Why it is Different and What it can do with Seismic Data for Oil and Gas Exploration and Production
By Norman Neidell, EurAm Geo-Focus
Introduction
Current seismic imaging does not image the subsurface. It images only reflections from the subsurface. Holography forms images of the subsurface itself and directly. These images are scaled in velocities which approximate the actual earth material values and look much like the subsurface geology. Hence, such images by having greater resolution and visibility may be directly interpreted in great detail. This technology differs from standard seismic data treatments in several aspects:
Spatial and time resolution depend also on survey data redundancy and not only on survey acquisition field parameters.
Time resolution is increased by about a factor of 5 and interpretive observations increase significantly.
The character of the source is incidental.
There is no common propagating waveform.
The image space and time sampling are user determined, and typically can be 16 or more times denser taken together, than standard seismic image sampling. Applicable Nyquist limits depend on the user selected image sampling and not only field parameters.
All imaged earth features are seen with frequencies and are necessary to describe their character within the user specified sampling bounds, irrespective of the source character and frequency content.
The data can be managed and interpreted using standard interpretive systems and is amenable to advanced calculations including attributes.
With this seismic technology one can usually estimate reservoir volumetrics ahead of the drill-bit in most cases.
Theory
Holographic seismic imaging uses a subsurface model based on voxels, each of which is treated as a point diffractor. Voxel size in space and time is decided by the user but of course must be consistent and compatible with the data information content of the survey. There is no assumption made regarding a layered earth nor containing a common propagating wavelet. Each source illuminates every voxel and information recorded by the many receivers must be restored in best approximation to the appropriate voxel. We seek a relative reflectivity value for each voxel. Please note that this point of view gives great weight also to the data redundancy which seismic field practices routinely include.
The rationale, theory, and mechanics of digital seismic holographic imaging have previously been well documented. Four papers by Neidell in 1997 (Parts 1 -4) explain the underlying concepts, while a fifth publication authored with Mr. James Charuk presents more general considerations and shows many case studies. The four-part series goes from explaining the space-time linkage of variables inherent in operations such as proposed by Kirchhoff to understanding the distinctions between reflective and diffractive contributions. Part 3 views operations like Kirchhoff methods as transformations while Part 4 looks both at the matter of resolution and understanding how imaging the propagation medium differs from capturing images of wavefields.
Method
Seismic holographic data is “rich” in information so that new displays are beneficial to fully present this content. Here we introduce and use extended visual dynamic range (EVDR) color displays scaled as estimated surface velocities in equal increments – usually 200 ft/s or 400 ft/s. A color bar as used should preferably be “universal” so that with minimum experience both lithology and geometry can be understood by knowledgeable inspection. This alone is a great advantage for initial interpretive insights.
These data presentations represent approximations to full wavefield inversions. These differ greatly from full waveform inversions (FWI) which embody all limitations inherent in an assumed propagating waveform. Full wavefield inversion displays closely resemble the underlying geology and provide as noted with increased interpretive visibility. Carbonate features are identified with great detail, and resolution becomes more than adequate for reservoir studies and meaningful 4d work. Interpretive advantages are usually realized for both clastic and carbonate formations, as well as conventional and unconventional reservoirs.
Detailed recognition of structure and velocity changes within formations especially using also corresponding well log measurements and production information, via correlative and AI studies allow reasonable estimates concerning hydrocarbon presence, porosity, and various rock properties to be better determined. This method has been applied virtually all over the globe and has been responsible for a number of significant discoveries. Skeptics to claims and statements made here should read the independent writings of Professor Enders Robinson – the “father” of digital seismic technology, and Professor Elmer Eisner, formerly chief scientist of Texaco, Inc who licensed the technology. Eisner (1998) describes the holographic or holistic method and how it substitutes other criteria as data limits in place of the usually understood Nyquist limits. Also, the work of Robinson in both 1998 and 2018 show a deep understanding and appreciation of the seismic holographic imaging process and strongly advocate its use. The real-world successes and the obvious advantage indicate that digital holographic seismic imaging should offer reduced risks, lower costs, and enhanced profits.
Case studies
As a first case we note the geological equivalent of a unicorn – an image of an Austin Chalk reef in Webb County, Texas in Figure 1. Such developments are not likely recognized at all using standard seismic data treatments. This case is a well-developed ancient atoll. It would be interesting to determine how many Austin Chalk reefs have been previously imaged.
Figure 1: Austin Chalk reef in Webb County, Texas. (a) Location of transect on a time slice through the zone of interest. (b) Seismic line along transect A-A’. (c) EVDR image along same transect.
The second case study shows a known and thick carbonate section below a highly productive sand section (Figure 2). This example presents a significant interpretive challenge. However, the zone of interest clearly stands out in the EVDR color display. In both cases a color bar using 400 ft/s increments is shown on the displays and with colors changes representing quantitative values.
It would be of great value now to note that the existing and readily available systems for managing and interpreting seismic data provide excellent vehicles for presenting and studying results of holographic seismic imaging as presented here. Hence, Figure 3 displays a holographic seismic imaging result which demonstrates both the capability and flexibility when using readily-available seismic workstation and software. We see that we can show time slices, sections, chair diagrams, etc., and readily perform operations such as flattening on particular horizons as well as other most frequently applied procedures and views. We may also overlay well logs and wiggle trace information to facilitate correlations and combine different kinds of data for correlative purposes.
Conclusions