PAT is an integrated passive seismic tomography package for inverting P- and S-wave travel times for 3-D velocity and Poisson’s structure and micro earthquake locations. It uses an algorithm based on adaptive grid. The procedure of the data analysis is depicted in the following flow chart.

The PST inversion algorithm

The most critical part of any Passive Seismic Tomography (PST) survey is the algorithm that is used to invert the arrival times of the P- and S- seismic phases to reliable geological models. LandTech engineers have recently developed a new revolutionary inversion algorithm (PAT) that incorporates new ray tracers, the required for the 3D inversion initial model using seismic interferometry, seismic array processing and an expert system mechanism which increases the resolution by an order of magnitude.

PAT uses a user-friendly interface that is common in all the steps of the processing, from the initial model design to the final plots of the 3D tomographic results.

  • The most usual data formats are supported.
  • Data selection is performed by interactive tools and filters.
  • Interactive design of initial tomography model.
  • Tools for calculating the 1D minimum velocity model for use as initial model.
  • Automatic Vp/Vs ratio calculation.
  • An automatic parametrization system (adaptive grids) has been developed.
  • Ray coverage and solution stability were taken into account for the automatic and optimal grid geometry design.
  • Checkerboard testing.
  • Synthetic anomalies resembling the geophysical targets can be interactively created and thoroughly tested.
  • A highly interactive graphical interface can present in 3D perspective view all the structures estimated by the software.
Interactive interface permits the prospective view of the velocity volume calculated together with the hypocentres.
The existence of interactive tools for selecting the well-located data and the interactive design of the best velocity model speed up the operation of the program permitting multiple trials and the best selections of the parameters.
Ray coverage and solution stability were considered for the automatic and optimal grid geometry design. Checkerboard test performed by the algorithm.

The software can present all the volume of interest in a a 3D view

A new revolutionary geostatistical methodology based on Kohonen neural networks and PST data attributes. This is used to derive lithological information of a region where a PST survey has been conducted. These attributes are Vp, Vs, Poisson’s and the attenuation quality factor Qp. The use of unsupervised artificial Kohonen neural networks and Self Organizing Maps (SOM) algorithms in passive seismic data analysis prove to be a useful tool for delineating the structural and lithological properties of the subsurface.
PAT incorporates processing modules based on Kohonen neural networks