Noise filtering of full-gravity gradient tensor data

In oil and mineral exploration, gravity gradient tensor data include higher- frequency signals than gravity data, which can be used to delineate small-scale anomalies. However, full-tensor gradiometry （FTG） data are contaminated by high-frequency random noise. The separation of noise from high-frequency signals is one of the most challenging tasks in processing of gravity gradient tensor data. We first derive the Cartesian equations of gravity gradient tensors under the constraint of the Laplace equation and the expression for the gravitational potential, and then we use the Cartesian equations to fit the measured gradient tensor data by using optimal linear inversion and remove the noise from the measured data. Based on model tests, we confirm that not only this method removes the high- frequency random noise but also enhances the weak anomaly signals masked by the noise. Compared with traditional low-pass filtering methods, this method avoids removing noise by sacrificing resolution. Finally, we apply our method to real gravity gradient tensor data acquired by Bell Geospace for the Vinton Dome at the Texas-Louisiana border.

Full gravity gradient tensors from vertical gravity by cosine transform

We present a method to calculate the full gravity gradient tensors from pre-existing vertical gravity data using the cosine transform technique and discuss the calculated tensor accuracy when the gravity anomalies are contaminated by noise. Gravity gradient tensors computation on 2D infinite horizontal cylinder and 3D ＂Y＂ type dyke models show that the results computed with the DCT technique are more accurate than the FFT technique regardless if the gravity anomalies are contaminated by noise or not. The DCT precision has increased 2 to 3 times from the standard deviation. In application, the gravity gradient tensors of the Hulin basin calculated by DCT and FFT show that the two results are consistent with each other. However, the DCT results are smoother than results computed with FFT. This shows that the proposed method is less affected by noise and can better reflect the fault distribution.

Edge enhancement of gravity anomalies and gravity gradient tensors using an improved small sub-domain filtering method

In order to enhance geological body boundary visual effects in images and improve interpretation accuracy using gravity and magnetic field data, we propose an improved small sub-domain filtering method to enhance gravity anomalies and gravity gradient tensors. We discuss the effect of Gaussian white noise on the improved small sub-domain filtering method, as well as analyze the effect of window size on geological body edge recognition at different extension directions. Model experiments show that the improved small sub-domain filtering method is less affected by noise, filter window size, and geological body edge direction so it can more accurately depict geological body edges than the conventional small sub-domain filtering method. It also shows that deeply buried body edges can be well delineated through increasing the filter window size. In application, the enhanced gravity anomalies and calculated gravity gradient tensors of the Hulin basin show that the improved small sub-domain filtering can recognize more horizontal fault locations than the conventional method.

A fast-imaging method for airborne gravity gradient data based on tensor invariants

Airborne gravity gradient data contain additional short-wavelength information about the buried geological bodies.This study develops a fast interpretation method based on the gravity gradient data for the sources’spatial location and physical property parameters.This study analyzes the advantages of the source parameter inversion method based on tensor invariants.It proposes a normalized fast-imaging method based on tensor invariants to quickly estimate the spatial location parameters of sources through the local maximum value position of the imaging results.First,the tensor invariant characteristics and the imaging method’s effect in a simple model are analyzed using a theoretical model.Second,to analyze the imaging method’s application effect in complex model conditions,the method’s applicability is quantitatively analyzed using the data added with noise,superimposed anomalies of adjacent sources,and anomalies of deep and shallow geological bodies.The theoretical model’s simulation results show that the model’s imaging results in this study have satisfactory performance on the spatial position estimation of the sources.Finally,the method is applied to the gravity anomaly data corresponding to the Humble salt dome.The imaging results can effectively estimate the distribution of the salt dome’s horizontal and depths,verifying the practicability of the method.

3D density inversion of gravity gradient data using the extrapolated Tikhonov regularization

We use the extrapolated Tikhonov regularization to deal with the ill-posed problem of 3D density inversion of gravity gradient data. The use of regularization parameters in the proposed method reduces the deviations between calculated and observed data. We also use the depth weighting function based on the eigenvector of gravity gradient tensor to eliminate undesired effects owing to the fast attenuation of the position function. Model data suggest that the extrapolated Tikhonov regularization in conjunction with the depth weighting function can effectively recover the 3D distribution of density anomalies. We conduct density inversion of gravity gradient data from the Australia Kauring test site and compare the inversion results with the published research results. The proposed inversion method can be used to obtain the 3D density distribution of underground anomalies.

