Interpretive processing

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Digital Imaging and Deconvolution: The ABCs of Seismic Exploration and Processing
DigitalImaging.png
Series Geophysical References Series
Title Digital Imaging and Deconvolution: The ABCs of Seismic Exploration and Processing
Author Enders A. Robinson and Sven Treitel
Chapter 12
DOI http://dx.doi.org/10.1190/1.9781560801610
ISBN 9781560801481
Store SEG Online Store
Listen! You hear the grating roar
Of pebbles which the waves draw back, and fling,
At their return, up the high strand.

—Matthew Arnold

What is petrophysics? Petrophysics (or rock physics) is the branch of geology that is concerned with the physical properties and behavior of rocks. Oil exploration requires direct and indirect measurements of the underground rock strata, the totality of which commonly is referred to as “the geology.” Well cores provide actual rock samples extracted from a well. Downhole instruments placed in oil wells provide direct measurements, or well logs, of the rocks in place. Cores and well logs are used to determine the petrophysics of the strata to help reveal potential oil-bearing reservoirs. Of interest in petrophysics are things such as rock type (e.g., sandstone, shale, limestone, etc.) and rock characteristics (e.g., porosity, permeability, fracturing, etc.).

The seismic method provides indirect measurements in the form of seismic records. The word indirect is appropriate because the seismic method uses a noninvasive technique (seismic waves and seismic recording instruments) to penetrate and record data from a remote body (the underground rocks). Similar techniques are radar, sonar, and ultrasonic medical imaging. Seismic records are made up of signals called traces, which record reflections of the seismic waves from the boundaries of different rock layers. Such rock-layer boundaries are called interfaces (or horizons). In some cases, horizons are approximately horizontal planar surfaces with low to moderate dips. In other cases, horizons are curved and contorted surfaces with steep dips.

Most familiar to us are water waves. Ancient Greek philosophers, many of whom were interested in music, hypothesized that a parallel exists between water waves and sound. It is said that by observing waves in the canals of his native Holland, Christiaan Huygens (1629-1695) could visualize the undulatory nature of light. It took well over a century for people to understand and accept Huygens’ theory of the wave nature of light. Today, we know that electromagnetic waves permeate through all the space in the universe.

The easiest way to observe a wavefield is to look at the surface of a body of water. To demonstrate wave motion, place a Pyrex baking dish with water in it on top of an overhead projector. Put various small obstacles in the dish. Use the tip of a pencil to generate waves in the dish and see on the screen how the waves interact with the obstacles.

Seismic records received by the instruments (i.e., by geophones on land or hydrophones at sea) represent the seismic wavefield as it is observed at the earth’s surface. Seismic processing is a method of using a computer to convert the observed seismic wave-field into an image of the underground geologic structure and stratigraphy. The horizontal dimensions (say, north and east) of such an image are in terms of distance (meters), whereas the vertical dimension (depth) can be in terms either of distance (meters) or of traveltime (seconds) to that depth. (Traveltime refers to the time that a seismic wave takes to travel a certain distance.) The purpose of seismic processing is to convert a recorded seismic wavefield into an image of the geology.

In most cases, the final image resulting from seismic processing is the migrated record. Migration is the act of transforming seismic data that were recorded as a function of arrival time into an image of the actual subsurface geometry. Imaging involves positioning (such as placing events in their correct positions), focusing (such as collapsing diffracted energy back to the point of diffraction), and sharpening (such as enhancing terminations of events relative to faults, salt flanks, and unconformities).

A stack is a composite record made by combining traces, usually by adding them together from different records. Stacking also involves filtering to deal with timing errors or waveform differences among the signals being stacked. Migrated seismic data necessarily are stacked in one way or another.

Interpretive processing is a method for enhancing the images (e.g., the depth-migrated records) provided by seismic processing to better reveal the overall geology or particular aspects of the geology. Interpretive processing comes under the heading of image enhancement. Generally speaking, interpretive processing involves principles of seismic waves and principles of deterministic and statistical imaging and of time-series analysis (Anderson et al., 1985[1]; Robinson, 1986[2], 1998a[3], 1998b[4], 2003[5]; Brillinger et al., 2004[6]).

The purpose of interpretive software is to do interpretive processing — namely, to convert the image of the geology provided by seismic processing into an enhanced (i.e., a prettier) image of that geology. Such enhanced images, which can be displayed on interpretive visualization systems, are used in the final evaluation to determine favorable sites for drilling new oil wells. The enhanced images, within the computer, are in the form of 2D or 3D arrays of data points.


References

  1. Anderson, O. D., J. K. Ord, and E. A. Robinson, 1985, Time series analysis, theory and practice, hydrological, geophysical, and spatial applications: Elsevier.
  2. Robinson, E. A., 1986, Image reconstruction in exploration geophysics, in H. Lee and G. Wade, eds., Modern acoustic imaging: IEEE Press, 285-296.
  3. Robinson, E. A., 1998a, Holistic migration: The Leading Edge, 17, no. 3, 313-320.
  4. Robinson, E. A., 1998b, Extended resolution by 3-D holographic seismic imaging: Proceedings of the Offshore Technology Conference, OTC 8677, 177-185.
  5. Robinson, E. A., 2003, Refinement of deconvolution by neural networks, in W. Sandham and M. Leggett, eds., Geophysical applications of artificial neural networks and fuzzy logic: Modern approaches in geophysics, 2003, 21, 57-70.
  6. Brillinger, D. R., E. A. Robinson, and F. P. Schoenberg, 2004, Time series analysis and applications to geophysical systems: Springer Verlag.

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