Instrumentation and Data Management/Analyses for Measurement While Drilling Technology

Status:  Active
Project Start Date:  12/14/2023


The design and construction of any foundation require sufficient and reliable information about subsurface conditions. Availability and accuracy of such information are key parameters for the successful planning, design, construction, and operation of many engineering projects including transportation infrastructure. Obtaining such sufficient and reliable in-situ geologic substrate data and characterizing the subsurface conditions for engineering design purposes, however, has always been a challenge to the natural resources and civil engineering industries. Recently, Measurement While Drilling (MWD) technology has shown a lot of potential for improving subsurface characterization. Therefore, obtaining, organizing, and interpreting the MWD data is of huge importance and urgency to DOTs as it can benefit the organization in several ways. For example, by improving the accuracy and consistency of subsurface data, MWD could significantly improve the design of transportation structures’ foundations, reduce the number of required subsurface exploration locations, and minimize delays and the number of change order requests, all of which leads to considerable cost savings. This project, therefore, aims to address the need for instrumentation as well as organization and interpretation of Measurement While Drilling (MWD) data for National Road Research Alliance (NRRA) State Members. To achieve these goals, Nebraska DOT's Geoprobe 3230DT drill rig will be equipped with MWD sensors and a data acquisition system and only Nebraska DOT projects will be investigated at this stage. Drillers will be trained to collect MWD data during their projects. A web-based Geographic Information System (GIS) will be developed for efficient storage, preprocessing, and visualization of MWD data. The collected MWD data on NDOT’s projects over the duration of this project will be analyzed to establish correlations and predictive models linking MWD data to key geotechnical properties of subsurface layers.

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