Forward Modeling of Gravity,Gravity Gradients,and Magnetic Anomalies due to Complex Bodies

On the basis of the results of improved analytical expression of computation of gravity anomalies due to a homogeneous polyhedral body composed of polygonal facets, and applying the forward theory with the coordinate transformation of vectors and tensors, we deduced both the analytical expressions for gravity gradient tensors and for magnetic anomalies of a polygon, and obtained new analytical expressions for computing vertical gradients of gravity anomalies and vertical component of magnetic anomalies caused by a polyhedral body. And also we developed explicitly the complete unified expressions for the calculation of gravity anomalies, gravity gradient, and magnetic anomalies due to the homogeneous polyhedron. Furthermore, we deduced new analytical expressions for computing vertical gradients of gravity anomalies due to a finite rectangular prism by applying the newly obtained expressions for gravity gradient tensors due to a polyhedral target body. Comparison with forward calculation of models shows the correctness of these new expressions. It will reduce forward calculation time of gravity-magnetic anomalies and improve computational efficiency by applying our unified expressions for joint forward modeling of gravity-magnetic anomalies due to homogeneous polyhedral bodies.

Improved preconditioned conjugate gradient algorithm and application in 3D inversion of gravity-gradiometry data

With the continuous development of full tensor gradiometer （FTG） measurement techniques, three-dimensional （3D） inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit （GPU） and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation （SSOR） technique and the incomplete Choleksy decomposition conjugate gradient algorithm （ICCG）. Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noise- contaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit （CPU）. Real airbome gravity-gradiometry data from Vinton salt dome （south- west Louisiana, USA） are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data.

Joint inversion of gravity and multiple components of tensor gravity data

Geological structures often exhibit smooth characteristics away from sharp discontinuities. One aim of geophysical inversion is to recover information about the smooth structures as well as about the sharp discontinuities. Because no specific operator can provide a perfect sparse representation of complicated geological models, hyper-parameter regularization inversion based on the iterative split Bregman method was used to recover the features of both smooth and sharp geological structures. A novel preconditioned matrix was proposed, which counteracted the natural decay of the sensitivity matrix and its inverse matrix was calculated easily. Application of the algorithm to synthetic data produces density models that are good representations of the designed models. The results show that the algorithm proposed is feasible and effective.

Multi-component joint inversion of gravity gradient based on fast forward calculation

With the development of gravity gradient full tensor measurement technique,three-dimensional( 3D) inversion based on gravity gradient tensor can provide more accurate information. But the forward calculation of 3D full tensor sensitivity matrix is very time-consuming,which restricts its development and application.According to the symmetry of the kernel function,the authors reconstruct the underground source of geological body to avoid repeat computation of the same value,and work out the corresponding relationship between the response of geological body to the observation point and the response of reconstructed geological body to the observation point. According to the relationship,rapid calculation of full tensor gravity sensitivity matrix can be achieved. The model calculation shows that this method can increase the speed of 30-45 times compared with the traditional calculation method. The sensitivity matrix is applied to the multi-component inversion of gravity gradient. The application of this method on the measured data provides the basis for the promotion of the method.

基于U⁃Rnet的重力全张量梯度数据反演

重力反演是通过地表信息获取地下地质体空间结构与物理性质的重要手段之一。每个重力梯度分量反映不同的地质体信息,联合重力梯度分量进行重力反演能够更好地研究地下密度异常体的形态和分布。为此,提出基于神经网络的重力全张量梯度数据反演算法,将U⁃Rnet网络应用于重力全张量数据的三维反演问题。为了检验该算法的有效性,采用六种典型模型进行模拟实验,获得了具有清晰边界和稀疏的反演结果。首先,对比L2和Tversky两种损失函数的反演结果,后者的反演结果能更清晰地反映模型的边界位置;然后,对不同梯度张量组合进行反演,四组实验结果在三个方向(x、y、z)上具有不同的反演精度,组合四的误差最低;最后,将该方法应用于美国德克萨斯州文顿盐丘的FTG数据,反演结果与实际地质信息基本吻合。

