Abstract
This study, a reweighting focusing (RF) inversion and modified preconditioned conjugate gradient (MPCG) inversion methods are described, and then, the proficiency of the two inversion approaches is compared. The RF inversion method is employed for inverting the 2D gravity and gravity horizontal gradient data. It is found that the obtained subsurface density distributions from the RF inversion of the gravity horizontal gradient data are situated around the furthest vertical borders of the causative mass, which can help interpret the underground structures. Also, the MPCG method, based on three data sets, is presented. Gravity and its horizontal and vertical gradients are the input data for the MPCG inversion algorithm. A privilege of the MPCG algorithm is its avoidance of the inverse operator. The proficiency of both inversion methods is examined with a noise-corrupted theoretical gravity data set related to an assumed subsurface model. The results show the density distributions inverted from the RF inversion reflect the shape of the model better than the ones inverted from the MPCG inversion. The RF and MPCG inversion methods are applied for inverting the real gravity data related to a chromite deposit mass from Northwest of Iran. The depths to the top and bottom estimated by the RF inversion are about 7 and 20 m, and those estimated by the MPCG inversion are about 7 and 25 m. Additionally, the Euler method was evaluated for comparison, giving a depth range of 5 to 10 m of the underground chromite mass below the observation surface.
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This manuscript was based on a subsample of data sets and knowledge provided by the Oil Exploration Operations Company of Iran (OEOC).
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This study was part of a PhD thesis supported by Islamic Azad University. However, it reflects only the opinions or views of the authors. The authors have sole responsibility for their work. The authors are grateful for the comments of respected reviewers to improve this study.
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Kabiri, M., Riazi Rad, Z.S. Gravity interpretation using modified preconditioned conjugate gradient and reweighting of inversion methods: a case study from Iran. Arab J Geosci 16, 472 (2023). https://doi.org/10.1007/s12517-023-11532-9
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DOI: https://doi.org/10.1007/s12517-023-11532-9