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Magnetotelluric Detection Thresholds as a Function of Leakage Plume Depth, TDS and Volume

Technical Report ·
DOI:https://doi.org/10.2172/1357405· OSTI ID:1357405
 [1];  [1];  [1];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
We conducted a synthetic magnetotelluric (MT) data analysis to establish a set of specific thresholds of plume depth, TDS concentration and volume for detection of brine and CO2 leakage from legacy wells into shallow aquifers in support of Strategic Monitoring Subtask 4.1 of the US DOE National Risk Assessment Partnership (NRAP Phase II), which is to develop geophysical forward modeling tools. 900 synthetic MT data sets span 9 plume depths, 10 TDS concentrations and 10 plume volumes. The monitoring protocol consisted of 10 MT stations in a 2×5 grid laid out along the flow direction. We model the MT response in the audio frequency range of 1 Hz to 10 kHz with a 50 Ωm baseline resistivity and the maximum depth up to 2000 m. Scatter plots show the MT detection thresholds for a trio of plume depth, TDS concentration and volume. Plumes with a large volume and high TDS located at a shallow depth produce a strong MT signal. We demonstrate that the MT method with surface based sensors can detect a brine and CO2 plume so long as the plume depth, TDS concentration and volume are above the thresholds. However, it is unlikely to detect a plume at a depth larger than 1000 m with the change of TDS concentration smaller than 10%. Simulated aquifer impact data based on the Kimberlina site provides a more realistic view of the leakage plume distribution than rectangular synthetic plumes in this sensitivity study, and it will be used to estimate MT responses over simulated brine and CO2 plumes and to evaluate the leakage detectability. Integration of the simulated aquifer impact data and the MT method into the NRAP DREAM tool may provide an optimized MT survey configuration for MT data collection. This study presents a viable approach for sensitivity study of geophysical monitoring methods for leakage detection. The results come in handy for rapid assessment of leakage detectability.
Research Organization:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC52-07NA27344
OSTI ID:
1357405
Report Number(s):
LLNL--TR-729937
Country of Publication:
United States
Language:
English

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