Contact
us

© 2018 by VertiShear, LLC Patents granted & pending. All rights reserved.

    VertiShear, LLC

    8760A Research Blvd Ste 500

    Austin, TX 78758

    ​​

    Tel: 512-910-8666

    info@vertishear.com

    DISCOVER HIDDEN RESERVES

    WITH COST-EFFECTIVE

    SHEAR WAVES

    ABOUT us

    VertiShear LLC was formed in 2011 to patent and commercialize a new seismic processing technology developed by Dr. Bob Hardage at The University of Texas’ Bureau of Economic Geology in Austin, Texas.

    VertiShear Technology makes it possible to extract hidden shear-wave seismic information from any vertical force source for both VSP and surface seismic studies, effectively breaking down the cost and time barriers currently limiting shear-wave data usage in the Oil & Gas industry.

     

    How Can

    shear waves

    Help You

    As the Oil & Gas Industry continues to explore higher-risk sources of hydrocarbons, multi-component seismic with shear wave analysis provides extremely valuable insights for drilling and production decisions.

     

    Lithology identification, fracture orientations, stress field characterizations, and fluid discrimination are all vital bits of information that become available when combining shear wave data with conventional p-wave data. However, existing methods for acquiring multi-component seismic data are very expensive and time consuming so many operators do not take advantage of this valuable data.

    VertiShear Technology unlocks hidden shear wave seismic images from legacy single component (1C) library data, and can expand three component (3C) data to become 9C data, all shot from a single vertical force source acquisition. Also, seismic acquisition teams can now obtain shear-wave rich data with dynamite and 1C geophones in the most challenging, remote environments such as swamps, marshes, or dense timber, thus allowing Oil & Gas Companies to dramatically improve their drilling decisions without incurring the traditional high costs for acquiring and processing multi-component data sets.