3D Model-based Tomography
Update subsurface velocity and anisotropic material parameters, and depth of structural horizons, along the structural model.
In 3D model-based tomography, velocity parameters are represented along the depth model horizons. The velocity parameters and the depth structure are updated along the background structural model. Unlike grid-based tomography
, in which only the velocity parameters are updated on a predefined coarse 3D grid, model-based tomography updates both the velocity field along the geological layers and the location of subsurface horizons.
The number of parameters to be inverted in model-based tomography is generally much fewer than in grid-based tomography. Therefore, there is no need for direct model-based tomography.
Model-based Tomography advantages:
It is easier to enforce geologically constrained solutions in Model-based Tomography because of its irregular inversion grid which follows the geological layers.
Model-based Tomography can handle thickness varying layers, and especially thin layers, without calculating very large matrixes.
Re-depthing using time-preserving tomography systematically reduces depth seismic-to-well marker mis-ties
Velocity before and after time-preserving tomography. After tomography, fine shale layer is revealed in the model.
Time Preserving Tomography is an efficient and accurate application for simulating different scenarios of isotropic/anisotropic velocity-depth models which are consistent with a given background model and with the seismic data. This new solution is an expansion of Paradigm grid-based well tie tomography, where in addition to mis-ties, the input can include all types of anisotropic velocity parameters (e.g., axial velocity, and Thomsen delta and epsilon parameters). This is a useful tool for both depth imagers and interpreters. During depth imaging, it enables the user to set external structural and stratigraphic geological constraints and to extend the description of the anisotropic model in a consistent manner. Interpreters can simulate many "legal" model scenarios which can also help in uncertainty and risk analysis.