The Efficient 3D Gravity Focusing Density Inversion Based on Preconditioned JFNK Method under Undulating Terrain: A Case Study from Huayangchuan, Shaanxi Province, China

Qingfa Meng,Guoqing Ma,Taihan Wang,Shengqing Xiong

doi:10.3390/min10090741

Abstract

Since polymetallic ores show higher anomalies in gravity exploration methods, we usually obtain the position and range of ore bodies by density inversion of gravity data. The three-dimensional (3D) gravity focusing density inversion is a common interpretation method in mineral exploration, which can directly and quantitatively obtain the density distribution of subsurface targets. However, in actual cases, it is computation inefficient. We proposed the preconditioned Jacobian-free Newton-Krylov (JFNK) method to accomplish the focusing inversion. The JFNK method is an efficient algorithm in solving large sparse systems of nonlinear equations, and we further accelerate the inversion process by the preconditioned technique. In the actual area, the gravity anomalies are distributed on the naturally undulating surface. Nowadays, the gravity inversion under undulating terrain was mainly achieved by discretizing the ground into unstructured meshes, but it is complicated and time-consuming. To improve the practicality, we presented an equivalent-dimensional method that incorporates unstructured meshes with structured meshes in gravity inversion, and the horizontal size is determined by the gradient of observed gravity and terrain data. The small size meshes are adopted at the position where the terrain or gravity gradient is large. We used synthetic data with undulating-terrain to test our new method. The results indicated that the recovered model obtained by this method was similar to the inversion method of unstructured meshes, and the new method computes faster. We also applied the method to field data in Huayangchuan, Shaanxi Province. The survey area has complicated terrain conditions and contains multiple polymetallic ores. Based on the high-density characteristics of polymetallic ore bodies in the area, we calculate the field data into 3D density models of the subsurface by the preconditioned JFNK method and infer six polymetallic ores.

Highlights

The gravity exploration method is used to detect polymetallic ores because of its higher density feature, and they can use the density inversion method of gravity anomaly to obtain the approximate horizontal position of the ores
We presented the preconditioned Jacobian-free Newton-Krylov (JFNK) gravity focusing density inversion method to obtain the density feature of the ores with accuracy and efficiency
We proposed the adaptive equivalent-dimensional mesh method which combines the unstructured and structure mesh to achieve gravity inversion with the undulating terrain

Summary

Introduction

The gravity exploration method is used to detect polymetallic ores because of its higher density feature, and they can use the density inversion method of gravity anomaly to obtain the approximate horizontal position of the ores. To improve the direct solution method, Liang used the gradient data and boundary element method to obtain the potential field of the horizontal plane directly from the curved surface data [18,19]. We presented the preconditioned JFNK gravity focusing density inversion method to obtain the density feature of the ores with accuracy and efficiency. We used the models with the undulating terrain and compared common unstructured meshing methods to gauge the performance of the algorithm and test its accuracy and efficiency.

Methodology subsurface into a finite number of rectangular

Gravity Model Tests

30 SNR shown in Figure

Actual

Conclusions