as more high-frequency details. The disadvantage of the majority of spectrum extension methods is the reduction of the signal/noise ratio. In our case it is preserved at the original level (68 percent correlation).

Both frequency band extension methods are highly dependent on the input seismic data. Application of tough noise suppression filters or frequency band cut-off makes application of both HFI™, and BE™ impossible. The advantage of HFI™ consists in the fact that it can work using seismic data not reduced to a zero-phase wavelet and can give good correlation with wells, whereas BE™ requires strict zero-phase input data.

HFI™ and BE™ are also used for preparation of seismic data for inversion, spectral decomposition and AVO analysis; in this case both stacked and pre-stack data are processed. Below there are the examples of HFI™ and BE™ application to stacked seismic data acquired at a number of fields in various geological conditions.

Western Siberian Fields
The task of the survey in one of the Western Siberian fields was to use HFI™ and BE™ methods of frequency band extension for 3D seismic data and to assess their applicability for:

Assessment of facies behavior in Upper-Jurassic sediments;
Delineation of Lower Cretaceous sediments for reservoirs identification;
Identification of low-amplitude tectonic dislocations both in Upper Jurassic and Lower Cretaceous sediments and assessment of their effect on facies behavior.
Both Upper Jurassic and Lower Cretaceous generally feature thin layers with low reflectivity factors and laterally lithologically variable that makes them complicated targets for interpretation. Faults in the lower part of the section are mainly low-amplitude.

Application of HFI™ technology resulted in a cube of data with a band width up to 140 Hz making it possible to resolve previously undescribed geomorphological peculiar features along JV1-1 horizon, such as a paleochannel spreading from the southeast to the northwest. Facies behavior data comparison with well log data revealed good correlation between the spread of the channel facies and reservoir properties. Availability of paleochannels within JV1-1 interval was also verified by O. Pinus et al. [3].

The enhanced resolution in the area of AB layer was not as prominent, as in Lower Jurassic that is the function of a lower contrast in impedance in the top part of the cross section. Anyway, the technology was helpful to resolve the horizons, which would be studied with the help other methods.
The most impressive result of HFI™ and BE™ application was the resolving of non-uniformities within Bazhenov formation that may be indicative of potential reservoirs.

In other cases in the Western Siberian fields the Neocomian clinoform formations characterized with the landslide cones and complicated paleorelief were surveyed. Application of HFI™ technology resulted in cubes of data with a band width up to 120-140 Hz making it possible to improve the resolution critically and to resolve morphological peculiar features of the target formations.
The input data quality is critical for the effectiveness of both technologies.

Hence, for example, the data, wherein the input spectrum after filter application was limited above 55 Hz, was tested. As a result the high-frequency side of the spectrum could not be used with HFI™ analysis and the output data resolution was not essentially improved.

Based on the results of application of HFI™ _ BE™ technologies providing the frequency band extension in terms of the stacked seismic data we can conclude that these technologies give very good outcomes at relatively low costs and may be used to resolve various geological and geophysical tasks including studies in Western Siberia. These technologies give the best results for data with the high impedance contrast and high signal/noise ratio.

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