REDUCING NON-UNIQUENESS IN SATELLITE GRAVITY INVERSION USING SEISMIC TOMOGRAPHY AND 3D OBJECT ORIENTED IMAGE ANALYSIS TECHNIQUES

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1 REDUCING NON-UNIQUENESS IN SATELLITE GRAVITY INVERSION USING SEISMIC TOMOGRAPHY AND 3D OBJECT ORIENTED IMAGE ANALYSIS TECHNIQUES ISLAM FADEL MARK VAN DER MEIJDE NORMAN KERLE

2 Research Topic: Reducing the non-uniqueness of satellite gravity inversion using constraints based on 3D seismic tomography data applying 3D Object Oriented Image Analysis (OOA).

3 3D OOA (Bio-medical) Recent Image analysis technique. Ruleset = Set of classification criteria Extract 3D objects from 3D image stacks. Schӧnmeyer et al. (2006)

4 3D OOA (Geosciences) Extract 3D objects from LiDAR point cloud. Example by ecognition community:

5 How did the non-uniqueness of satellite gravity been recently reduced? The non-uniqueness has been reduced using seismic data. 3D Seismic Tomography Cammarano et al., 2011 Conversion functions Velocity Density Mishra et al. (2012) Ebbing et al. (2001) Subsurface Interpretation of layers and objects then forward modeling using estimated density values. Additional uncertainties due to the dependency on other physical parameters: Temperature Pressure Composition Trial and error. Usually 2D over profiles. NEW 3D structures from 3D seismic tomography data constrain the inversion of satellite gravity.

6 The Methodology The problem of the non-uniqueness has been divided into 2 sub-problems: The non-uniqueness The shape of the subsurface objects The values of the density contrasts of these objects?? Reduced using 3D OOA of 3D seismic tomography model. Reduced using Object-based inversion and Forward Modeling.

7 The Methodology 3D seismic tomography model (4) Object-based inversion (1) 3D OOA (3) Reconstruct the objects in IGMAS+ (5) Forward modeling (2) Classify the subsurface objects (6) Evaluate

8 Study Area From 3D tomography model and literature the study area mainly composed of : Tanzania Craton. Eastern and Western rift branches. Low velocity anomaly (start ~ at 250 km depth). (Adams et al., 2012) (Adams et al., 2012)

9 1-3D OOA results Results 2- Objects-Reconstruction 3- Object-based inversion

10 3D OOA Results Use of 3D histogram and visual interpretation. Homogeneity and discontinuity characteristics to extract 3D objects. 3D histogram upper mantle part km

11 Object-Based inversion (Upper Mantle) Object-Based Inversion Measured signal EIGEN6C2 Craton Rift Rift 70 % correlation Boundary Calculated signal from the upper mantle part. Low velocity Boundary km Deep High velocity Construction Process km km 1000

12 Objects-Based Inversion (Crustal Part) Object-Based Inversion MOHO Measured signal EIGEN6C2 95 % correlation Crust Calculated signal from the full model. Moho Upper Mantle m k Add layers represent the crustal part from the 3D tomography model. 0.0 km m k The Moho (Tugume et al. (in press))

13 Objects-Based Inversion Calculated signal Measured signal EIGEN6C2 The difference between the measured and the calculated signal from the full model.

14 Upper Mantle Crust Density Contrast Values Object Density Contrast (t/m3) Unit 1 (U1) Unit 2 (U2) Unit 3 (U3) Unit 4 (U4) Unit 5 (U5) MOHO MOHO Craton (C) Shallow High Velocity (SHV) Boundary Shallow High Velocity (BSHV) Rift (R) Boundary Shallow Low Velocity (BSLV) Low Velocity Zone (LV) Inner Low Velocity (ILV) Boundary Deep Low Velocity (BDLV) Deep High Velocity (DHV) Reference 0 Correlation Standard deviation 11

15 Conclusion and Recommendations A new methodology was developed and tested to reduce the non-uniqueness of the gravity modeling. 3D OOA can extract the 3D objects from 3D geophysical data. The methodology was able to reduce the non-uniqueness of the shape of the subsurface objects. However, the density contrast estimation needs to be constrained. The object based inversion approach is very promising and fast. However, IGMAS+ needs to be developed to allow the user to put boundary conditions for density contrast estimations.

16 THANK YOU For more details: Fadel, I., Kerle, N., van der Meijde, M., D object-oriented image analysis of geophysical data. Geophysical Journal International, /gji/ggu139. Fadel, I., et al., 3D object-oriented image analysis in 3D geophysical modelling: Analysing the central part of the East African Rift System. Int. J. Appl. Earth Observ. Geoinf. (2013), References Adams, A., Nyblade, A., Weeraratne, D., Upper mantle shear wave velocity structure beneath the East African plateau: evidence for a deep, plateauwide low velocity anomaly. Geophysical Journal International 189 (1), Götze, H., Lahmeyer, B., Application of three-dimensional interactive modeling in gravity and magnetics. Geophysics 53 (8), Schmidt, S., Götze, H., Fichler, Ch.,A.M., IGMAS+: a new 3D gravity, FTG and magnetic modelling software. Extended abstract. Geoinformatik, Schmidt, S., Plonka, C., Götze, H., Lahmeyer, B., Hybrid modelling of gravity, gravity gradients and magnetic fields. Geophysical Prospecting 59 (6, SI), Schӧenmeyer, R., Prvulovic, D., Rotarska-Jagiela, A., Haenschel, C., Linden, D. E. J., Automated segmentation of lateral ventricles from human and primate magnetic resonance images using cognition network technology. Magnetic Resonance Imaging 24 (10), Tugume, F., Nyblade, A., Julia, J., van der Meijde, M., Precambrian crustal structure in Africa and Arabia: evidence lacking for secular variation. Tectonophysics (in press).