S-Wave Analysis of Fracture Systems

S-Wave Analysis

Most rocks are anisotropic, meaning that their elastic properties are different when measured in different directions.

For example, elastic moduli measured perpendicular to bedding differ from elastic moduli measured parallel to bedding – and moduli measured parallel to elongated and aligned grains differ from moduli measured perpendicular to that grain axis.

Because elastic moduli affect seismic propagation velocity, seismic wave modes react to rock anisotropy by exhibiting direction-dependent velocity, which in turn creates direction dependent reflectivity. Repeated tests by numerous people have shown shear (S) waves have greater sensitivity to rock anisotropy than do compressional (P) waves.

Slowly the important role of S-waves for evaluating fracture systems, one of the most common types of rock anisotropy, is moving from the research arena into actual use across fracture prospects. Examples of S-wave technology being used to determine fracture orientation have been published in past Geophysical Corners (e.g., Gaiser, April and May 2003 EXPLORERs).

It seems timely to introduce one more example.

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Most rocks are anisotropic, meaning that their elastic properties are different when measured in different directions.

For example, elastic moduli measured perpendicular to bedding differ from elastic moduli measured parallel to bedding – and moduli measured parallel to elongated and aligned grains differ from moduli measured perpendicular to that grain axis.

Because elastic moduli affect seismic propagation velocity, seismic wave modes react to rock anisotropy by exhibiting direction-dependent velocity, which in turn creates direction dependent reflectivity. Repeated tests by numerous people have shown shear (S) waves have greater sensitivity to rock anisotropy than do compressional (P) waves.

Slowly the important role of S-waves for evaluating fracture systems, one of the most common types of rock anisotropy, is moving from the research arena into actual use across fracture prospects. Examples of S-wave technology being used to determine fracture orientation have been published in past Geophysical Corners (e.g., Gaiser, April and May 2003 EXPLORERs).

It seems timely to introduce one more example.


The prospect considered here involves two fractured carbonate intervals at a depth of a little more than 1,800 meters (6,000 feet). A small 5.75-km2 (2.25-mile2) three-component 3-D seismic survey (3C3D) was acquired to determine whether PP (compressional) and PS (converted-S) data could be used to determine fracture orientation for optimal positioning of a horizontal well.

shows a PP and PS azimuth-dependent data analysis done in a superbin near the center of this survey. At this superbin location, common-azimuth gathers of PP and PS data extending from 0 to 2,000-meter offsets were made in narrow, overlapping, 20-degree azimuth corridors.

In each of these azimuth corridors, the far-offset traces were excellent quality and were summed to make a single trace showing arrival times and amplitudes of the reflection waveforms from two fracture target intervals A and B.

To aid in visually assessing the character of these summed traces, each trace is repeated three times inside its azimuth corridor in the display format used in.

Inspection of these azimuth dependent data shows two important facts:

PS waves arrive earliest in the azimuth corridor centered 50° east of north (the fast-S mode, S1) and latest in an azimuth direction 140° east of north (the slow-S mode, S2).

PS waves exhibit a greater variation in arrival times and amplitudes than do their companion PP waves. For example, PP reflectivity from interval A is practically constant in all azimuth directions, whereas PS reflectivity varies significantly with azimuth. Likewise, PP arrival time of event A changes by only 4 ms between azimuth directions 50° and 140°, but PS arrival times change by almost 50 ms, an order of magnitude greater than the variation in PP arrival times.


Azimuth-dependent trace gathers like these were created at many locations across the seismic image space, and the azimuths in which PS reflection amplitudes from fracture intervals A and B were maximum were determined at each analysis location to estimate fracture orientation for each interval.

A map of S-wave-based azimuth results for interval A in the vicinity of calibration well C1 is displayed as.

Shown as rose diagrams on this map are fracture orientations across the two reservoir intervals as interpreted by a service company using Formation Multi- Imaging (FMI) log data acquired in well C1. S-wave estimates of fracture orientations are shown as short arrows at analysis sites near the well. This S-wave-generated map indicates the same fracture orientations interpreted from the FMI log data.

On the basis of this close correspondence between FMI and S-wave estimates of fracture orientation, the operator used S-wave estimates across the total seismic image area to position and orient a horizontal well trending perpendicular to seismic based fracture orientation. This well found the S-wave estimates of fracture orientation to be accurate across its drilled lateral distance of approximately 1,000 meters, and serves as a good real-world example of the value of S-wave seismic data for evaluating fracture prospects.

In this instance, S-wave data provided fracture information that could not be extracted from P-wave data.

We conclude that application of S-wave seismic technology across fracture prospects should be considered by operators when possible.


A post-mortem comment on this particular horizontal drilling: The well was not placed in production – even though the well bore intersected a high population of fractures trending perpendicular to the well axis – because too many of the fractures were plugged with cement.

That problem sets the stage for next month’s article, in which we will describe S-wave attributes that can be used to indicate fracture intensity and openness.