Lianghui Guo

Preferential filtering for gravity anomaly separation

We present the preferential filtering method for gravity anomaly separation based on Green equivalent-layer concept and Wiener filter. Compared to the conventional upward continuation and the preferential continuation, the preferential filtering method has the advantage of no requirement of continuation height. The method was tested both on the synthetic gravity data of a model of multiple rectangular prisms and on the real gravity data from a magnetite area in Jilin Province, China. The results show that the preferential filtering method produced better separation of gravity anomaly than both the conventional low-pass filtering and the upward continuation.

GICUDA: A parallel program for 3D correlation imaging of large scale gravity and gravity gradiometry data on graphics processing units with CUDA

The 3D correlation imaging for gravity and gravity gradiometry data provides a rapid approach to the equivalent estimation of objective bodies with different density contrasts in the subsurface. The subsurface is divided into a 3D regular grid, and then a cross correlation between the observed data and the theoretical gravity anomaly due to a point mass source is calculated at each grid node. The resultant correlation coefficients are adopted to describe the equivalent mass distribution in a quantitate probability sense. However, when the size of the survey data is large, it is still computationally expensive. With the advent of the CUDA, GPUs lead to a new path for parallel computing, which have been widely applied in seismic processing, astronomy, molecular dynamics simulation, fluid mechanics and some other fields. We transfer the main time-consuming program of 3D correlation imaging into GPU device, where the program can be executed in a parallel way. The synthetic and real tests have been performed to validate the correctness of our code on NVIDIA GTX 550. The precision evaluation and performance speedup comparison of the CPU and GPU implementations are illustrated with different sizes of gravity data. When the size of grid nodes and observed data sets is 1024x1024x1 and 1024x1024, the speed up can reach to 81.5 for gravity data and 90.7 for gravity vertical gradient data respectively, thus providing the basis for the rapid interpretation of gravity and gravity gradiometry data.

3D correlation imaging of the vertical gradient of gravity data

We present a new 3D correlation imaging approach for vertical gradient of gravity data for deriving a 3D equivalent mass distribution in the subsurface. In this approach, we divide the subsurface space into a 3D regular grid, and then at each grid node calculate a cross correlation between the vertical gradient of the observed gravity data and the theoretical gravity vertical gradient due to a point mass source. The resultant correlation coefficients are used to describe the equivalent mass distribution in a probability sense. We simulate a geological syncline model intruded by a dike and later broken by two vertical faults. The vertical gradient of gravity anomaly of the model is calculated and used to test the approach. The results demonstrate that the equivalent mass distribution derived by the approach reflects the basic geological structures of the model. We also test the approach on the transformed vertical gradient of real Bouguer gravity data from a geothermal survey area in Northern China. The thermal reservoirs are located in the lower portion of the sedimentary basin. From the resultant equivalent mass distribution, we produce the depth distribution of the bottom interface of the basin and predict possible hidden faults present in the basin.

A correlation-based approach for determining the threshold value of singular value decomposition filtering for potential field data denoising

We present a correlation coefficient analysis (CCA) method for obtaining threshold when using singular value decomposition (SVD) filtering method to reduce noise in potential field data. Before computation of correlation coefficients, SVD is performed on the gridded potential field data with the purpose of obtaining singular values of the data. A sliding window is utilized to truncate the acquired singular values, which allows us to obtain different singular value sequences. The lower limit of the sliding window is generally set to zero and the upper limit of the sliding window is the threshold. Then, we calculate and plot the correlation coefficients associated with the initial sequence and the newly obtained sequences, choosing the inflection point of the plotted correlation coefficients as the threshold. The CCA method offers a quantitative way to determine a threshold, which can be easily implemented by a computer program. We illustrate the method using synthetic datasets and field data from a metallic deposit area in the middle-lower reaches of the Yangtze River in China. The results show that the proposed method is effective and is able to provide an optimal threshold.

3D correlation imaging of magnetic total field anomaly and its vertical gradient

We present a new 3D correlation imaging approach for magnetic total field anomaly and its vertical gradient for deriving a 3D equivalent magnetic dipole distribution in the subsurface. In this approach, we divide the subsurface space into a 3D regular grid, and then at each grid node calculate cross correlation between the observed magnetic total field anomaly (or its vertical gradient) and the theoretical magnetic total field anomaly (or its vertical gradient) due to a magnetic dipole. The resultant correlation coefficients are used to describe the equivalent magnetic dipoles distribution in a probabilistic sense. The approach was tested both on the synthetic magnetic data of a model of multiple rectangular prisms and on the real aeromagnetic data from an iron-ore deposit area in the middle–lower reaches of the Yangtze River, China. The results show that the equivalent magnetic dipole distribution derived by the approach basically reflects the subsurface magnetic sources and also illustrate that the approach for the vertical gradient produces a higher resolution of the equivalent magnetic source distribution than that for magnetic total field anomaly alone.

Global correlation imaging of magnetic total field gradients

Firstly we introduce the correlation imaging approach for the x-, y- and z-gradients of a magnetic total field anomaly for deriving the distribution of equivalent magnetic sources of the subsurface. In this approach, the subsurface space is divided into a regular grid, and then a correlation coefficient function is computed at each grid node, based on the cross-correlation between the x-gradient (or y-gradient or z-gradient) of the observed magnetic total field anomaly and the x-gradient (or y-gradient or z-gradient) of the theoretical magnetic total field anomaly due to a magnetic dipole. The resultant correlation coefficient is used to describe the probability of a magnetic dipole occurring at the node. We then define a global correlation coefficient function for comprehensively delineating the probability of an occurrence of a magnetic dipole, which takes, at each node, the maximum positive value of the corresponding correlation coefficient function of the three gradients. We finally test the approach both on synthetic data and real data from a metallic deposit area in the middle-lower reaches of the Yangtze River, China.

