In standard supervised machine learning approaches, the seismic-to-rock property relationship is learned using available data. These methods, particularly deep learning, depend on having enough labeled data to adequately train the neural network. WellGen overcomes this challenge by generating synthetic data, simulating many pseudo-wells based on existing well statistics and rock physics modeling.
WellGen addresses common machine learning challenges, including:
AVO is a comprehensive HampsonRussell module for pre-stack data conditioning, attribute computation and analysis. This module has the tools for conditioning pre-stack seismic data to produce optimum attribute volumes, cross-plotting and interpretation functions for locating AVO anomalies, and AVO modeling tools for calibration. Customizable workflows and the integration of AVO tools into the Geoview interface make sophisticated AVO analysis simple.
Benefits of HampsonRussell AVO:
Strata performs both post-stack and pre-stack inversions. In the conventional post-stack domain, Strata analyzes post-stack seismic volumes to produce an acoustic impedance volume. In the pre-stack domain, Strata analyzes angle gathers or angle stacks to produce volumes of acoustic impedance, shear impedance and density.
Benefits of Strata:
Emerge is a geostatistical, attribute prediction module that can predict property volumes using well logs and attributes from seismic data. The predicted properties can be any log types available, such as porosity, velocity, density, gamma-ray, lithology and water saturation. Emerge can also be used to predict missing logs or parts of logs by using existing logs that are common to the available wells with deep learning and deep-feed neural network (DFNN) techniques.
Benefits of Emerge:
GeoSI is a geostatistical (single stack and multiple stack) inversion application that generates high-frequency stochastic models for high-resolution reservoir characterization and uncertainty analysis. It addresses the band-limited nature of deterministic inversion methods and integrates well data and seismic data at a fine scale within a stratigraphic geomodel framework.
Benefits of GeoSI:
ProAZ maps fractures and predicts stress by observing azimuthal variations in the P-wave seismic data. Pre-stack azimuthally processed seismic data are analyzed in terms of time and amplitude azimuthal variations attributed to anisotropic effects. ProAZ provides a series of tools to enable interpreters to interactively explore for azimuthal variations in their datasets and generate azimuthal attributes to summarize the results.
Benefits of ProAZ: