Formatted Title
When Life Gives You Lemonade, Make Lemons: How to Reverse Engineer Valid Geological Data from Analogs, Outcrops and Regional Geology in a Remediation Project
Background/Objectives
Geological constraints resulting from depositional environments of contaminated sites play a key role in developing optimal remediation strategies. This is because contamination mass-flux is largely a function of effective porosity and permeability of sediments, determined by the variability of sedimentary texture and geometry related to different depositional environments (e.g., fluvial, deltaic, alluvial fan, etc.). The ground truth for such approach is robust borehole geological data. However, often a significant challenge in the environmental industry remains in finding borehole geological data of good quality and appropriate spatial distribution necessary for stratigraphic correlations. This study explores ways to compensate for this lack of optimal site-specific geological data by gleaning information from the plethora of process analogs, outcrops, local geomorphology, and regional stratigraphic considerations and using that as valid proxy for site-specific correlation data.
Approach/Activities
Here several case examples from contaminated sites are considered, where the borehole geological data are insufficient and/or of low resolution for delineating site deposition environment to serve remediation purposes. At these sites, firstly, a thorough regional research was done in order to understand the general depositional setting. Secondly, any outcrop section or surface geomorphology (for shallow sites) close to the site area was investigated in detail for grain size trends, bed-dimensions etc. A combination of these information along with existing data resulted in picking appropriate facies models for the sites. Finally, stratigraphic correlations were conducted even through areas of borehole data gaps using appropriate width-thickness ratios of their facies elements.
Results/Lessons Learned
This “reverse-engineering” approach of harnessing the regional knowledge, aided by understanding of facies models in absence of new or better dataset can significantly enhance site investigation and remediation strategies.