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GCUnderstanding Seismic Amplitudes*

By

Steve Henry1

 

Search and Discovery Article #40135 (2004)

 

*Adapted from the Geophysical Corner columns in AAPG Explorer, July and August, 2004, entitled, respectively, “Understanding Seismic Amplitudes” and “More Amplitude Understanding” and prepared by the author. Appreciation is expressed to the author, to Alistar R. Brown, editor of Geophysical Corner, and to Larry Nation, AAPG Communications Director, for their support of this online version. 

 

1GeoLearn, Houston, Texas ([email protected])

 

General Statement 

Seismic interpretation is fundamentally based on interpreting changes in amplitude. The changing amplitude values that define the seismic Previous HittraceNext Hit are typically explained using the convolutional model. This model states that Previous HittraceNext Hit amplitudes have three controlling factors:

  • The reflection coefficient (RC) series (geology).

  • The seismic wavelet.

  • The wavelet's interactions through convolution.

 

Large impedance (velocity x density) contrasts at geologic boundaries will generally have higher amplitudes on the seismic Previous HittraceNext Hit. Interpreters associate changes in seismic amplitudes with changes in the geology; this is a good assumption only if all of the factors that affect Previous HittraceNext Hit amplitudes have been considered. 

This article is intended to provide the interpreter with a checklist of the factors that should be considered when associating amplitude changes on the seismic Previous HittraceNext Hit with changes in geology. First, it presents the major effects that interpreters need to understand about seismic acquisition, where the wavelet is generated and the field Previous HittraceNext Hit recorded, and the interaction of the wavelet with the geology. Of 21-listed factors that affect seismic amplitudes through seismic acquisition and the earth, five are most important. One of the primary goals of seismic processing is to compensate for curved ray spherical divergence, which is one of the five factors. The other four factors before processing remain in the seismic data, as they are not normally corrected in seismic processing. 

Second, this article discusses the factors affecting amplitudes in seismic processing and interpreter controls on the workstation (loading, processing, and display). When all these factors have been considered, then the changes in amplitudes can be more reliably related to changes in geology.

 

 

uGeneral statement

uFigure captions

uFactors before processing

uFactors in processing & interpretation

uConclusion

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uGeneral statement

uFigure captions

uFactors before processing

uFactors in processing & interpretation

uConclusion

uReference

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uGeneral statement

uFigure captions

uFactors before processing

uFactors in processing & interpretation

uConclusion

uReference

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uGeneral statement

uFigure captions

uFactors before processing

uFactors in processing & interpretation

uConclusion

uReference

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure and Table Captions

Figure 1 Factors affecting amplitudes are shown in red for the sources, and cyan for those in the earth. Numbers refer to Table 1, where bold lettering (F5-F8) indicates increased importance.

Figure 2. Factors affecting amplitudes are shown in blue for the receivers and violet for the recording systems. Numbers refer to Table 1, where bold lettering (F21) indicates increased importance.

Figure 3. Illustrative earth model. Reflection coefficients for sands are identical. Red dots are where the amplitudes have been calculated in Figure 4. Blue dot is position of amplitude for dipping Sand 3 before seismic migration moved amplitude 1100 m laterally and 275 m (200 ms) vertically updip (Vavg-2860 m/s).

Figure 4. Notice the changes in amplitude values through the application of a typical seismic processing sequence. This illustrates the changes for the zero-offset Previous HittraceNext Hit at the top sand reflectors shown in Figure 3. Observe the amplitude decreases with depth, and the major amplitude changes due to the amplitude correction, and deconvolution. Amplitudes from the dipping sand also change with NMO and Stack, and move with migration to proper location.

Table 1. Checklist of factors that affect amplitudes before processing. Factors in bold are more important.

Table 2. Checklist of factors, in processing and interpretation, affecting amplitudes. Factors in bold lettering are more important.

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Factors Affecting Amplitude Before Seismic Processing 

Factors that affect amplitudes, before seismic processing, are illustrated in Figures 1 and 2. A checklist of 21 factors, along with brief comments describing the factors and an estimated magnitude of the effect, comprises Table 1 The magnitude of most of these can only be estimated, and removing their effects to obtain absolutely true amplitudes is impossible. Fortunately, Previous HitrelativeNext Hit changes in amplitude have been shown to be adequate and have been successfully applied for reducing risk, such as direct hydrocarbon indicators, estimating lithofacies, etc.  

Although only the moderate and major effects are discussed here, it is important to keep in mind how the amplitudes are being used in the interpretation. If a well is being proposed based solely on an amplitude anomaly, even a minor to moderate effect would need to be examined, as it could have a significant impact. 

The five factors that have a big effect on amplitudes during the acquisition of field data are shown in black lettering in Figures 1 and 2. The most important of these factors is the loss of energy due to curved-ray spherical divergence (F6). This effect on amplitudes is often approximated by the inverse square of distance, which for constant velocity is the inverse square of time. This factor is smaller for reflectors that are separated by less time, and minor for most lateral changes. For the real, non-constant velocity earth, this effect is greater (1/v2t) but still inadequate for recovering true amplitudes of deep reflectors.  

Laterally discontinuous (F5) high impedance geologic features can greatly reduce the amount of energy transmitted to the underlying geology. This reduces the amplitude of otherwise high amplitude reflectors beneath and over a lateral distance of half a spread length off the sides of the anomaly. In extreme cases (e.g. salt, volcanics), the amplitudes of underlying reflectors can be reduced to below the noise level and disappear from the data. 

Tuning (F7) occurs when the separation between RC creates constructive or destructive interference of the wavelet's center and side lobes. This interference can increase or decrease amplitudes and is most evident in areas of geologic thinning such as angular unconformities or stratigraphic pinch-outs. The magnitude of this effect can be major, but normally it does not exceed a factor of 1.5 as determined by the size of the side lobes. 

