LTrace Inversion Suite

By providing efficient solutions for estimating elastic properties like velocities, impedances, and density, it enables users to derive meaningful insights from seismic data with enhanced precision and speed, supporting informed decision-making in subsurface analysis.

Features:

• Analytical acoustic and elastic inversion for estimating Velocities or Impedances and Density.
• Runs 6x to 10x faster than a Constrained Sparse Spike inversion. Accelerated by CUDA on NVIDIA® GPUs.
• A new AVO formulation integrated into the BLI framework, based on cutting-edge work by de Figueiredo & Grana, as featured in SEG Geophysics and EAGE presentations.
• Direct Inversion to Key Properties – Enables direct inversion to P-impedance and Vp/Vs, a common domain for facies classification, potentially improving prediction accuracy.
• Multi-trace, multi-well wavelet estimation
• Low-frequency modeling module
• A new QC interface for validating inversion results against well data

The suite includes advanced features such as elastic and acoustic inversion, multi-well-trace wavelet estimation, which generates accurate wavelets from seismic and well log data, and low-frequency modeling that interpolates trends using 3D horizons. The elastic and acoustic inversion modules leverage GPU acceleration for rapid processing—delivering results 6x to 10x faster than traditional methods— yielding close to real time results for 2D sections. A dedicated QC interface allows iterative parameter adjustments, ensuring robust comparisons with well logs.

The elastic and acoustic inversion are based on the Bayesian Linearized Inversion approach, based on Buland and Omre (2003), alongside innovative AVO formulations for better facies classification, based on de Figueiredo and Grana (2025) and Grana et. al. (2025). More technical details on the methodology can be found in our technical documentation. 

We provide a demo dataset based on F3_demo, the details of how to download it are at the end of this manual. Please, use the following sections as reference for both the acoustic and elastic inversion plugins, as they are based on the same methodology.

Check out our plugin at the OpendTect Pro Store
Get the demo dataset here

 

QC interface for validating inversion results against well data

 

Multi trace wavelet

This module provides an interactive interface accurately define the energy phase and energy, based on the statistical analysis of multiple seismic traces and wells. For a given radius around the wells, the software computes the best time shift for each trace that provides the maximum correlation with the synthetics.

• Statistical analysis of multiple traces around multiple wells
• Interactive interface to select the traces to be used
• Phase tuning: define the best wavelet phase based on the selected traces
• Energy tuning: for the given phase, define the best energy value based on the selected traces

 

Low frequency modeling

The Low Frequency Modeling tool provides an interface for modeling volumes from existing well data and a stratigraphic grid defined through multiple horizons. These volumes can then be used as input trend data for the inversion plugins.

Key features include:
🔹Multiple interpolation options: Proportional, Parallel to Top, Parallel to Bottom, and Parallel to Center.
🔹A single Z Interpolation Range parameter to control vertical distance influence using Gaussian interpolation.
🔹2D Line output for quick visualization before generating a full 3D cube.

 

Acoustic inversion

Absolute Acoustic Impedance remains a cornerstone of modern seismic interpretation projects. It enables interpreting layer properties without distortions caused by tuning effects. LTrace Acoustic Bayesian Linear Inversion provides a analytical acoustic seismic inversion using the linearized Bayesian methodology for estimating acoustic impedance from seismic data. The input data are the full stack seismic data, the wavelet and the low frequency model of acoustic inversion.

 

Elastic inversion

LTrace Bayesian Linear Inversion provides a analytical elastic seismic inversion using the linearized Bayesian methodology for estimating velocities or impedances and density. We use angle stacked seismic data – such as near, mid and far – along with low frequency models to quickly perform the inversion.

For the elastic inversion, the software uses the latest Graphics Processing Unit (GPU) technologies to accelerate the inversion processing. If the user has an NVIDIA® GPU, the inversion will be automatically processed using it. Using GPUs provides a performance gain over CPUs of 4 to 7 times in our benchmarks, depending on the model of the GPU and the vertical gate selected at the inversion.

 

Theoretical concepts

The methodology is based on (Buland, A. & Omre, H., 2003) with some particularities. Using the convolutional seismic modeling and under the Gaussian assumption for the seismic errors and for the prior distribution of the elastic properties, the Bayesian posterior distribution is analytically calculated.  

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.

 

 

OpendTect BLI Webinar

 

 

Video tutorials

Main references

• Buland, A., & Omre, H. (2003). Bayesian linearized AVO inversion. Geophysics, 68(1), 185–198. 
• De Figueiredo, L., & Grana, D. (2025). Two-Term and Three-Term AVO Approximation for Facies Classification. 86th EAGE Annual Conference & Exhibition, 2025, 1–5. 
• Grana, D., de Figueiredo, L., Paparozzi, E., & Ravasio, A. (2025). Hierarchical Bayesian AVO facies inversion using IP and VP/VS parameterization. Geophysics, 90(4).