From Bureau of Economic Geology, The University of Texas at Austin (
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Invited Keynote Address, Lithology and Fluid Prediction Workshop, European Association of Geoscientists and Engineers (EAGE) Convention, Stavanger, Norway, June 1, 2003

Lithology and Fluid Prediction in Exploration: Think Vectors!

Bob Hardage

For decades, the seismic information that has been used to estimate lithological and fluid properties of a propagating medium has been data in scalar form. For example, marine seismic data have been generated with scalar sources (air guns suspended in water) and recorded with scalar sensors (hydrophones). Onshore, vector sources (such as vertical-displacement vibrators) and vector sensors (vertical geophones) have been used, but we still have extracted only the vertical component of the P wavefield from the data and then used those data as scalar information. Scalar seismic data and vector seismic data are significantly different data domains. We will discuss some of the restrictions we have imposed on the rock/fluid prediction process by limiting our thought processes to scalar data. For example, how can we estimate anisotropic parameters of a medium with scalar data?

Illuminating Wavefields
We must begin thinking of the seismic data that we use in rock/fluid prediction as vector data. The downgoing near-field wavefields produced by a vector source in a homogeneous Earth consist of three fundamental modes: a compressional mode (P) and two shear modes (SH and SV). Each of these modes has a distinct particle displacement vector. The magnitudes and orientations of these particle displacement vectors carry valuable rock and fluid information. This information becomes available only if the vector properties of the illuminating wavefields are preserved during data acquisition, processing, and interpretation. In anisotropic media, the orientations of these particle displacement vectors shift so that they are no longer normal to, or tangent to, the propagating wavefield. However, these anisotropic wave modes (qP, qSH, qSV) can still be analyzed as vector data.

Reflected Wavefields
Once we use vector-wavefield seismic data to illuminate targets, new options for lithology and fluid estimation become available. Reflected wavefields are more complicated than the near-field illumination wavefields because several types of upgoing wave modes can be produced by the reflection process at an interface. These additional upgoing modes result from the fact that P and SV modes are coupled, allowing P displacements to convert into SV displacements during reflection/transmission. Similarly, SV displacement can generate P displacement. This transfer of energy from P to SV is the basis of the popular, scalar-based, P-wave AVO technology that is widely practiced in rock and fluid prediction.

We will look at a number of examples where reflected vector-wavefield data provide new insights into the conditions that exist within a propagation medium. For example, traditional seismic stratigraphy is based on scalar P-wave data. However, different seismic sequences and seismic facies become available when vector data are utilized in seismic stratigraphy analyses. Interpreters now need to transition from scalar seismic stratigraphy to elastic-wavefield seismic stratigraphy.

Subsurface Calibration
If we use vector-based seismic information rather than scalar-based seismic data in rock/fluid predictions, the subsurface geologic and engineering control used in these estimation efforts needs to be expressed in the same vector-space coordinates as the seismic data. An important challenge remains: How should scalar geologic/engineering information be transformed into vector data to implement a new generation of rock/fluid prediction?

An emerging seismic technology that is beginning to dominate exploration and exploitation programs is the concept of the vector seismic wavefield. Seismic sources, sensors, processing algorithms, and interpretation principles are shifting from the scalar world to the vector world to take advantage of the new rock/fluid information that is becoming available with vector data rather than scalar data. Vector thinking must now begin to be applied in seismic prediction of subsurface rock and fluid properties.