Amplitude variations with angle (AVA or AVO) relate Previous HitrelativeNext Hit amplitude changes (F8) in pre-stacked data to combined rock and pore-space fluid properties. This effect can be large for some gas effects. The appearance of this offset-dependent variation will be much less apparent on the stacked Previous HittraceNext Hit that contains the summation of all offsets. Overall on the final stack, AVA effects are in the range of a factor of 2-5 compared to no AVA. 

The placement of sources and receivers on the surface of the earth is not always uniform, resulting in missing ground positions (F21) that can have a moderate to major effect on amplitudes. Often, buildings, platforms, lakes, rivers, etc., must be avoided; stations are skipped; and traces will be missing from the stacking bin. This reduces the ability of stack to reduce random noise -- but the greater effect is a frequency unbalancing.

 

Factors Affecting Amplitudes Arising in Processing and Interpretation 

In addition to the 21 factors that could affect seismic amplitudes through seismic acquisition and the earth, 14 other additional factors, listed here (Table 2), arise in seismic processing and interpretation. Again, only the major factors are discussed; unfortunately, any of the factors could be important in interpreting amplitude changes as changes in geology. 

It is good practice for interpreters to inform seismic processors (good processors appreciate this) how they will use the data in interpretation (i.e., structural, stratigraphic, AVA, etc.). Processors will appreciate your insights because they will be using tens of processing programs containing hundreds of parameters. Many of the programs and parameters alter seismic amplitudes. 

Table 2 summarizes the most important of these amplitude-altering processing steps. You can use this table in amplitude discussions with your processor. 

In order to assist in the understanding of workstation amplitudes, the processing of a pair of seismic traces is reviewed. Both the wavelet shape and amplitude from the top of high impedance sands are followed from the raw field traces to their final processed form. To begin this journey, consider a simplified earth in which thick (200m) sands reside in a shale-dominated section (Figure 3). Two of the sand units are flat (sands 1 and 2), and the third is dipping at 15 degrees (sand 3). The normal incidence reflection coefficients for the top of all of the sand units are identical. Ideally, workstation amplitude for these sands would also be identical. 

Figure 4 shows the wavelets from the top of these thick sands as seen through successive stages of seismic processing. Reading from left to right, first observe the zero-offset, raw field Previous HittraceNext Hit before processing. Then notice the changes in the seismic amplitudes due to an idealized processing sequence of:

  • Curved-ray, spherical-divergence correction.

  • Minimum-phase deconvolution.

  • Normal moveout (NMO) correction and stack.

  • Migration.

 

After-migration amplitude values (shown in red) should ideally be identical for all the top sand reflectors. The only amplitudes that are identical are the two from the flat sand 1. The deeper flat sand visible on Previous HitTraceNext Hit 1 should have the same amplitude value as the shallower reflector; unfortunately, spherical-divergence correction programs (F23) typically under-correct deep amplitudes.  

This correction only accounted for one of the many amplitude-altering factors encountered by the wavelet during its round-trip between the surface and the top of sand 2. The observed amplitude at sand 2 also is a function of the phase and frequency content of the wavelet (F24), which is different from sand 1 due to attenuation and maybe assumptions in deconvolution. 

On the migrated version of Previous HitTraceNext Hit 2 we view the dipping-reflector from sand 3 at the same time as sand 2 on Previous HitTraceNext Hit 1. The dipping sand has lower amplitude than the flat sand, due to NMO (F26) combined with stack (F29). 

In our simple model, we assume that a flat-reflector value was used for the NMO correction. Thus, NMO is correct only for flat reflectors so that the stack process attenuates the amplitude of dipping reflectors, due to uncorrected dip contamination of the NMO velocities. In addition, dipping reflectors are displaced from their apparent location on the stacked section. Thus, they must be migrated (F32) to their proper subsurface positions. As shown in Figure 3, the amplitude that will be displayed on the workstation for Previous HitTraceNext Hit 2 at 3.0 sec. was actually from a point 1100 m laterally and 275 m vertically down dip. 

The journey of these amplitudes is not yet completed, as we must load the data onto the workstation for our interpretation. In the loading process, a percentage of the largest peaks and troughs may be clipped (squared off) to improve the visual dynamic range (F34). Only the largest amplitudes are affected, but these are often of the greatest interest as possible direct hydrocarbon indicators. 

With the seismic data now loaded, interpreters have many opportunities to alter amplitudes further (F35). For example, 2-D line Previous HitbalancingNext Hit programs change gains, timing, frequency, and phase. In addition, user-applied settings for filtering, phase rotation, and even the selection of color bars change how amplitudes are perceived.

 

Concluding Remarks 

Amplitudes are the basic input to seismic attribute analysis calculations. 

Factors have been described that affect seismic amplitudes through seismic acquisition, the earth, seismic processing, and seismic interpretation. Seismic interpretation contains most of the major amplitude factors (Table 2), and the interpreter controls these based on knowledge (F36). By not understanding the factors that affect amplitudes, drilling decisions can be in error. 

On the other hand, Previous HitrelativeTop amplitudes provided to interpreters are, with care, being successfully used for reducing risk and discovering hydrocarbons. You can improve your amplitude-based interpretations by considering the factors described. Your interpretation is on the firmest foundation by comparing amplitudes that are at approximately the same two-way time and have similar overlying geologic sections. Relating amplitudes to geology on vertically separated reflectors, or in areas of laterally changing geology, is risky -- and a reason for many unsuccessful wells.

 

Reference 

Sheriff, R. E., 1975, Factors affecting seismic amplitudes: Geophysical Prospecting, v. 23, p. 125-138.

 

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