National Science Foundation STTR Phase I

Real-Time Ground Model Updating Reduces Risk and Uncertainty in Construction

Emprise Concepts, LLC, in collaboration with the Colorado School of Mines, is developing an innovative software-based framework to update geological and geotechnical ground models in real time during underground construction and tunneling projects. The Phase I effort focuses on developing and testing algorithms that integrate geotechnical instrumentation, monitoring data, construction equipment sensors, existing infrastructure information, and a priori geostatistical models. The proposed technology directly addresses a long-standing industry challenge by transforming construction data into actionable, real-time insights.

Project Scope:	Research and development of a computational software platform to dynamically update geological and geotechnical ground models
Unique Features:	Real-time integration of construction, monitoring, and instrumentation data, Automated geotechnical backanalysis and parameter inversion
Our Services:	Applied research and development, geostatistical modeling, backanalysis algorithm development, risk modeling, and commercialization planning
Emprise Personnel:	Jacob Grasmick Noah Kimmes

Impact & Benefits

• Reduced Construction Risk: Real-time ground model updating improves understanding of subsurface conditions as excavation progresses.

• Improved Decision-Making: Automated backanalysis provides timely insights to support construction and risk management decisions.

• Cost and Schedule Savings: Early identification of changing ground conditions helps reduce delays, redesigns, and mitigation costs.

Scalable Commercial Technology: Software-based solution supports deployment across a wide range of underground projects.

Project Gallery

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Project Summary

Emprise Concepts, LLC, in collaboration with the Colorado School of Mines, is developing an innovative software-based framework to update geological and geotechnical ground models in real time during underground construction and tunneling projects. The Phase I effort focuses on developing and testing algorithms that integrate geotechnical instrumentation, monitoring data, construction equipment sensors, existing infrastructure information, and a priori geostatistical models. Reducing uncertainty during construction has the potential to significantly lower project risk, minimize delays, and reduce cost overruns. The proposed technology directly addresses a long-standing industry challenge by transforming construction data into actionable, real-time insights.

Project Writeup

The Phase I project evaluates the technical feasibility and commercial potential of a real-time ground model updating platform designed to automate geotechnical backanalysis and risk assessment during underground construction. The research approach integrates multiple data sources into a common digital environment, beginning with a priori data such as borehole investigations, BIM models, and elevation data to establish an initial digital twin. During construction, geotechnical and structural monitoring data, mechanical sensor outputs from construction equipment, and observational data are incorporated. Advanced analytics are applied to invert key geotechnical parameters. These results are assimilated into a probabilistic geostatistical framework using Bayesian inference, producing continuously updated ground models. The evolving models are translated into real-time risk metrics relevant to underground construction, such as ground deformation and interaction with adjacent structures. By automating backanalysis and updating ground models as construction progresses, the platform enables faster, more informed decision-making with minimal additional labor. The technology supports safer, more economical, and more sustainable underground construction and represents a viable commercial opportunity through software licensing and professional services.