Bayesian Linear Inversion

LTrace Bayesian Linear Inversion (BLI) provides a deterministic elastic seismic inversion using the linearized Bayesian methodology for estimating velocities or impedances and density (maximum a posteriori solution of the Bayesian posterior distribution). We use angle stacked seismic data – such as near, mid and far – along with low frequency models to quickly perform the inversion. The results are comparable to a constrained sparse spike inversion but are obtained 6x to 10x faster. The software implements an approximation on the horizontal continuity model, allowing the user to impose lateral correlation on the results with a low overhead.

OpendTect BLI Webinar – 07/08/2020

Theoretical concepts

Using the convolutional seismic modeling and under the Gaussian assumption for the seismic errors and the prior distribution of the elastic properties, the Basyesian posterior distribution is analytically calculated:

The methodology is based on (Buland, A. & Omre, H., 2003) with some particularities. The prior distribution of elastic properties includes the property correlations, low frequency models and 3 dimensional spatial correlation models. We developed the software as a plugin for OpendTect, an open source platform used throughout the industry. We have employed the latest GPU-based libraries for extreme parallelism and acceleration, therefore, if the user has an NVIDIA® GPU, the process will run on it using only 10 to 20% of the time compared to running the inversion on CPU.


  • Deterministic elastic inversion for estimating Velocities or Impedances and Density.
  • Runs 6x to 10x faster than a Constrained Sparse Spike inversion.
  • Horizontal correlation.
  • Quality Control (QC) for comparing the inversion results with well log data and iterative parameters adjustment.
  • Accelerated by CUDA on NVIDIA® GPUs.

Check out our plugin at the: