Classifying lithologies and facies is important to distinctly define rocks of interest and to build a better understanding of the depositional environments encountered in the wellbore.
Typical reservoir properties considered for lithology prediction are mineral composition, especially volume of sand and clay, porosity, fluid saturations and texture characteristics.
Petrophysical facies classification for seismic reservoir characterization workflows integrates log data with core or cuttings data and production data to define facies properties. Rock physics modeling establishes the elastic relationships between those rock properties and the seismic response.
With those relationships established, an integrated seismic inversion and classification workflow utilizing multi-dimensional probability density functions (PDFs) for each possible facies and a supervised Bayesian classification scheme generates probability cubes for the distribution of the different facies that have been defined with lithology and fluid properties.
This methodology, grounded with real-world petrophysical measurements, quantifies uncertainty in seismic lithology and facies prediction while providing a superior definition of the lithology classes.
The predicted facies and fluid volumes are the foundation for advanced earth modeling.
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Our Petrophysical workflows and Rock Physics modeling integrate log, core/cuttings and production data to obtain meaningful physical properties
Seismic inversion workflows customized for your reservoir characterization goals and backed by global expertise in clastic, carbonate and unconventional reservoirs
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