Noise filtering of full-gravity gradient tensor data
Yuan Yuan1, Huang Da-Nian1, Yu Qing-Lu2, and Geng Mei-Xia1
1. College of Geo-Exploration Science and Technology, Jilin University, Changchun, 130026, China.
2. Sinopec Geophysical Research Institute, Nanjing, 211103, China.
Abstract：
In oil and mineral exploration, gravity gradient tensor data include higher-frequency signals than gravity data, which can be used to delineate small-scale anomalies. However, full-tensor gradiometry (FTG) data are contaminated by high-frequency random noise. The separation of noise from high-frequency signals is one of the most challenging tasks in processing of gravity gradient tensor data. We first derive the Cartesian equations of gravity gradient tensors under the constraint of the Laplace equation and the expression for the gravitational potential, and then we use the Cartesian equations to fit the measured gradient tensor data by using optimal linear inversion and remove the noise from the measured data. Based on model tests, we confirm that not only this method removes the high-frequency random noise but also enhances the weak anomaly signals masked by the noise. Compared with traditional low-pass filtering methods, this method avoids removing noise by sacrificing resolution. Finally, we apply our method to real gravity gradient tensor data acquired by Bell Geospace for the Vinton Dome at the Texas–Louisiana border.
YUAN Yuan,HUANG Da-Nian,YU Qing-Lu et al. Noise filtering of full-gravity gradient tensor data[J]. APPLIED GEOPHYSICS, 2013, 10(3): 241-250.
[1]
Barnes, G. and Lumley, J., 2011, Processing gravity gradient data: Geophysics, 76(2), I33 - I47.
[2]
Barnes, G., Lumley, J., Houghton, P. I., and Gleave, R. J., 2011, Comparing gravity and gravity gradient surveys: Geophysical Prospecting, 59, 176 - 187.
[3]
Barnes, G., Barraud, J., Lumley, J., and Davies, M., 2008, Advantages of multi-tensor high resolution gravity gradient data: 78th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 3587 - 3590.
[4]
Beiki, M., 2010, Analytic signals of gravity gradient tensor and their application to estimate source location: Geophysics, 75(6), 159 - 174.
[5]
Blakely, R. J., 1995, Potential theory in gravity and magnetic applications: Cambridge University Press, Cambridge.
[6]
Brzezowski, S. J., and Heller, W. G., 1988, Gravity gradiometer survey errors: Geophysics, 53, 1355 - 1361.
[7]
Hansen, P. C., and Leary, D. P. O., 1993, The use of the L-curve in the regularization of discrete ill-posed problems: SIAM Journal on Scientific Computing, 14, 1487 - 1503.
[8]
Jorgensen, G. J., Kisabeth, J. L., and Routh, P. S., 2001, The role of potential field data and joint inverse modeling in the exploration of the deepwater Gulf of Mexico mini-basin province: Petroleum Frontiers, 17, 18 - 35.
[9]
Li, Y., 2001, Processing gravity gradiometer data using an equivalent source technique. 71st Annual International Meeting, SEG, Expanded Abstracts, 1466 - 1469.
[10]
Lyrio, J. C., Tenorio, L., and Li, Y., 2004, Efficient automatic denoising of gravity gradiometry data: Geophysics, 69, 772 - 782.
[11]
Ma, G. Q., Du, X. J., and Li, L. L., 2012, Comparison of the tensor local wavenumber method with the conventional local wavenumber method for interpretation of total tensor data of potential fields: Chinese Journal of Geophysics, 55(7), 2450 - 2461.
[12]
Menke, W., 1984, Geophysical data analysis discrete inverse theory: Academic Press.
[13]
Mikhailov, V., Pajot, G., Diament, M., and Price, A., 2007, Tensor deconvolution: A method to locate equivalent sources from full tensor gravity data: Geophysics, 72(5), I61 - I69.
[14]
Mims, J., Selman, D., Dickinson, J., Murphy, C., and Mataragio, J., 2009, Comparison study between airborne and ship-borne full tensor gravity gradiometry (FTG) data: SEG Technical Program Expanded Abstracts, 28, 942 - 946.
[15]
Mumaw, G., 2004, Marine 3D full tensor gravity gradiometry-The first five years: Hydro International, 8, 38 - 41.
[16]
Murphy, C. A., 2006, Evaluating Air-FTG survey data: bringing value to the full picture: 18th ASEG Preview, 24 - 25.
[17]
Murphy, C. A., and Brewster, J., 2007, Target delineation using full tensor gravity gradiometry data: ASEG, Extended Abstracts.
[18]
Murphy, C. A., 2010, Recent developments with Air-FTG: Abstracts from the ASEG-PESA Airborne Gravity 2010 Workshop, 142 - 151.
[19]
Oldenburg, D. W., and Li, Y., 1994, Subspace linear inverse method: Inverse Problems, 915 - 935
[20]
Pajot, G., Viron, O., Diament, M., Lequentrec-Lalancette, M. F., and Mikhailov, V., 2008, Noise reduction through joint processing of gravity and gravity gradient data: Geophysics, 73(3), I23 - I33.
[21]
Pilkington, M., 2012, Analysis of gravity gradiometer inverse problems using optimal design measures: Geophysics, 77(2), G25 - G31.
[22]
Rao, B. S. R., and Murthy, I. V. R., 1978, Gravity and magnetic methods?of?prospecting, Amold - Heinemann.
[23]
Sneeuw, N., 2006, Physical Geodesy: Lecture notes, University of Stuttgart.
[24]
While, J., Jackson, A., Smit, D., and Biegert, E., 2006, Spectral analysis of gravity gradiometry profiles: Geophysics, 71, 11 - 22.
[25]
Zhang, C., Mushayandebvu, M. F., Reid, A. B., Fairhead, J. D., and Odegard, M. E., 2000, Euler deconvolution of gravity tensor gradient data: Geophysics, 65(2), 512 - 520.
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