scholarly journals USING THE COMBINATION OF THE 3D GRAVITY INVERSION METHOD WITH THE DIRECTIONAL ANALYTIC SIGNAL DERIVATIVES AND THE CURVATURE GRAVITY GRADIENT TENSOR METHOD TO DETERMINE STRUCTURE OF THE PRE-CENOZOIC BASEMENT ON SOUTHEAST CONTINENTAL SHELF OF VIETNAM

2019 ◽  
Vol 18 (4) ◽  
pp. 393-405
Author(s):  
Nguyen Kim Dung ◽  
Do Duc Thanh ◽  
Hoang Van Vuong ◽  
Duong Thi Hoai Thu
Keyword(s):  
Continental Shelf ◽  
Density Distribution ◽  
Analytic Signal ◽  
Gravity Gradient ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Gradient Tensor ◽  
Gravity Gradient Tensor ◽  
Maximum Value ◽  
3D Gravity

In this paper, we present some new results of the Pre-Cenozoic basement structure on the Southeast continental shelf of Vietnam based on the combination of some modern methods to analyse and interpret gravity data. They are the 3D gravity inversion method, the directional analytic signal derivatives and the curvature gravity gradient tensor. The results obtained include the density distribution, the fault system and the main structural blocks inside of the Pre-Cenozoic basement on Southeast continental shelf of Vietnam. The initial results about density distribution show that it relatively clearly reflects the shape of basins in the area: The contours that have value σ =2.7 g/cm3 and value σ = 2.76 g/cm3 are near the edges of the Cuu Long basin and the Nam Con Son basin, respectively. The density value reaches the maximum at the center of basins. For the Cuu Long basin, the maximum value is σmax= 2.76 g/cm3 and the Nam Con Son has maximum value σmax= 3.0 g/cm3. Many faults that appear in the study area have the existence depth in the wide range from 6 km to 30 km, even above 30 km and the faults that have the existence depth from 8 to 10 km are in the majority. In particular, the boundary of anomalous sources existing in the Pre-Cenozoic basement is shown by the better resolution, at which more edge points are identified than the maximum horizontal gradient amplitude method that is widely used. The results also show that the combination of individual results complements each other and creats the sufficient and clearer picture inside of the Pre-Cenozoic basement.

Analytic signals of gravity gradient tensor and their application to estimate source location

Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. I59-I74 ◽  
Author(s):  
Majid Beiki
Keyword(s):  
Analytic Signal ◽  
Three Dimensions ◽  
Gravity Gradient ◽  
Automatic Identification ◽  
Gradient Tensor ◽  
Gravity Gradient Tensor ◽  
Signal Functions ◽  
First Vertical Derivative ◽  
Tensor Data ◽  
Analytic Signals

The analytic signal concept can be applied to gravity gradient tensor data in three dimensions. Within the gravity gradient tensor, the horizontal and vertical derivatives of gravity vector components are Hilbert transform pairs. Three analytic signal functions then are introduced along [Formula: see text]-, [Formula: see text]-, and [Formula: see text]-directions. The amplitude of the first vertical derivative of the analytic signals in [Formula: see text]- and [Formula: see text]-directions enhances the edges of causative bodies. The directional analytic signals are homogenous and satisfy Euler’s homogeneity equation. The application of directional analytic signals to Euler deconvolution on generic models demonstrates their ability to locate causative bodies. One of the advantages of this method is that it allows the automatic identification of the structural index from solving three Euler equations derived from the gravity gradient tensor for a collection of data points in a window. The other advantage is a reduction of interference effects from neighboring sources by differentiation of the directional analytic signals in [Formula: see text]-, [Formula: see text]-, and [Formula: see text]-directions. Application of the method is demonstrated on gravity gradient tensor data in the Vredefort impact structure, South Africa.

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

Minerals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 741
Author(s):  
Qingfa Meng ◽  
Guoqing Ma ◽  
Taihan Wang ◽  
Shengqing Xiong
Keyword(s):  
Field Data ◽  
Unstructured Meshes ◽  
New Method ◽  
Shaanxi Province ◽  
Gravity Gradient ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Density Inversion ◽  
Ore Bodies ◽  
3D Gravity

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.

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