Putting High-Resolution Data to Work: Targeted Conventional and Multi-Level Monitoring Well Design
Date and Time: Wed, November 18, 2020, 12:15 PM - 2:30 PM
Presenters: Mark A. Higgins
, M.S., Ph.D. Candidate, Department of Geosciences, University of Connecticut
Robert J. Stuetzle, M.A.Sc., P.Geo., Environmental Remediation Manager and Hydrogeologist, Dow Chemical Company
Continuing Education Credits:
This is the first time this course is being offered by EPOC. The CT State Board of Examiners of Environmental Professionals (LEP Board) has approved this course/webinar for 2.0 hours of continuing education credits (CTLEP-505W).
- EPOC Members: $100
- Non-members: $200 (consider joining EPOC at this time to receive the member rate for this program)
- Gov't Employee/Students: $50
Advances in high resolution data collection have improved our ability to characterize the subsurface at a point in time, but remediation sites often require temporal data to provide a measure of remedial progress and to fulfill regulatory requirements. This course provides an overview of the state-of-the-art in data collection and groundwater monitoring methodologies and demonstrates how to use those high-resolution datasets to develop an effective monitoring network through an interactive exercise.
This course will begin with an overview of standard well-completion practices and some associated issues that often go overlooked. Next, the course will provide a comprehensive review and comparison of contemporary data collection methods including various drilling, direct push, and down hole testing techniques. Then, monitoring well design and completion methods which utilize those datasets will be discussed. Finally, a high-resolution site characterization and monitoring well design exercise will take place, in which all of the course content will be incorporated into an interactive activity.
Course participants will learn about high resolution data collection methods that will improve their site characterization approaches. They will learn how to effectively implement these datasets to design monitoring well networks that produce the most reliable information. Participants will also learn about when each of these tools are appropriate to site conditions and their limitations.
- 12:15 PM: Login to GoToWebinar Platform
- 12:30 - 12:40: Introduction
- 12:40 – 1:00: Monitoring Wells
- 1:00 – 1:25: Characterization – An Overview of Data Collection Methods
- 1:25 – 1:40: Monitoring Well Design and Completion
- 1:40 – 2:20: Applying Characterization Data to Build an Effective Monitoring Network (Exercise)
- 2:20 – 2:30: Discussion
Mark A. Higgins, M.S., Ph.D. Candidate, Department of Geosciences, University of Connecticut
Mark is currently a Ph.D. Candidate under Gary Robbins in the Department of Geosciences at the University of Connecticut. Prior to pursuing his Ph.D. in 2017, he spent six years working for Flexible Liner Underground Technologies (FLUTe). As the East Coast Field Manager, he focused on novel high-resolution downhole flow profiling methods and multi-level sampling systems design and implementation. Mark’s former work involved environmental site characterizations across the USA, Canada, Caribbean, and Europe. His current research involves investigating arsenic and road salt contamination issues Connecticut soil and groundwater, implementing bacteria as novel groundwater tracers, and developing analytical models to improve groundwater sampling practices.
Robert J. Stuetzle, M.A.Sc., P.Geo.
Robert J. Stuetzle is a Contaminant Hydrogeologist at The Dow Chemical Company. His area of expertise is in understanding subsurface processes for effective site characterization, remedial design and performance monitoring. He earned his M.A.Sc in Water Resources Engineering supervised by Dr. Beth Parker and Dr. John Cherry, from the University of Guelph and a B.Sc. in Science and Business: Hydrogeology Specialization from the University of Waterloo. He has over a decade of experience in his field and is a registered Professional Geoscientist (P.Geo.) in Ontario, Canada.