Magnetic Resonance in the Subsurface – 5th International ... - LIAG

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2D qt-inversion to investigate spatial variations of hydraulic conductivity using SNMR 40 2D qt-inversion to investigate spatial variations of hydraulic conductivity using SNMR Raphael Dlugosch 1 , Thomas Günther, Mike Müller-Petke, and Ugur Yaramanci Leibniz Institute for Applied Geophysics (LIAG), Hannover 1 Raphael.Dlugosch@liag-hannover.de Surface-NMR is able to detect water content in the subsurface. Additionally, hydraulic conductivities can be estimated from NMR decay times (Legchenko et al. 2002, Dlugosch et al., 2011b). Both make SNMR a useful tool to answer hydrological questions. Most applications are 1D but SNMR has moved on to 2D targets (Hertrich et al., 2005; Hertrich et al., 2007) using comprehensive datasets while Girard et al. (2007) uses only coincident loops. The development of multi channel instrumentation made comprehensive 2D datasets time efficient (Dlugosch et al., 2011a). Current 2D inversions focus on estimating the water content distribution but do not invert for spatial information of relaxation time T2*. Thus, estimation of hydraulic conductivity is yet undone. We present the development a robust inversion to estimate a 2D distribution of T2*. Finally, this enables to image spatial variations in hydraulic conductivity from SNMR data with a high lateral resolution. The inversion is based on the qt-inversion scheme (Müller-Petke and Yaramanci, 2010). It exploits the full measured free induction decay data cube and increases both spatial resolution and stability of the inverse problem. By accounting for separate transmitter and receiver loops an increased lateral resolution is expected as shown by Hertrich et al. (2005). A challenging problem for a 2D inversion of water content and decay time is the size of the inverse problem both at the model and data domain. We use an irregular mesh and monoexponential decay per cell to minimize the number of free parameter in the model domain. In addition the FID data is gate integrated to minimize the size of the dataset (Behroozmand et al., 2012). We present first preliminary results of a synthetic dataset. References Behroozmand, A. A., Auken, E., Fiandaca, G., Christiansen, A. V. & Christensen, N. B. (2012): Efficient full decay inversion of MRS data with a stretched-exponential approximation of the distribution. Geophysical Journal International, Blackwell Publishing Ltd, 190 (2), 900-912. Dlugosch, R., Müller-Petke, M., Günther, T., Costabel, S. and Yaramanci, U., 2011a. Assessment of the Potential of a new Generation of surface NMR instruments, Near Surface Geophysics 9(2), 123-134. Dlugosch, R., Müller-Petke, M., Günther, T., Ronczka, M. and Yaramanci, U., 2011b. An extended model for predicting hydraulic conductivity from NMR measurements. – EAGE Near Surface 2011, 12,-14.09.2011; Leicester Girard, J.-F., Boucher, M., Legchenko, A. & Baltassat, J.-M. (2007): 2D magnetic resonance tomography applied to karstic conduit imaging. Journal of Applied Geophysics, 63 (3-4), 103-116. Hertrich, M., Braun, M., Yaramanci, U., 2005. Magnetic resonance soundings with separated transmitter and receiver loops, Near Surface Geophysics 3(3), 131-144. Hertrich, M., Braun, M., Günther, T., Green, A., Yaramanci, U., 2007. Surface Nuclear Magnetic Resonance Tomography, IEEE Transactions on Geoscience and remote sensing 45, 3752-3759. Legchenko, A., Baltassat, J.-M., Beauce, A., Bernard, J. (2002): Nuclear magnetic resonance as a geophysical tool for hydrogeologists. Journal of Applied Geophysics, 50 (1-2), 21-46. Müller-Petke, M., Yaramanci, U., 2010. QT inversion - Comprehensive use of the complete surface NMR data set, Geophysics 75, WA199 - WA209. Magnetic Resonance in the Subsurface – 5 th International Workshop on Magnetic Resonance Hannover, Germany, 25 – 27 September 2012
Locating a karst conduit with 2D Monte Carlo inversion of magnetic resonance measurements 41 Locating a karst conduit with 2D Monte Carlo inversion of magnetic resonance measurements Chevalier* A., A. Legchenko, M. Boucher UJF, IRD / LTHE, Grenoble, France Antoine.chevalier@ujf-grenoble.fr Assessing the ability of magnetic resonance measurement to reconstruct heterogeneous 2D and 3D water saturated formations by means of inversion algorithms is a recent issue for MRS applications (Hertrich et al. 2009; Legchenko et al 2011). Non-uniqueness of inversion results in conjunction with limited accuracy of measurements affected by electromagnetic noise may cause erroneous interpretations. The best way to deal with this issue is to compute a great number of water content distributions consistent with the data set, and to propose a probabilistic answer instead of a single solution using Monte Carlo approaches. (Mosegaard et al, 1995) The Poumeyssens site (southern France) was previously investigated with MRS (Boucher et al, 2006 and Girard et al, 2007). Eleven 1D soundings were performed with 3 turns 25×25 m 2 coincident overlapping loops on