University of Tehran Press Journal of the Earth and Space Physics 2538-371X 46 4 2021 01 20 3D Gravity Cross-Correlation Imaging for Large Scale Data Analysis: Application to the Crustal Structure of Iran 3D Gravity Cross-Correlation Imaging for Large Scale Data Analysis: Application to the Crustal Structure of Iran 131 145 77996 10.22059/jesphys.2020.298815.1007197 FA Iman Ahmadi Ph.D. Student, Department of Mining and Metallurgical Engineering, Yazd University, Yazd, Iran Ahmad Ghorbani Associate Professor. Department of Mining and Metallurgical Engineering, Yazd University, Yazd, Iran Abdol Hamid Ansari Associate Professor. Department of Mining and Metallurgical Engineering, Yazd University, Yazd, Iran Journal Article 2020 03 09 We propose the 3D gravity cross-correlation method to large scale data analyses as a fast analysis method to image the underground mass distribution. This method presents the cross-correlation product of the observed gravity anomaly (or its vertical gradient) and the calculated field due to an elementary mass contrast source. The cross-correlation product of the domain is used to highlight the zones of the highest probability of mass concentrations. First, some synthetic examples demonstrate the reliability and resolution of the method. The synthetic models discover different parameters of investigation space as space dimensions and densities. Tests with synthetic bodies show that the resultant correlation coefficients of the approach can delineate causative bodies in the subsurface. Finally, terrestrial gravity anomaly data of Iran is used to study the crustal structure and the Moho depth of Iran. The result is in a good agreement compared with other research studies of the domain. This technique took about five minutes to calculate the 3D gravity cross-correlation of the whole terrestrial gravity data set of Iran (25,937 data) a computer. Hence, it can easily be used repeatedly to monitor changes of gravity field. We propose the 3D gravity cross-correlation method to large scale data analyses as a fast analysis method to image the underground mass distribution. This method presents the cross-correlation product of the observed gravity anomaly (or its vertical gradient) and the calculated field due to an elementary mass contrast source. The cross-correlation product of the domain is used to highlight the zones of the highest probability of mass concentrations. First, some synthetic examples demonstrate the reliability and resolution of the method. The synthetic models discover different parameters of investigation space as space dimensions and densities. Tests with synthetic bodies show that the resultant correlation coefficients of the approach can delineate causative bodies in the subsurface. Finally, terrestrial gravity anomaly data of Iran is used to study the crustal structure and the Moho depth of Iran. The result is in a good agreement compared with other research studies of the domain. This technique took about five minutes to calculate the 3D gravity cross-correlation of the whole terrestrial gravity data set of Iran (25,937 data) a computer. Hence, it can easily be used repeatedly to monitor changes of gravity field. https://jesphys.ut.ac.ir/article_77996_182581906573c2917cdd108ffad72878.pdf