3D Gravity Inversion with Correlation Image in Space Domain and Application to the Northern Sinai Peninsula

Authors

  • Xu Zhang Shanghai Shannan Investigation & Design Co.,Ltd. , Shanghai, 201206, China
  • Peng Yu State Key Laboratory of Marine Geology, Tongji University, Shanghai, 200092, China
  • Jian Wang Key Laboratory of Crustal Dynamics, Institute of Crustal Dynamics, China Earthquake Administration, Beijing, 100085, China

DOI:

https://doi.org/10.30564/jgr.v1i2.845

Abstract

We present a 3D inversion method to recover density distribution from gravity data in space domain. Our method firstly employs 3D correlation image of the vertical gradient of gravity data as a starting model to generate a higher resolution image for inversion. The 3D density distribution is then obtained by inverting the correlation image of gravity data to fit the observed data based on classical inversion method of the steepest descent method. We also perform the effective equivalent storage and subdomain techniques in the starting model calculation, the forward modeling and the inversion procedures, which allow fast computation in space domain with reducing memory consumption but maintaining accuracy. The efficiency and stability of our method is demonstrated on two sets of synthetic data and one set of the Northern Sinai Peninsula gravity data. The inverted 3D density distributions show that high density bodies beneath Risan Aniza and low density bodies exist to the southeast of Risan Aniza at depths between 1~10 and 20 km, which may be originated from hot anomalies in the lower crust. The results show that our inversion method is useful for 3D quantitative interpretation.

Keywords:

3D gravity inversion, Space domain, Correlation image, Effective equivalent storage, Subdomain technique, Northern Sinai Peninsula

References

[1] Abdelrahman, E.M., Radwan, A.H., Issawy, E.A., El-Araby, H.M., El-Araby, T.M., Abo-Ezz, E.R.. Gravity interpretation of vertical faults using correlation factors between successive least-squares residual anomalies. Mining Pribram Symp. on Mathematical Methods in Geology, 1999, MC2: 1-6.

[2] Abedi, M., Gholami, A., Norouzi, G.H., Fathianpour, N.. Fast inversion of magnetic data using Lanczos bidiagonalization method. Journal of Applied Geophysics, 2013, 90: 126-137.

[3] Baniamerian J., Oskooi B. and Fedi M.. ource imaging of potential fields through a matrix space-domain algorithm, Journal of Applied Geophysics, 2017, 136: 51.

[4] Baniamerian J., Fedi M. and Oskooi B.. Compact Depth from Extreme Points: a tool for fast potential field imaging. Geophysical prospecting, 2016, 64: 1386-1398.

[5] Charles F. Van Loan.. Computational Frameworks for the Fast Fourier Transform, 1992.

[6] Chauhan M.S., Fedi M. and Mrinal K. S..Gravity inversion by the Multi‐Homogeneity Depth Estimation method for investigating salt domes and complex sources, Geophysical Prospecting, 2018, 66: 175-191.

[7] Fedi M.. ”DEXP: A fast method to determine the depth and the structural index of potential fields sources.” Geophysics, 2007, 72(1): I1-I11.

[8] Fedi M. and Pilkington M.. “Understanding imaging methods for potential field data.” Geophysics, 2012, 77(1): G13-G24.

[9] Gibert D. and Sailhac P.. Comment on: self-potential signals associated with preferential grounwater flow pathways in sinkholes. Journal of Geophysical Research, 2008, 113.

[10] Guo, L.H., Meng, X.H., Shi, L.. 3D correlation imagingof the vertical gradient of gravity data. J Geophys Eng, 2011, 8: 6-12.

[11] Khalil, M.A., Santos, F.M.. 3D Gravity Inversion of Northern Sinai Peninsula: A Case Study. Pure Appl Geophys, 2014, 171: 1557-1569.

[12] Khalil, M.A., Santos, F.M., Farzamian,M.. 3D gravity inversion and Euler deconvolution to delineate the hydro-tectonic regime in El-Arish area, northern Sinai Peninsula. Journal of Applied Geophysics,2014, 103: 104-113.

