Details
| Original language | English |
|---|---|
| Pages (from-to) | JM51-JM63 |
| Journal | GEOPHYSICS |
| Volume | 83 |
| Issue number | 6 |
| Publication status | Published - 1 Nov 2018 |
| Externally published | Yes |
Abstract
Hydrologic parameters, such as porosity, salinity, and hydraulic conductivity are keys for understanding the subsurface. Hydrogeophysical investigations can lead to ambiguous results, particularly in the presence of clay and saltwater. A combination of magnetic resonance sounding and vertical electrical sounding is known to provide insight into these properties. Structural coupling increases the model resolution and reduces the ambiguity for both methods. Inversion schemes using block models exist, but they have trouble resolving smooth or complex parameter distributions. We have developed a structurally coupled cooperative inversion (SCCI) that works with smooth parameter distributions and is able to introduce blocky features through the exchange of structural information. The coupling adapts the smoothness constraint locally in connection to the model roughness to allow for sharper model boundaries. We investigate the performance of the SCCI using blocky and smooth synthetic models that depend on two controlling coupling parameters. A well-known field case is used to verify the results with drilling core and well logs. Varying the coupling parameters results in equivalent models covering the bandwidth from smooth to blocky, while providing a similar data fit. The SCCI results are more consistent with the synthetic models. Structural coupling improves the resolution of the single methods and can be used to describe hydrogeophysical targets in more detail and less ambiguously.
Keywords
- Algorithm, Electrical/resistivity, Inversion, Surface nuclear magnetic resonance
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. JM51-JM63.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Structurally coupled cooperative inversion of magnetic resonance with resistivity soundings
AU - Skibbe, Nico
AU - Günther, Thomas
AU - Müller-Petke, Mike
N1 - Publisher Copyright: © The Authors.
PY - 2018/11/1
Y1 - 2018/11/1
N2 - Hydrologic parameters, such as porosity, salinity, and hydraulic conductivity are keys for understanding the subsurface. Hydrogeophysical investigations can lead to ambiguous results, particularly in the presence of clay and saltwater. A combination of magnetic resonance sounding and vertical electrical sounding is known to provide insight into these properties. Structural coupling increases the model resolution and reduces the ambiguity for both methods. Inversion schemes using block models exist, but they have trouble resolving smooth or complex parameter distributions. We have developed a structurally coupled cooperative inversion (SCCI) that works with smooth parameter distributions and is able to introduce blocky features through the exchange of structural information. The coupling adapts the smoothness constraint locally in connection to the model roughness to allow for sharper model boundaries. We investigate the performance of the SCCI using blocky and smooth synthetic models that depend on two controlling coupling parameters. A well-known field case is used to verify the results with drilling core and well logs. Varying the coupling parameters results in equivalent models covering the bandwidth from smooth to blocky, while providing a similar data fit. The SCCI results are more consistent with the synthetic models. Structural coupling improves the resolution of the single methods and can be used to describe hydrogeophysical targets in more detail and less ambiguously.
AB - Hydrologic parameters, such as porosity, salinity, and hydraulic conductivity are keys for understanding the subsurface. Hydrogeophysical investigations can lead to ambiguous results, particularly in the presence of clay and saltwater. A combination of magnetic resonance sounding and vertical electrical sounding is known to provide insight into these properties. Structural coupling increases the model resolution and reduces the ambiguity for both methods. Inversion schemes using block models exist, but they have trouble resolving smooth or complex parameter distributions. We have developed a structurally coupled cooperative inversion (SCCI) that works with smooth parameter distributions and is able to introduce blocky features through the exchange of structural information. The coupling adapts the smoothness constraint locally in connection to the model roughness to allow for sharper model boundaries. We investigate the performance of the SCCI using blocky and smooth synthetic models that depend on two controlling coupling parameters. A well-known field case is used to verify the results with drilling core and well logs. Varying the coupling parameters results in equivalent models covering the bandwidth from smooth to blocky, while providing a similar data fit. The SCCI results are more consistent with the synthetic models. Structural coupling improves the resolution of the single methods and can be used to describe hydrogeophysical targets in more detail and less ambiguously.
KW - Algorithm
KW - Electrical/resistivity
KW - Inversion
KW - Surface nuclear magnetic resonance
UR - http://www.scopus.com/inward/record.url?scp=85054708537&partnerID=8YFLogxK
U2 - 10.1190/geo2018-0046.1
DO - 10.1190/geo2018-0046.1
M3 - Article
AN - SCOPUS:85054708537
VL - 83
SP - JM51-JM63
JO - GEOPHYSICS
JF - GEOPHYSICS
SN - 0016-8033
IS - 6
ER -