The Crustal Structure of the North–South Earthquake Belt in China Revealed from Deep Seismic Soundings and Gravity Data

The North–South earthquake belt (NSEB) is one of the major earthquake regions in China. The studies of crustal structure play a great role in understanding tectonic evolution and in evaluating earthquake hazards in this region. However, some fundamental crustal parameters, especially crustal interface structure, are not clear in this region. In this paper, we reconstructed the crustal interface structure around the NSEB based on both the deep seismic sounding (DSS) data and the gravity data. We firstly reconstructed the crustal structure of crystalline basement (interface G), interface between upper and lower crusts (interface C) and Moho in the study area by compiling the results of 38 DSS profiles published previously. Then, we forwardly calculated the gravity anomalies caused by the interfaces G and C, and then subtracted them from the complete Bouguer gravity anomalies, yielding the regional gravity anomalies mainly due to the Moho interface. We then utilized a lateral-variable density interface inversion technique with constraints of the DSS data to invert the regional anomalies for the Moho depth model in the study area. The reliability of our Moho depth model was evaluated by comparing with other Moho depth models derived from other gravity inversion technique and receiver function analysis. Based on our Moho depth model, we mapped the crustal apparent density distribution in the study area for better understanding the geodynamics around the NSEB.

A Hybrid Positive-and-Negative Curvature Approach for Detection of the Edges of Magnetic Anomalies, and Its Application in the South China Sea

In work discussed in this paper the characteristics of both the most positive and most negative curvatures of a magnetic anomaly were analyzed, and a new approach for detection of the edges of magnetic anomalies is proposed. The new approach, called the hybrid positive-and-negative curvature approach, combines the most positive and most negative curvatures into one curvature by formula adjustments and weighted summation, combining the advantages of the two curvatures to improve edge detection. This approach is suitable for vertically magnetized or reduction-to-pole anomalies, which avoids the complexity of magnetic anomalies caused by oblique magnetization. Testing on synthetic vertically magnetized magnetic anomalies data demonstrated that the hybrid approach traces the edges of magnetic source bodies effectively, discriminates between high and low magnetism intuitively, and is better than approaches based solely on use of the most positive or most negative curvature. Testing on reduced-to-pole magnetic anomalies data around the ocean basin of the South China Sea showed that the hybrid approach enables better edge detection than the most positive or most negative curvatures. On the basis of the features of the reduced-to-pole magnetic anomalies and their hybrid curvature, we suggest the tectonic boundary between the southwestern subbasin and the eastern subbasin of the South China Sea ranges from the northeastern edge of the Zhongsha Islands in the southeast direction to the northeastern edge of the Reed Bank.

An empirical mode decomposition based noise cancelation method for potential field data along with a new stopping criterion

Potential field data is generally contaminated by random noise. The high-frequency noise contained in the data brings unfavorable influences to subsequent data processing. Therefore, suppressing the adverse effects of noise has always been a crucial step which is desirable prior to applying other transformations. Over the past decades, numerous mathematical approaches have been proposed for noise cancelation of potential field data. In the work discussed in this paper, the application of the empirical mode decomposition for denoising of potential field data is briefly described, and a new stopping criterion for this filtering method is introduced. Using the proposed method, the empirical mode decomposition is firstly performed on the original potential field data to get numerous intrinsic mode functions corresponding to components with different frequencies. Each intrinsic mode function is subtracted from the original data to get different residual datasets. The correlation coefficients associated with the original data and various residual datasets are calculated and plotted. The inflection point of the correlation coefficient curve is adopted as the last intrinsic mode function to be selected. The new stopping criterion offers a quantitative way to determine which intrinsic mode functions should be removed during filtering and can be easily implemented within the algorithm. Tests on synthetic noisy gravity data demonstrate that the empirical mode decomposition based noise cancelation method along with this new stopping criterion yield acceptable filtering results for potential field data. The newly developed method is also investigated on real gravity data collected over a magnetite zone in Jilin Province, China.

Compensation for aircraft effects of magnetic gradient tensor measurements in a towed bird

The effect of magnetic interference from the helicopter on full gradient tensor measurements acquired in a towed bird is substantial and must be corrected if airborne data are to be usable. During the actual flight process, the helicopter’s and bird’s attitudes, as well as the relative position between the helicopter and bird, change continuously. Thus the traditional method of compensation for aircraft effects is not suitable for this mode of measurement. For a particularly long towline, magnetic interference from helicopter can be reduced, but the errors introduced by substantial variations in altitude and orientation of the bird may be even greater than the magnetic interference from the helicopter. We have developed a compensation model from the perspective of forward modelling to correct full gradient tensor data measured in a towed bird for the magnetic effects of the helicopter, taking into account variations in attitude of the bird and helicopter. We designed training flight projects that allow compensation parameters to be estimated. The feasibility of the compensation method was verified by modelling and simulated flight tests. Finally, this method was applied to real data and the data quality was improved. We present a compensation model of aircraft effects for full magnetic gradient tensor data acquired in a towed bird. Training flight tests were designed so that aircraft compensation parameters could be estimated. The feasibility of the compensation method was verified by modelling and by a flight simulation test.