磁源体参数反演的快速局部波数法

现有磁异常解释的局部波数法在计算地质体位置时大多是通过复杂的方程求解来完成,且需已知地质体构造指数信息,构造指数是描述地质体类型的参数,在实际数据解释中是难以确定的,因此现有方法计算结果的精度较低。本文提出磁异常解释的快速局部波数法,定义水平与垂直局部波数的平方和为和局部波数,利用和局部波数与其它局部波数的线性组合直接、快速地实现地质体位置参数和属性参数(构造指数)的计算,无需任何先验信息及方程求解运算。通过理论模型试验证明快速局部波数法能准确地完成磁异常的解释,且受背景异常和倾斜磁化干扰较小。将快速局部波数法应用于实际磁数据的解释,获得了地质体的位置和构造指数。     

归一化总水平导数法在位场数据解释中的应用

本文提出归一化总水平导数法,通过对总水平导数进行空间归一化计算实现了异常体水平位置和深度的估计,此外还推导出基于归一化总水平导数的欧拉反褶积法来估算地下地质体的空间位置,两种方法反演结果的相互验证可有效地提高反演结果的可信度.理论模型试验证明空间归一化总水平导数法和归一化总水平导数欧拉反褶积法均能有效地完成异常体的水平位置和深度的估计,所获得的位置参数与理论值相一致.在利用归一化总水平导数法进行磁异常解释时,对数据进行化磁极计算可得到更加准确的结果.将其应用于实际航磁数据的解释,获得了岩脉的大致分布特征.     

解释位场全张量数据的张量局部波数法及其与常规局部波数法的比较

全张量探测技术以其信息量大、精度高、干扰小等优点在地球物理领域中得到广泛应用.本文提出采用张量局部波数法来进行位场全张量数据的解释,首先给出了张量局部波数的定义,然后推导出利用张量局部波数法进行反演的基本公式.本文方法在进行张量数据反演时无需事先知道场源体的类型(构造指数)即可获得场源体的位置信息,且可根据位置参数对场源体的类型进行估计.通过理论模型证明张量局部波数法可以很好地完成位场全张量数据的反演工作,并将其与常规局部波数法进行对比,证明全张量局部波数法的反演结果更加准确,即使在测点分布不合理的情况下,张量局部波数法仍可以获得准确的结果.最后应用张量局部波数法对美国得克萨斯州实测重力数据进行了反演,其反演结果与已有的研究成果相一致.     

局部波数反演磁源参数的改进算法及应用

利用局部波数确定磁源体的深度及类型是一种非常有效且实用的方法.本文基于水平方向波数k_x和垂向波数k_x的理论公式,推导出2种求取场源参数的方法.这2种方法均是要首先确定波数k_s的极大值点及其对应的水平坐标,然后利用k_s异常及向上延拓不同高度的k_s异常与该极大值作相应的计算反演场源深度及构造指数.模型试验证明了本文方法可以准确的计算出地质体的埋深及构造指数,与理论值偏差较小,在理论模型异常上加入一定幅值的干扰噪声,依然可以得到较为准确的反演结果.将其应用于一段实测岩脉数据,其结果与实际资料吻合.     

空间归一化边界识别方法用于判断地质体的水平位置及深度(英文)

边界识别是重磁数据解释中的常用方法之一,依据其结果可划分出地质体的水平范围。边界识别结果受地质体埋深及导数计算误差的影响所识别边界与真实边界之间存在一定的差距,且边界识别法无法直观地给出地质体的深度信息。为了获得异常体的水平位置和深度信息,本文提出空间归一化边界识别方法,其对不同深度的边界识别函数进行归一化计算,空间归一化边界识别法的最大值对应于异常体的水平位置和深度。常规边界识别结果的误差随理深的减小而减小,而空间归一化边界识别法是通过最大值来判断地质体的位置,最大值是在地质体处获得,因此归一化边界识别方法所获得的结果是准确的。通过理论模型试验证明归一化边界识别方法能有效地完成异常体的水平位置和深度的计算,所获得的水平位置和深度信息与理论值相一致,为下一步的勘探计划提供了更加可靠的依据。将其应用于实际航磁数据的解释,获得了断裂的具体分布形式。     

