14
*STTR
Project: Imaging the Stratigraphy Around a CPT
Penetration Using a Combined ERT and CPT
Method—Vista Engineering
Technologies, LLC, 8203 W. Quinault, Building C,
Suite 200, Kennewick, WA 99336;
509-737-1377; http://www.vistaengr.com
Dr. Wesley L. Bratton, Principal
Investigator, bratton@vistaengr.com
Mr. Phillip C. Ohl,
Business Official, ohl@vistaengr.com
DOE Grant No. DE-FG02-06ER86292
Amount:
$664,327
Research
Institution
Improved technologies are needed to measure key factors that affect mass-transport rates in the shallow subsurface at large scales. Mass-transport parameters are important at large scales because the flow and transport occurs on such scales. Although many technologies can make discrete point measurements of key parameters, few are able to expand and assess those parameters on a larger scale or provide maps of those parameters in a cross-section. This project will develop, evaluate, and demonstrate a commercially viable method for mapping the stratigraphy of the subsurface around cone penetrometer (CPT) penetrations. The approach will combine the point measurement capabilities of the CPT with the mapping potential of Electrical Resistance Tomography (ERT) so that key mass-transport parameters can be assessed. Numerical modeling computations and laboratory tests conducted during Phase I demonstrated that sufficient resolution could be obtained. In Phase II, additional numerical modeling will be performed to optimize the probe electrode spacing and measurement strategy. The goal is to optimize the number of unique measurements such that sufficient data is provided for the image inversion process. A CPT probe with 3 to 5 electrodes will be designed to both transmit electrical current and measure the electrical potential. The probe will be used in field tests to map the stratigraphy at a well-characterized site.
Commercial Applications and Other Benefits as described by the awardee: The combined ERT-CPT approach should permit real-time mapping of the subsurface stratigraphy and provide a much improved image of the subsurface, thereby significantly improving the reliability of flow and transport models.