Seismic Anisotropy: Basic Theory and Applications in Exploration and Reservoir Characterization

by Ilya Tsvankin and Vladimir Grechka

Duration: Two days

Intended Audience: Intermediate level

Prerequisites (Knowledge/Experience/Education Required): The course is designed for both graduate students majoring in applied geophysics and more experienced geophysicists working in research, technical service, or exploration. Attendees are expected to be familiar with the basics of seismic wave propagation and data processing.

Elastic anisotropy, widely recognized as a typical feature of sedimentary formations, has a strong influence on seismic velocities and amplitudes. For example, the difference between stacking and vertical velocity in anisotropic media most commonly is the reason for misties in time-to-depth conversion. This course provides the necessary background information regarding anisotropic wave propagation and discusses modeling, inversion, and processing of seismic reflection data in the presence of anisotropy.

The most critical step in extending seismic processing to anisotropic media is to identify and obtain from the data the medium parameters responsible for measured reflection signatures. Therefore, the course emphasizes parameter estimation for transversely isotropic and orthorhombic subsurface models using both conventional narrow-azimuth data and wide-azimuth surveys. A description of P-wave time and depth processing for VTI (transversely isotropic with a vertical symmetry axis) media is followed by analysis of the joint inversion of P-waves and converted PS-modes which can yield the true vertical velocity needed for depth imaging. Field-data examples illustrate the improvements achieved by anisotropic migration algorithms and the possibilities of applying anisotropy parameters in lithology discrimination. The part devoted to anisotropic AVO analysis includes simple analytic approximations for reflection coefficients as well as for amplitude distortions (geometrical spreading) in the overburden. The course also introduces fracture-detection methods based on the azimuthal variation of reflection moveout and prestack amplitudes of P- and PS-waves.

The course should be useful for both graduate students and geophysicists working in exploration or reservoir monitoring. Mathematical details are kept to a minimum, but familiarity with the basics of elastic wave propagation and seismic data processing would be helpful.

Course Outline:

  • Basic description of anisotropic wave propagation
  • Anisotropic ray tracing
  • Notation and seismic signatures for vertical transverse isotropy
  • Normal-moveout velocity for 2D anisotropic media
  • 3D description of NMO velocity and NMO ellipse
  • Nonhyperbolic reflection moveout
  • P-wave time-domain signatures in VTI media
  • Inversion of dip and nonhyperbolic moveout
  • Time and depth processing of P-wave data for TI media
  • Moveout of PS-waves and the PP+PS=SS method
  • Joint inversion of PP and PS data for TI media
  • Case studies of multicomponent (PP+PS) processing
  • Notation and signatures for orthorhombic and HTI media
  • Anisotropic inversion of VSP data
  • Velocity-model building for downhole microseismic
  • Reflection coefficients and anisotropic AVO analysis
  • Effective medium theories and fracture characterization

Learner Outcomes (I):

  1. Use appropriate parameterization for TI and orthorhombic models
  2. Apply linearized approximations to gain insight into anisotropic signatures
  3. Choose the most efficient method to model anisotropic wave propagation
  4. Recognize anisotropy-induced distortions in velocity analysis and imaging
  5. Evaluate the influence of anisotropy on kinematic and dynamic signatures

Learner Outcomes (II):

  1. Separate anisotropy and lateral velocity variation in NMO for layer-cake media
  2. Apply moveout and amplitude inversion to P-wave and multicomponent data
  3. Combine seismic data with borehole information to estimate TI parameters
  4. Predict the applicability of effective media theories for fracture models
  5. Use seismic attributes to characterize naturally fractured reservoirs

Instructor Biographies:
Ilya Tsvankin
Vladimir Grechka