航空地球物理勘查技术发展战略研究

航空地球物理勘探是重要的快速找矿勘查方法,21世纪以来我国航空地球物理勘查技术已取得长足进步,但现有技术与装备仍难以满足国家“新一轮找矿突破战略行动”和深地、深海探测等对重大关键核心技术与装备的新需求。本文聚焦我国航空地球物理勘查技术高质量发展布局,梳理和总结了国内外航空地球物理勘查技术发展现状,评估了当前国内外技术竞争和发展态势,分析研判了我国在该领域面临的主要挑战。结合科技发展新变化、新特征和新趋势,瞄准超导传感器、航空重力全张量梯度、航磁全张量梯度、多场源全深度航空电磁、航空地震等前沿关键技术,以及新一轮找矿突破战略行动等急需的实用化技术,制定了我国航空地球物理勘查技术发展路线图。针对前沿技术攻关能力不够强、技术适应性较差和创新基础较薄弱等问题,提出了组建国家级航空地球物理技术创新中心、开展第四代航空地球物理勘查技术研发和构建一体化的航空地球物理技术装备发展体系建议。

利用重力梯度张量等位面曲率的地质体定位

针对重力梯度张量曲率的研究,前人的工作主要集中在重力张量曲率的解释及边缘检测中,几乎没有涉及到地下密度异常体的定位.本文结合重力矢量和重力梯度张量提出了一套基于重力梯度张量等位面曲率的地下密度异常体位置估计策略.首先,从重力梯度张量等位面曲率的基本定义出发,计算重力梯度张量等位面曲率.然后,通过寻找球面或圆形等位面的重力梯度张量曲率,提出了利用最大主曲率定位地下密度异常体位置的源参数估计方法,并详细推导了估计3D球体(质点)和2D水平线源位置信息的解析表达式.再者,针对噪声和多源存在的情况,提出了一套利用重力梯度张量等位面曲率获得密度异常体位置信息的稳健估计流程,并利用模糊C均值聚类算法进一步确定地下密度异常体的中心位置.最后,通过理论模型测试和文顿盐丘实测航空重力梯度数据测试,验证了本文算法的可行性和可靠性.结果表明:在满足曲率半径定义条件的情况下,本文所提出的源参数估计方法可以定位单个或多个地下3D和2D密度异常体的空间位置,具有较好的稳健性和抗噪能力.该方法拓展了重力梯度张量曲率的应用范围,可为重力梯度张量的三维反演工作提供先验的空间位置信息.

重力梯度张量的预条件共轭梯度法反演

针对重力梯度张量反演中的问题,提出基于预条件共轭梯度法的重力梯度张量反演。通过在目标函数中加入粗糙度对模型进行约束以避免反演参数远多于采集点数的欠定问题不稳定,并在目标函数中添加深度加权矩阵对核函数进行补偿,以避免核函数随着深度的增大而快速衰减的问题。分别反演、比较各重力梯度张量分量和联合5个独立分量,并将重力梯度张量5个独立联合反演应用于Y型岩脉。研究结果表明:联合反演效果明显优于单一分量的反演效果,且能较好地与原始模型相吻合,证明了本文算法的有效性。

重力梯度张量解析信号的欧拉反褶积

利用重力梯度张量数据高精度的特点以及解析信号在确定异常体位置上的优势,将重力梯度张量解析信号代替位场的导数完成重力梯度张量解析信号的欧拉反褶积;通过在1个窗口内对1组数据点解3个欧拉方程来自动识别构造指数,从而规避了传统欧拉反褶积方法中需要事先确定构造指数的问题,同时减少了背景场的影响。研究结果表明:使用重力梯度张量的解析信号,其欧拉反褶积的解收敛性很好,能准确地判断地下异常体源的位置,有效规避背景场的影响,反演效果较好。

基于重力梯度张量曲率的边界识别

重力梯度张量曲率目前广泛用于重力数据的处理和解释中.为了拓宽重力梯度张量曲率的应用,本文回顾了重力梯度张量曲率的定义,从等位面的曲率定义出发,讨论了正确计算曲率的测量参考系及局部旋转的相关理论,并以单个球体和棱柱体为例来说明曲率的正确计算方式.然后,在正确计算重力梯度张量曲率的基础上,将重力梯度张量曲率应用到重力数据的边界识别中,通过理论模型和实际数据详细分析和比较了各种曲率在重力边界识别中的应用效果.结果表明:基于等位面的局部旋转坐标系是各种曲率正确计算的先决条件,纠正了曲率计算的误区;在边界识别中,局部坐标系下所计算的高斯曲率进行边界识别能够较好的圈定地下地质体的边界.

