Following a record five years of sustained production rates of over 97%, CGG Multi-Physics finished 2018 with a production rate for Marine GravMag of over 99% for the second year in a row. No serious injuries or incidents were recorded in 2018 and several clients recognised Multi-Physics field personnel with awards for their leadership and commitment to QHSE. CGG Multi-Physics is an ISO 9001 and OHSAS 18001 certified organisation renowned for dedication to quality, health, safety and environmental responsibility.
CGG Multi-Physics delivers the highest-quality marine gravity and magnetic data by evaluating field data on a daily basis to ensure the best possible performance, rigorously testing equipment before and after deployment, and using its industry-leading suite of LCT modelling software combined with exclusive processing techniques, and state-of-the-art in-house GIS capabilities. Field personnel receive ongoing, comprehensive training at its Houston, Texas facility and further development is provided through regular enrolment in courses offered by CGG University. CGG Multi-Physics works closely with clients during every phase of the project to ensure that final products are tailored to the exact specifications of the overall programme.
In addition to proprietary data acquisition and processing services, CGG Multi-Physics also houses the most comprehensive, privately-owned, multi-client potential fields geophysical database in the world. Data may be licensed for entire surveys or for specific areas of interest (AOI). The data libraries can be found in both the CGG GeoStore and ArcGIS Online.
Greg Paleolog, SVP, Multi-Physics, CGG, said: “Once again, CGG Multi-Physics has demonstrated its commitment to achieving an industry-high performance with these achievements in GravMag acquisition. GravMag data integration is the proven way to add to the bigger geoscience picture for a relatively small investment. It enhances the overall understanding of an area by providing information that allows for clearer differentiation and more confident modelling of geological formations and structures than with seismic data alone.”
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