SKUA-GOCAD Reservoir Properties

Construct robust, geologically consistent reservoir models.

Porosity model
 
The Paradigm® SKUA-GOCAD Reservoir Properties application contains a flexible and dynamic workflow for populating reservoir grids. It offers an extensive suite of geostatistical algorithms for spatially interpolating (mapping), and stochastically simulating geological facies (or any discrete variables) and petrophysical properties, such as porosity and permeability (or any continuous variables).

A post-processing workflow provides tools for summarizing and analyzing simulation results, together with decision-making support tools such as volumetric map computation and connectivity analysis.

Reservoir Properties benefits:

 
  • Comprehensive suite of algorithms to reproduce your geological vision of the reservoir
  • Integration of multiple sources of data to constrain your reservoir model
  • Flexibility to capture your reservoir’s non-stationarity
  • Easy-to-use workflow that ensures repeatability, smooth project transfer, and audit trail.
  • More accurate and reliable models that promote a better understanding of reservoir architecture and connectivity for evaluating in-place resources and forecasting production, resulting in optimized development plans.

Reservoir Properties features:

  • A dynamic workflow guides users systematically through an interactive sequence of steps in which parameters are requested as needed. The workflow enables easy scenario management, flexible sensitivity analysis, quick model updates, and contextual note taking, including snapshots.
  • Geostatistical algorithms: A large number of industry-proven geostatistical algorithms are provided for interpolation and stochastic simulation.
  • Multiple constraints: The Reservoir Properties application offers a variety of options to easily incorporate multiple secondary data, resulting in realistic, constrained reservoir models.
  • Customizable algorithm combinations: A user-defined sequence of modeling steps allows users to combine fit-for-purpose algorithms.
  • Flexible parameter specification: All parameters can be specified as spatially varying to account for geological non-stationarity.
  • Post-processing: Users can summarize and extract relevant information from multiple realizations of the reservoir model, and infer threshold probabilities and other decision-supporting statistics or metrics.