Location and dimensionality estimation of geological bodies using eigenvectors of "Computed Gravity Gradient Tensor"


1 M.Sc. Student, Department of Physics, faculty of Science, Razi University, Kermanshah, Iran

2 Assistant Professor, Department of Physics, faculty of Science, Razi University, Kermanshah, Iran


One of the methodologies employed in gravimetry exploration is eigenvector analysis of Gravity Gradient Tensor (GGT) which yields a solution including an estimation of a causative body’s Center of Mass (COM), dimensionality and strike direction. The eigenvectors of GGT give very rewarding clues about COM and strike direction. Additionally, the relationships between its components provide a quantity (I), representative of a geologic body dimensions. Although this procedure directly measures derivative components of gravity vector, it is costly and demands modern gradiometers. This study intends to obtain GGT from an ordinary gravity field measurement (gz). This Tensor is called Computed GGT (CGGT). In this procedure, some information about a geologic mass COM, strike and rough geometry, just after an ordinary gravimetry survey, is gained. Because of derivative calculations, the impacts of noise existing in the main measured gravity field (gz) could be destructive in CGGT solutions. Accordingly, to adjust them, a “moving twenty-five point averaging” method, and “upward continuation” are applied. The methodology is tested on various complex isolated and binary models in noisy conditions. It is also tested on real geologic example from a salt dome, USA, and all the results are highly acceptable.


Main Subjects

Abdelrahman, E. M. and El-Araby, T. M., 1996, Shape and depth solutions from moving average residual gravity anomalies. Journal of Applied Geophysics, 36, 89-95.
Aster, R. C., Borchers, B. and Thurber, C., 2003, Parameter Estimation and Inverse Problems. Elsevier.
Bell, R. E., Anderson, R. and Pratson, L., 1997, Gravity gradiometry resurfaces. The Leading Edge, 16, 55–59.
Bell, R. E. and Hansen, R. O., 1998, The rise and fall of early oil field technology: The torsion balance gradiometer. The Leading Edge, 17, 81-83.
Beiki, M. and Pedersen, L. B., 2010, Eigenvector analysis of the gravity gradient tensor to locate geologic bodies. Geophysics, 75(6), I37–I49.
Childers, V. A., Bell, R. E. and Brozena, J. M., 1999, Airborne gravimetry: An investigation of filtering. Geophysics, 64, 61–69.
Dransfield, M. H., 2007, Airborne gravity gradiometry in the research for mineral deposits. Proceedings of Exploration 07: Fifth Decennial International Conference on Mineral Exploration, edited by Milkereit, B., 341-354.
Droujinine, A., Vasilevsky, A. and Evans, R., 2007, Feasibility of using full tensor gradient FTG data for detection of local lateral density contrasts during reservoir monitoring. Geophysical Journal International, 169, 795– 820.
Edwards, A. J., J. Maki, T. and Peterson, D. G., 1997, Gravity gradiometry as a tool for underground facility detection. Journal of Environmental & Engineering Geophysics, 2(2), 137–143.
Fedi, M., Ferranti, L., Florio, G., Giori, I. and Italiano, F., 2005, Understanding the structural setting in the southern Apennines Italy: Insight from gravity gradient tensor. Tectonophysics, 397(1–2), 21–36.
Fitz Gerald, D., Argast, D., Paterson, R. and Holstein, H., 2009, Full tensor magnetic gradiometry processing and interpretation developments. 11th South African Geophysical Association SAGA.
Hatch, D., 2004, Evaluation of a full tensor gravity gradiometer for kimberlite exploration. The ASEG-PESA Airborne gravity workshop, Extended Abstracts, 73–80.
Hinojosa, J. H. and Mickus, K. L., 2002, Hilbert transform of gravity gradient profiles: Special cases of the general gravity-gradient tensor in the Fourier transform domain. Geophysics, 67(3), 766–769.
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.
Murphy, C. A. and Brewster, J., 2007, Target delineation using full tensor gravity gradiometry data. Extended Abstract, ASEG-PESA 19th International Geophysical Conference and Exhibition, Perth, Australia.
Nabighian, M. N., 1984, Toward a three-dimensional automatic interpretation of potential field data via generalized Hilbert transforms: Fundamental relations. Geophysics, 49(6), 780-786.
Nettleton, L. L., 1962, Gravity and magnetic for geologists and seismologists. AAPG Bulletin, 46, 1815-1838.
Nettelton, L. L., 1976, Gravity and Magnetics in oil prospecting. McGraw-Hill, New York.
Oruc, B., 2010, Depth Estimation of Simple Causative Sources from Gravity Gradient Tensor Invariants and Vertical Component. Pure. Appl. Geophys. 167, 1259–1272.
Pajot, G., de 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–I34.
Pedersen, L. B. and Rasmussen, T. M., 1990, The gradient tensor of potential field anomalies: Some implications on data collection and data processing of maps. Geophysics, 55, 1558–1566.
Pawlowski, B., 1998, Gravity gradiometry in resource exploration. The Leading Edge, 17, 51–52.
Routh, P., Jorgensen, G. J. and Kisabeth, J. L., 2001, Base of the salt mapping using gravity and tensor gravity data. 70th Annual International Meeting, SEG, Expanded Abstracts, 1482–1484.
Vasco, O. W. and Taylor, C., 1991, Inversion of airborne gravity gradient data, southwestern Oklahoma. Geophysics, 56, 90–91.
While, J., Biegert, E. and Jackson, A., 2009, Generalized sampling interpolation of noise gravity/gravity gradient data. Geophysical Journal International, 178, 638–650.
While, J., Jackson, A., Smit, D. and Biegert, E., 2006, Spectral analysis of gravity gradiometry profiles. Geophysics, 71(1), J11–J22.
Zhdanov, M. S., Ellis, R. and Mukherjee, S., 2004, Three-dimensional regularized focusing inversion of gravity gradient tensor component data. Geophysics, 69, 925–937.
Zhang, C., Mushayandebvu, M. F., Reid, A. B., Fairhead, J. D. and Odegard, M., 2000, Euler deconvolution of gravity tensor gradient data. Geophysics, 65, 512–520.
Zhou, W., 2016, Depth Estimation Method Based on the Ratio of Gravity and Full Tensor Gradient Invariant. Pure.  Appl. Geophys, 173(2), 499-508.