Using VSP for Groundwater Monitoring Program Optimization
ASP Workshop
Charleston, SC
September 16, 2015
Alex Mikszewski, PEAmec Foster Wheeler
Introduction
2
Long-Term Groundwater Monitoring
Increasing percentage of sites at this stage
Can be significant annual spend >$100k
VSP 7: Identify Sampling Redundancy Module
Temporal: Iterative Thinning, Variogram Analysis
Spatial: Kriging Analysis
VSP Input
3
Time-series data
>10 observations
Time gaps/outliers
Well coordinates
Discrete time period analysis for spatial optimization
Vertical layering considerations
VSP Temporal Optimization
4
Iterative Thinning
Identify sampling frequency to reproduce temporal trend
Iterative process: remove points, re-evaluate trend compliance
Single-well Variogram
Identify minimum temporal spacing for event independence
Sample no more frequently than range of correlation
PNNL, 2014
VSP Iterative Thinning Example
7
Approved reduction to annual monitoring
Combined with spatial optimization leads to annual savings of >$30k
Optimal Monitoring Spacing (Days)
Well Arsenic Manganese Well Screened ZoneMW-1 367 367 OverburdenMW-2 457 610 OverburdenMW-3 457 457 Overburden/BedrockMW-4 608 456 OverburdenMW-5 374 374 OverburdenMW-6 455 364 OverburdenMW-7 457 610 OverburdenMW-8 366 366 Overburden/BedrockMW-9 457 332 Bedrock
MW-10 537 537 Overburden
Minimum years 1.0 0.9Maximum years 1.7 1.7Average years 1.2 1.2
VSP Spatial Optimization
9
Based on kriging root-mean-square-error (RMSE)
Wells ranked in value based on RMSE contribution
Optimization concept: leave enough wells to maintain
accurate kriging of the plume
PNNL, 2014
Monitoring & Remediation Optimization System (MAROS)
13
Individual Well Concentration Trends Mann-Kendall Regression
Spatial Moment Analysis Total plume mass Center & spread of plume mass Trends
Sampling Network Optimization Well redundancy/sufficiency Monitoring frequency analysis
How MAROS Spatial Optimization Works
17
Calculate Slope Factor (Measured vs. Estimated)
Delaunay Triangulation
0 to 1, 0 = no information provided by well
Calculate Average Concentration & Triangulation Area Ratios
Iterative Optimization
Remove low slope factor wells
Check ratios
MAROS thresholds
How MAROS Temporal Optimization Works
18
Individual Well Frequency
Cost Effective Sampling (CES) Method
Rate of Change of Constituents at Wells (Trends, Variability)
Network-Level Frequency
Based on Zeroeth Moment (Total Plume Mass) COV
Higher Plume Mass Variability = More Sampling
User thresholds
VSP vs. MAROS
20
VSP Pros
Transparency & ease of use
Geostatistical foundation for spatial optimization
Intuitive iterative thinning algorithm
MAROS Pros
Spatial moment quantification & trending
Network-level optimization based on zeroeth moment
Option to evaluate new well locations