[13] Li, C.-F., Lu, Y. and Wang, J.. A global reference model of Curie-point depths based on EMAG2. Scientific Reports, 2017, 7: 45129.

[14] Li, Y., Oldenburg, D.W.. 3-D inversion of magnetic data. Geophysics, 1996, 61: 394-408.

[15] Li, Y., Oldenburg, D.W.. 3-D inversion of gravity data. Geophysics, 1998, 63: 109-119.

[16] Li, Y.G., Oldenburg, D.W.. Fast inversion of large-scale magnetic data using wavelet transforms and a logarithmic barrier method. Geophys J Int, 2003, 152: 251-265.

[17] Liu, G., Yan, H., Meng, X., Chen, Z. An extension of gravity probability tomography imaging. Journal of Applied Geophysics, 2014, 102: 62-67.

[18] MohammadRezaie, AliMoradzadeh and Ali NejatiKalateh,Fast 3D inversion of gravity data using solution space priorconditioned lanczos bidiagonalization,Journal of Applied Geophysics,2017, 136: 42-50.

[19] Mauriello, P., Patella, D.. Gravity probability tomography: a new tool for buried mass distribution imaging. Geophysical Prospecting, 2001, 49: 1-12.

[20] Meng, X.H., Liu, G.F., Chen, Z.X., Guo, L.H.. 3-D gravity and magnetic inversion for physical properties based on residual anomaly correlation (in Chinese with English abstract). Chinese Journal of Geophysics, 2012, 55: 304-309.

[21] Moustafa A.R.. Structural setting and tectonic evolution of North Sinai folds, Egypt. In Homberg, G. and Bachmann, M. (eds). Evolution of the Levant Margin and Western Arabia Platform since the Mesozoic. Geological Society, London, Special Publications, 2015, 341: 37-63.

[22] Patella, D.. Introduction to ground surface self-potential tomography. Geophysical Prospecting, 1997, 45: 653-681.

[23] Portniaguine, O., Zhdanov, M.S.. Focusing geophysical inversion images. Geophysics, 1999, 64: 874-887; 3‐D magnetic inversion with data compression and image focusing. Geophysics, 2002, 67: 1532-1541.

[24] Shamsipour, P., Chouteau, M., Marcotte, D.. 3D stochastic inversion of magnetic data. Journal of Applied Geophysics, 2011, 73: 336-347.

[25] Shamsipour, P., Marcotte, D., Chouteau, M., Keating, P.. 3D stochastic inversion of gravity data using cokriging and cosimulation. Geophysics, 2010, 75: I1-I10.

[26] Tikhonov, A.N., Arsenin, V.Y.. Solution of ill-posed Problems. Winston, 1977.

[27] Yao, C.L.. High speed computation and efficient storage in 3D gravity and magnetic inversion based on genetic algorithms (in Chinese with English abstract). Cheinese Journal of Geophysics, 2003, 46: 252-258.

[28] Yao, C.L., Zheng, Y.M., Zhang, Y.W.. 3-D gravity and magnetic inversion for physical properties using stochastic subspaces (in Chinese with English abstract). Cheinese Journal of Geophysics, 2007, 50: 1576-1583.

[29] Zhdanov, M.S.. Tutorial: Regularization in inversion theory. Center for Wave Phenomena, 1993: 1-47.

[30] Zhdanov, M.S.. Geophysical inverse theory and regularization problems. Elsevier, 2002.

[31] Zhao,G,D, Chen B., Chen L.W, Liu J.X, Ren Z.Y.. High-accuracy 3D Fourier forward modeling of gravity field based on the Gauss-FFT technique. Journal of Applied Geophysics, 2018, 150: 294-303.

Downloads

How to Cite

Zhang, X., Yu, P., & Wang, J. (2019). 3D Gravity Inversion with Correlation Image in Space Domain and Application to the Northern Sinai Peninsula. Journal of Geological Research, 1(2), 9–18. https://doi.org/10.30564/jgr.v1i2.845

Issue

Article Type

Articles