Details
| Original language | English |
|---|---|
| Pages (from-to) | JM65-JM75 |
| Journal | GEOPHYSICS |
| Volume | 83 |
| Issue number | 6 |
| Publication status | Published - 1 Nov 2018 |
| Externally published | Yes |
Abstract
Surface nuclear magnetic resonance is a valuable technique that provides insight into the distribution of water content and relaxation time, thus revealing hydraulic properties in the subsurface. Recent research has introduced a new measurement layout that allows for time-efficient imaging of the 2D parameter distribution. Furthermore, for 1D investigations, it has been verified that complex data can provide improved resolution and depth penetration. In our research, we have developed an inverse modeling algorithm based on the QT-inversion scheme that uses the 2D complex magnetic resonance tomography data. We evaluate the uses and limitations of complex data for 2D investigations. By comparing resolution measures, we test this algorithm against state-of-the-art amplitude-based inverse modeling using resolution measures, a rigorous synthetic test, and a field example. Finally, we assess the impact of unknown conductivity and off-resonance excitation on the subsurface image and examined their limitations in field applications. We find that complex inversion is feasible in practice and provides superior results but demands precise knowledge of the true excitation frequency.
Keywords
- Hydrogeophysics, Inversion, Modeling, Surface nmr
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)
- Geochemistry and Petrology
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In: GEOPHYSICS, Vol. 83, No. 6, 01.11.2018, p. JM65-JM75.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Two-dimensional QT inversion of complex magnetic resonance tomography data
AU - Jiang, Chuandong
AU - Müller-Petke, Mike
AU - Wang, Qi
AU - Igel, Jan
N1 - Funding information: We thank R. Dlugosch and R. Meyer for acquiring the MRT data and D. Epping for assisting the GPR measurements. C. Jiang and Q. Wang were supported by the Natural Science Foundation of China (41604083 and 41704103) and the International Postdoctoral Exchange Fellowship Program (20160057).
PY - 2018/11/1
Y1 - 2018/11/1
N2 - Surface nuclear magnetic resonance is a valuable technique that provides insight into the distribution of water content and relaxation time, thus revealing hydraulic properties in the subsurface. Recent research has introduced a new measurement layout that allows for time-efficient imaging of the 2D parameter distribution. Furthermore, for 1D investigations, it has been verified that complex data can provide improved resolution and depth penetration. In our research, we have developed an inverse modeling algorithm based on the QT-inversion scheme that uses the 2D complex magnetic resonance tomography data. We evaluate the uses and limitations of complex data for 2D investigations. By comparing resolution measures, we test this algorithm against state-of-the-art amplitude-based inverse modeling using resolution measures, a rigorous synthetic test, and a field example. Finally, we assess the impact of unknown conductivity and off-resonance excitation on the subsurface image and examined their limitations in field applications. We find that complex inversion is feasible in practice and provides superior results but demands precise knowledge of the true excitation frequency.
AB - Surface nuclear magnetic resonance is a valuable technique that provides insight into the distribution of water content and relaxation time, thus revealing hydraulic properties in the subsurface. Recent research has introduced a new measurement layout that allows for time-efficient imaging of the 2D parameter distribution. Furthermore, for 1D investigations, it has been verified that complex data can provide improved resolution and depth penetration. In our research, we have developed an inverse modeling algorithm based on the QT-inversion scheme that uses the 2D complex magnetic resonance tomography data. We evaluate the uses and limitations of complex data for 2D investigations. By comparing resolution measures, we test this algorithm against state-of-the-art amplitude-based inverse modeling using resolution measures, a rigorous synthetic test, and a field example. Finally, we assess the impact of unknown conductivity and off-resonance excitation on the subsurface image and examined their limitations in field applications. We find that complex inversion is feasible in practice and provides superior results but demands precise knowledge of the true excitation frequency.
KW - Hydrogeophysics
KW - Inversion
KW - Modeling
KW - Surface nmr
UR - http://www.scopus.com/inward/record.url?scp=85055532047&partnerID=8YFLogxK
U2 - 10.1190/geo2017-0756.1
DO - 10.1190/geo2017-0756.1
M3 - Article
AN - SCOPUS:85055532047
VL - 83
SP - JM65-JM75
JO - GEOPHYSICS
JF - GEOPHYSICS
SN - 0016-8033
IS - 6
ER -