二度体的重力张量有限元正演模拟

介绍了重力梯度张量,并将有限单元法应用于二维重力梯度张量的正演计算。为了验证有限元正演方法的精度,对截面为矩形的两个二度体组合模型进行有限元正演模拟,结果表明正演曲线与理论曲线形态一致,拟合情况好。通过对截面形状不规则、密度分块均匀的二度体进行正演模拟,说明有限元法可通过网格剖分来逼近不规则目标体的边界,并对剖分单元赋予不同的密度值来实现对复杂二度体的重力张量的正演模拟。

重力张量数据的目标体边缘检测方法探讨

文中介绍了几种目前常用的利用位场数据提取目标体边界的算法。通过分析各种边界提取算法的结果特征,将其分为阶跃型边缘和屋脊型边缘两种,并把边缘检测技术应用到重力张量数据处理中,利用阶跃型边缘检测算子和屋脊型边缘检测算子直接提取目标体边界。模型实验结果表明,利用边缘检测算法得到的目标体边界与实际边界吻合较好,与利用极值点、零点或其他特征点的边界提取算法相比,通过边缘检测算法得到的目标体边界更为精确、完整。同时通过对理论模型添加5%的高斯白噪声,证明了边缘检测算法具有一定的抗干扰能力。

矩形棱柱体重力梯度张量异常正演计算公式

矩形棱柱体重力梯度张量异常常用的正演计算公式含有解析奇点。结合理论推导过程详细分析了"奇点"存在的原因,并基于前人提出的长方体ΔT场及其梯度场无解析奇点理论表达式,建立了矩形棱柱体重力梯度张量无解析"奇点"公式,通过模型计算结果对比和理论分析证明了其正确性。

重力场匹配导航的全张量重力梯度基准图模拟

针对目前重力场匹配导航研究的需要,提出了一种计算机模拟全张量重力梯度基准图的方法,可利用地形高程数据模拟计算局部地区的重力梯度数字地图。该方法从扰动重力梯度的原理出发,分析了地形起伏对重力梯度场的影响,并提出以立方体为地形单元模型,积分计算测量点附近的地形对测量点重力梯度各个分量值的扰动影响。在此基础上模拟格网式测量,从而得到较高分辨率的全张量重力梯度数字地图。仿真实验表明,这种方法计算所得的重力梯度基准图可以精确到10-2～10-1E,相对误差为8.27%,并且存在大量的细节纹理,有着较好的导航应用前景。与实测数据的对比分析说明,所得的重力梯度基准图基本符合实测数据的特性,所提出的方法可以作为一种有效的全张量重力梯度基准图模拟的方法。

全张量重力梯度数据误差分析及补偿

针对用于航空移动平台的高精度全张量重力梯度测量系统,深入研究了梯度仪12个加速度计按3个不同旋转轴圆盘形成差分组合的结构。在确认该结构具有有效抑制运动共模加速度、减少外界环境干扰、实现高精度探测优点的同时,着重分析了重力梯度仪测量误差的来源和影响。研究表明,主要影响包括仪器固有随机噪声和外界确定性噪声。为定量描述影响程度,推导了在航空动态环境下的测量方程,并分离出加速度计的性能不匹配、平台不稳定、圆盘转速不稳定3个主要固有因素,从时间域和频率域角度定量分析固有影响因素的噪声水平。试验分析表明,通过利用Simulink仿真系统可以获得固有因素产生的噪声水平,并提出抑制方案。针对搭载环境测量误差,还分析了实测飞行中姿态和质量的改变对重力梯度测量值造成的环境影响,提出了基于点质量源的自身梯度校正方法。