Concealed faults and intrusions identification based on multiscale edge detection and 3D inversion of gravity and magnetic data: A case study in Qiongheba area, Xinjiang, Northwest China

2019 ◽  
Vol 7 (2) ◽  
pp. T331-T345 ◽  
Author(s):  
Jiayong Yan ◽  
Xiangbin Chen ◽  
Guixiang Meng ◽  
Qingtian Lü ◽  
Zhen Deng ◽  
...  
Keyword(s):  
Edge Detection ◽  
Junggar Basin ◽  
Northwest China ◽  
Gold Deposits ◽  
Combination Method ◽  
Magnetic Data ◽  
3D Inversion ◽  
Data Set ◽  
Gravity And Magnetic ◽  
Gravity And Magnetic Data

Qiongheba is a polymetallic ore concentration area located in the east margin of the Junggar Basin in Xinjiang, Northwest China. Because all three main types of metal deposits (porphyry-type copper, skarn-type iron-copper, and structural altered rock-type gold deposits) in this area are controlled strictly by fault structures and intrusions buried under the Quaternary sediments, the detection of concealed faults and intrusions is of great significance for mineral prospecting. We aim to make clear the faults and intrusions based on the high-precision gravity and magnetic data set. First, multiscale edge detection of gravity and magnetic data is used to distinguish and divide the faults system. Second, 3D recognition of concealed intrusions combining with 3D inversion and multiscale edge detection of gravity and magnetic is carried out to construct the 3D formation of concealed intrusions. Last, seven prospecting targets are proposed based on our research and existed regional geologic and geochemical information, and two of them have been confirmed to be rich in polymetal (Cu-Fe-Mo-Au in the Layikeleke deposit and Cu in the Baxi deposit) by drilling. Our research results not only proved the effectiveness of the combination method of 3D inversion and multiscale edge detection of gravity and magnetic data in the prospecting of concealed faults and intrusions, but they also provide abundant information for mineral exploration prediction in the Qiongheba area.

3D inversion modeling of joint gravity and magnetic data based on a sinusoidal correlation constraint

2019 ◽  
Vol 16 (4) ◽  
pp. 519-529
Author(s):  
Xiu-He Gao ◽  
Sheng-Qing Xiong ◽  
Zhao-Fa Zeng ◽  
Chang-Chun Yu ◽  
Gui-Bin Zhang ◽  
...  
Keyword(s):  
Magnetic Data ◽  
3D Inversion ◽  
Gravity And Magnetic ◽  
Gravity And Magnetic Data

Cross-gradients joint 3D inversion with applications to gravity and magnetic data

Geophysics ◽  
2009 ◽  
Vol 74 (4) ◽  
pp. L31-L42 ◽  
Author(s):  
Emilia Fregoso ◽  
Luis A. Gallardo
Keyword(s):  
Joint Inversion ◽  
Three Dimensional ◽  
Structural Similarity ◽  
Solution Procedure ◽  
Magnetic Data ◽  
3D Inversion ◽  
Gravity And Magnetic ◽  
New Formulation ◽  
Value Decomposition ◽  
Gravity And Magnetic Data

We extend the cross-gradient methodology for joint inversion to three-dimensional environments and introduce a solution procedure based on a statistical formulation and equality constraints for structural similarity resemblance. We apply the proposed solution to the joint 3D inversion of gravity and magnetic data and gauge the advantages of this new formulation on test and field-data experiments. Combining singular-value decomposition (SVD) and other conventional regularizing constraints, we determine 3D distributions of the density and magnetization with enhanced structural similarity. The algorithm reduces some misleading features of the models, which are introduced commonly by conventional separate inversions of gravity and magnetic data, and facilitates an integrated interpretation of the models.

ACLAS — A method to define geologically significant lineaments from potential-field data

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. G87-G100 ◽  
Author(s):  
Lorenzo Cascone ◽  
Chris Green ◽  
Simon Campbell ◽  
Ahmed Salem ◽  
Derek Fairhead
Keyword(s):  
Large Scale ◽  
Magnetic Data ◽  
Data Set ◽  
New Approach ◽  
Potential Field Data ◽  
North West ◽  
Gravity And Magnetic ◽  
Lineament Analysis ◽  
The Individual ◽  
Gravity And Magnetic Data

Geologic features, such as faults, dikes, and contacts appear as lineaments in gravity and magnetic data. The automated coherent lineament analysis and selection (ACLAS) method is a new approach to automatically compare and combine sets of lineaments or edges derived from two or more existing enhancement techniques applied to the same gravity or magnetic data set. ACLAS can be applied to the results of any edge-detection algorithms and overcomes discrepancies between techniques to generate a coherent set of detected lineaments, which can be more reliably incorporated into geologic interpretation. We have determined that the method increases spatial accuracy, removes artifacts not related to real edges, increases stability, and is quick to implement and execute. The direction of lower density or susceptibility can also be automatically determined, representing, for example, the downthrown side of a fault. We have evaluated ACLAS on magnetic anomalies calculated from a simple slab model and from a synthetic continental margin model with noise added to the result. The approach helps us to identify and discount artifacts of the different techniques, although the success of the combination is limited by the appropriateness of the individual techniques and their inherent assumptions. ACLAS has been applied separately to gravity and magnetic data from the Australian North West Shelf; displaying results from the two data sets together helps in the appreciation of similarities and differences between gravity and magnetic results and indicates the application of the new approach to large-scale structural mapping. Future developments could include refinement of depth estimates for ACLAS lineaments.

