Rock Mechanics

Minimize Risk And Improve Efficiencies In All Phases Of The Reservoir Lifecycle

Minimize Risk, Improve Efficiencies.

Rock Mechanics data is fundamental to reservoir characterization and optimization. From exploration and well planning through abandonment, a thorough and relevant understanding of the reservoir environment allows operators the opportunity to make beneficial decisions to minimize risk while enhancing economic and operational productivity.

Premier Corex's Specialized Core Prep Technique Ensures Sample Quality, Integrity, and Maintains ASTM Standards.

  • Allows sample extraction in difficult/challenging core otherwise not usable for testing

  • Proven method that minimizes lost material, lost time and induced damage to material

  • Verified with pre and post CT

  • Sample quality and integrity are paramount to effective testing and representative results

World Class People, Equipment and Capabilities

Our geochemistry workflows and unique instrument calibrations allow us to lead the industry in speed and accuracy.

  • Our lab professionals have an extensive and unique blend of experience in both commercial and R&D laboratories

  • Multiple load frames to ensure continued workflow. Sample sizes form 0.75” to 1.5” diameter

  • Anisotropic static and dynamic measurements in-situ

  • Flexible testing capabilities from basic UCS/TXC type testing to research and advanced testing types

Demonstrable Quality

  • Stringent quality assurance ensures highest levels of data confidence

  • Traceable calibrations, standardized processes and procedures, and regular system validations demonstrate reproducibility

The professionals at Premier Corex have decades of experience in Rock Mechanics testing, analysis and application. Rock Mechanics can be used as stand-alone data, or within our comprehensive process combining other results from Routine and Special Core Analysis, XRF, XRD, reservoir modeling, petrophysical and existing well log data to build extremely robust and predictive geomechanical models.

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