CRAVA is a program for elastic inversion of seismic data. CRAVA is fast, can use zero-offset data, handles spatial dependence, calculates the uncertainty.


CRAVA is fast:

  • Ten million grid cells are processed in less than ten minutes.
  • Processing time is proportional to the size of the problem.

CRAVA can use zero-offset data:

Although CRAVA is intended for elastic inversion, it is also possible to use a zero-offset cube as input. The inverted results will then be the seismic impedance.

CRAVA handles spatial dependence:

  • Sedimentary rocks and their elastic properties have a strong spatial dependence. This is handled by CRAVA using spatial correlations (variograms) to model the elastic properties.
  • It is also known that seismic measurement errors often have spatial and temporal dependencies. This is due to processing techniques used for seismic data and from the spatial averaging in the stacking process. CRAVA takes this effect into account.

CRAVA calculates the uncertainty:

  • In addition to the inverted elastic properties, the variance of the inverted elastic properties and their internal spatial correlations are also calculated. The latter is important when determining the elastic properties of well observations.
  • The uncertainty in the result can be evaluated using stochastic simulation (Monte Carlo) of the cubes of elastic properties. How much the different cubes vary depends on the accuracy of the inversion.

CRAVA can add spatial structure for bandwidths lower than seismic resolution:

  • Seismic data are band-limited so small-scale variations are invisible during seismic surveys. Using stochastic simulation, CRAVA adds small-scale variations with correct spatial heterogeneity to the inverted cubes. This gives cubes that look realistic.


CRAVA kan lastes ned HER


The program calculates elastic properties such as density and P and S wave velocities from seismic amplitude cubes. Input data is amplitude data stacked at different angles and associated wavelets, and the result is 3D cubes of inverted elastic parameters. With CRAVA it is also possible to examine the accuracy of the results by calculating uncertainty, or by simulating (Monte Carlo) cubes of possible elastic properties.


The main function of CRAVA is elastic inversion. It is also possible to use CRAVA in estimation mode, where you can use Crava to estimate background model, wavelet or prior correlations. There is also a mode of forward modeling where one can generate seismic. Furthermore, CRAVA also contains facies predictions and a rock physics template.


CRAVA performs a seismic inversion here and returns the prediction or “most probable” elastic properties given data. The prediction is unique given the seismic data and the assumptions about the wavelet and the physical model.


In this mode, CRAVA will check input data and estimate what is missing to perform an inversion. What can be estimated are background model, wavelet and / or prior correlations.