Integrated interpretation of gravity, magnetic, seismic, and well data to image volcanic units for oil-gas exploration in the eastern Junggar Basin, northwest China

2020 ◽  
Vol 8 (4) ◽  
pp. SS113-SS127
Author(s):  
Kaijun Xu ◽  
Yaoguo Li
Keyword(s):  
Seismic Data ◽  
Volcanic Rocks ◽  
Junggar Basin ◽  
Magnetic Data ◽  
Magnetic Method ◽  
Data Set ◽  
Amplitude Inversion ◽  
Gravity And Magnetic ◽  
Integrated Interpretation ◽  
Well Data

We carried out a multigeophysical data joint interpretation to image volcanic units in an area where seismic imaging is difficult due to complicated and variable volcanic lithology. The gravity and magnetic methods can be effective in imaging the volcanic units because volcanic rocks are often strongly magnetic and have large density contrasts. Gravity and magnetic data have good lateral resolution, but they are faced with challenges in defining the depth extent. Although seismic data make for poor imaging in volcanic rocks, they can provide a reliable stratigraphic structure above volcanic rocks to improve the vertical resolution of the gravity and magnetic method. We have developed an integrated interpretation method that combines the advantages of seismic, gravity, magnetic, and well data to generate a 3D quasigeology model to image volcanic units. We first use seismic data to obtain the stratigraphic boundaries, and then we apply an anomaly stripping method based on a seismic-derived structure to extract residual gravity and magnetic anomaly produced by volcanic rocks. We further perform the 3D gravity and magnetic amplitude inversion to recover the distribution of the density and effective susceptibility. We perform geology differentiation using the inverted density and effective magnetic susceptibility to identify the spatial distribution of four groups of volcanic units. The results show that the integrated interpretation of multigeophysical data can significantly decrease the uncertainty associated with any single data set and yield more reliable imaging of lateral and vertical distribution of volcanic rocks.

scholarly journals Separation of sources and 3D inversion of gravity and magnetic data for the Thuringian Basin, Germany

2012 ◽  
Vol 42 (2) ◽  
pp. 119-132
Author(s):  
Ilya Prutkin ◽  
Gerhard Jentzsch ◽  
Thomas Jahr
Keyword(s):  
Contact Surface ◽  
Joint Inversion ◽  
Magnetic Data ◽  
Large Area ◽  
3D Inversion ◽  
Lateral Direction ◽  
Line Segments ◽  
Gravity And Magnetic ◽  
3D Geometry ◽  
Gravity And Magnetic Data

Separation of sources and 3D inversion of gravity and magnetic data for the Thuringian Basin, Germany We propose a novel methodology for separation of potential field sources and its 3D inversion. New approaches are developed to separate sources: i) in depth using a succession of upward and downward continuation; ii) in the lateral direction by means of approximation with the field of 3D line segments; iii) according to density and magnetization contrast based on pseudo-gravity calculation. Our original inversion algorithms allow the recovery of unknown 3D geometry both for a restricted body of arbitrary shape and for a contact surface. For the first time, we apply our algorithms to joint inversion of gravity and magnetic data for a large area (the Thuringian Basin in central Germany). We separate in depth sources of both gravitational and magnetic anomalies for the whole territory of Thuringia and compare corresponding components. A 3D model of the main sources is presented based on approximation with 3D line segments and their further transforming into a restricted body or a contact surface with the same field.

Automatic 3-D interpretation of potential field data using analytic signal derivatives

Geophysics ◽  
1997 ◽  
Vol 62 (1) ◽  
pp. 87-96 ◽  
Author(s):  
Nicole Debeglia ◽  
Jacques Corpel
Keyword(s):  
Signal Amplitude ◽  
Vertical Gradient ◽  
Analytic Signal ◽  
Magnetic Data ◽  
Practical Implementation ◽  
Potential Field Data ◽  
Gravity And Magnetic ◽  
Second Derivatives ◽  
Gravity And Magnetic Data ◽  
Derivatives Of

A new method has been developed for the automatic and general interpretation of gravity and magnetic data. This technique, based on the analysis of 3-D analytic signal derivatives, involves as few assumptions as possible on the magnetization or density properties and on the geometry of the structures. It is therefore particularly well suited to preliminary interpretation and model initialization. Processing the derivatives of the analytic signal amplitude, instead of the original analytic signal amplitude, gives a more efficient separation of anomalies caused by close structures. Moreover, gravity and magnetic data can be taken into account by the same procedure merely through using the gravity vertical gradient. The main advantage of derivatives, however, is that any source geometry can be considered as the sum of only two types of model: contact and thin‐dike models. In a first step, depths are estimated using a double interpretation of the analytic signal amplitude function for these two basic models. Second, the most suitable solution is defined at each estimation location through analysis of the vertical and horizontal gradients. Practical implementation of the method involves accurate frequency‐domain algorithms for computing derivatives with an automatic control of noise effects by appropriate filtering and upward continuation operations. Tests on theoretical magnetic fields give good depth evaluations for derivative orders ranging from 0 to 3. For actual magnetic data with borehole controls, the first and second derivatives seem to provide the most satisfactory depth estimations.

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