a single profile crossing the conduit. Entirely mapped by divers, the Poumeyssens karst conduit is a target of choice to put 2D linear and Monte Carlo inversion algorithms to the test. Reported results, based on a strongly constrained linear inversion routine, show that the principal conduit was correctly located with MRS but the possibility of existence of other conduits in the area was not analyzed. We now investigate results obtained through less constrained 2D inversion scheme based on the Monte Carlo approach. To compute the occurrence probability of such a scenario, we use a Simulated Annealing algorithm driven by a Blocky prior idea (generating models using blocks of water). Its capability to resolve different models with 100% water content was tested numerically varying the signal to noise ratio. The average water content computed from the solution collection, show that the models were resolved within an uncertainty of 5 to 10 m where the true 100 % water content is gradually scattered from a central maximum (50%) to the edge (10%). The standard deviation of the water content distribution is between 30 and 50 %. Analysis of the field data shows that the Poumeyssens conduit was correctly resolved with MRS using either linear or Monte Carlo inversion. Use of the Monte Carlo method allowed estimating the uncertainty in the conduit localization as about 5 m. In this zone, the MRS water content was scattered from 50% in the center to 10% towards the edges of the zone. The possibility of existence of other conduits was estimated as highly improbable among the collection of well-fitting scenarios. To conclude, a Blocky simulated annealing algorithm was proved to be reliable and efficient approach to assess the inversion uncertainties on 2D targets such as karstic conduit. References Boucher, M., J.-F. Girard, A. Legchenko, J.-M. Baltassat, N. Dörfliger, et K. Chalikakis (2006): Using 2D inversion of magnetic resonance soundings to locate a water-filled karst conduit: Journal of Hydrology, 330(3–4). 413–421. Girard, J-F, M. Boucher, A. Legchenko, and J-M. Baltassat (2007): 2D magnetic resonance tomography applied to karstic conduit imaging: Journal of Applied Geophysics, 63, 103-116. Hertrich, M., A.G. Green, M. Braun, and U. Yaramanci (2009): High-resolution surface NMR tomography of shallow aquifers based on multioffset measurements: Geophysics, 74, 47- 59. Legchenko, A., M. Descloitres, C. Vincent, H. Guyard, S. Garambois, K. Chalikakis and M. Ezersky (2011): Three-dimensional magnetic resonance imaging for groundwater: New Journal of Physics, 13, 025022, doi: 10.1088/1367-2630/13/2/025022. Mosegaard, K. and Tarantola, A. (1995): Monte Carlo sampling of solutions to inverse problems: Journal of Geophysical Research, 100(7), 431- 447. Magnetic Resonance in the Subsurface – 5 th International Workshop on Magnetic Resonance Hannover, Germany, 25 – 27 September 2012
Page 1 and 2: Magnetic Resonance in the Subsurfac
Page 3 and 4: Poster Presentation Posters are dis
Page 5 and 6: Scientific Committee Yaramanci, Ugu
Page 7 and 8: Toke Højbjerg Nielsen Toke Højbje
Page 9 and 10: 10.00 - 10.50 Coffee Break & Poster
Page 11 and 12: Poster Measurement Technology Poste
Page 13 and 14: Locating a karst conduit with 2D Mo
Page 15 and 16: Measurement Technology Magnetic Res
Page 17 and 18: Design and Experimental study of Sm
Page 19 and 20: Quantifying Background Magnetic Fie
Page 21 and 22: 3 component NMR with NMARMIT sensor
Page 23 and 24: Aquater MRS instrument Oleg A. Shus
Page 25 and 26: Signal Processing Magnetic Resonanc
Page 27 and 28: Model-based cancelling of powerline
Page 29 and 30: Higher-Order Statistical Signal Pro
Page 31 and 32: MRS noise investigations with focus
Page 33 and 34: Modeling and Inversion Magnetic Res
Page 35 and 36: Inversion of T1 relaxation times ba
Page 37 and 38: Earth's magnetic field and MRS phas
Page 39: 2D Cell Inversion for Magnetic Reso
Page 43 and 44: Hybrid and multi-objective genetic
Page 45 and 46: Comparison of borehole and surface
Page 47 and 48: Researching vertical resolution of
Page 49 and 50: Advances in hydrological parameteri
Page 51 and 52: Direct inversion for water retentio
Page 53 and 54: An efficient full coupled inversion
Page 55 and 56: Hard rock hydrogeophysics applied t
Page 57 and 58: A laboratory study to determine the
Page 59 and 60: A general model for predicting hydr
Page 61 and 62: Research and Practice of the Relati
Page 63 and 64: Exploiting the phase information: e
Page 65 and 66: MRS and borehole correlation in Den
Page 67 and 68: Feasibility study of the MRS monito
Page 69 and 70: NMR Logging: A tool for quantifying
Page 71 and 72: Investigating hydraulic properties
Page 73 and 74: Application of underground magnetic
Page 75 and 76: Case studies of the MRS method in v
Page 77 and 78: Assessment of the use of surface NM
Page 79 and 80: Application of surface-NMR to study
Page 81 and 82: Calibration MRS Hydrodynamic Parame
Page 83: The Experimental Study of MRS Metho

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