


 Anisotropic tomography with rock physics constraints  

Next: Acknowledgement
Up: Li et al.: RP
Previous: Posterior Uncertainty Analysis
In this paper, we have proposed a new formulation to incorporate rock physics prior information with the anisotropic tomography. Two models were analyzed using this method, and the inversion results demonstrate the tradeoff among the parameters and the instability due to the huge nullspace when no prior information is included. Any estimation of the local crossparameter distribution (column weighting, diagonal covariance and full covariance) is helpful to stabilize the inversion and leads to a better representation of the subsurface. However, we should be careful in using too tight of a prior distribution when the lithology is uncertain, especially for areas where parameters are not wellconstrained by the data. The posterior distribution analysis shows that by adding the rock physics prior information, we will obtain a better estimation of the true prior statistics in the inversion and a smaller uncertainty in the posterior statistics.
The experiment of rock physics constrained tomography suggests to us a new workflow in anisotropic model building.
 First, Build an initial model using the deterministic rock physics modeling and obtain the initial image.
 Second, Build the pointbypoint crossparameter covariance according to the stochastic rock physics modeling.
Build the spatial covariance using geology information and/or the initial image.
 Third, run the rock physics constrained joint tomography with surface seismic data and borehole data.
Repeat the workflow if necessary. Up to now, it is possible to use all the information: surface reflection seismic, borehole data, geological estimation and the rock physics covariance in the tomography to produce a unique earth model that explains the seismic data and satisfies the geological and rock physics theory at the same time.



 Anisotropic tomography with rock physics constraints  

Next: Acknowledgement
Up: Li et al.: RP
Previous: Posterior Uncertainty Analysis
20110524