基于剩余异常相关成像的重磁物性反演方法

将场源区剖分成长方体单元,通过采集的重磁数据反演出这些单元的密度或者磁化率变化,勾画出场源的分布图像,这种方式是重磁三维反演的重要方向.重磁相关成像通过计算测量的重磁异常与地下各点在测区上的重磁异常的归一化相关,显示出异常地质体的空间赋存状态和等效剩余重磁物性.该方法计算速度快,方法简单、稳定,但是反演的结果只是在-1到+1之间的等效物性,不能够直接反演剩余密度或者磁化率,并且无法引入已知的地质约束.本文通过对物性模型的正演和实测结果的残差进行相关成像,迭代更新物性模型实现对物性参数的反演过程.模型实验证明该方法相对相关成像不仅能提高分辨率,还能够得到真正的物性参数.     

多因复成矿区磁异常偏位解释法

分析了多因复成矿床磁性体的典型特征,总结了该类型矿区磁异常反演解释存在的主要问题,通过提取磁异常基本特征、引入解释偏角和剖面位移等概念,提出了以磁异常共轭解释法为基础的偏位解释法,模型试算及实例分析表明该方法能获得较高的反演精度和符合实际的反演结果,能实现复杂磁异常的反演解释.对比分析认为该方法相对传统方法在一些特殊情况下具有明显优势,是磁法勘探领域中一种新的反演方法,能较好解决多生产实际中一些以往不能解决的重要问题.     

基于航磁矢量数据的磁源总磁化方向估算

在地质体具有较强剩磁或自退磁效应的情况下,获得地质体总磁化方向对磁法勘探的数据处理、反演及解释具有重要意义.与传统航磁总场测量相比,航磁矢量(三分量)测量能够获得地磁场的矢量信息.基于三分量磁异常一阶矩与磁源磁矩的积分关系,我们实现了基于航磁矢量数据的磁源总磁化方向估算.针对该方法易受相邻异常影响,从而使多异常的估算难以确定磁源中心位置的问题,分析了在不同磁化倾角下,估算的磁化偏角、倾角与实际磁源中心位置的关系,并根据该关系采取了限定估算区域的方法,获得了多异常的估算结果.将该方法应用于东天山启鑫地区实测航磁三分量数据,估算了具有强剩磁的启鑫岩体总磁化方向,并将估算的方向应用于化极计算.化极结果显示,减少了启鑫岩体磁异常受斜磁化的影响,且与磁异常模量计算结果类似.该方法假设磁源均匀磁化,估算结果可视为地质体总磁化方向的整体体现,对强剩磁地质体磁异常的数据处理、反演及解释具有实际意义.     

磁梯度张量解析信号分析法及其在场源位置识别中的应用

相对于传统磁异常数据,磁梯度张量数据可以提供有关异常体更多的信息,分辨率更高,具有广阔的应用前景.本文给出了基于磁梯度张量解析信号进行边界增强的新方法,该方法是通过对异常垂向一阶导数与z方向解析信号的比值做归一化得到的,其零值线位置可以很准确的反映出地质体边界位置,而且可以有效降低噪声的干扰.文中还证明了异常垂向一阶导数与x、y、z三个方向解析信号的比值同样满足欧拉齐次方程,且在计算过程中不需考虑构造指数N的影响,避免了因构造指数不当而引起的反演误差.通过对单一地质体及组合地质体模型的实验证明:与常规欧拉反褶积法相比,该反演方法能够更好的得到地质体界面及深度信息,所得的解更集中.将其应用到保定实测数据中,获得了更精确的场源信息.     

全张量磁梯度数据解释的均衡边界识别及深度成像技术

全张量磁梯度数据具有高精度、高分辨率、多参量的优点,能更加清晰地刻画地质体的分布特征,综合利用磁张量梯度数据准确地获得地质体水平位置和深度信息是解释的主要目的.磁张量数据的方向解析信号具有减小倾斜磁化干扰的优点,常被用来圈定磁源体的水平位置,但解析信号强度随着地质体埋深的增加急剧衰减,难以有效识别较深的地质体.张量数据均衡边界识别技术,利用不同方向解析信号的比值函数,能有效地均衡不同深度地质体的响应,同时显示不同深度地质体的边界,提高了对较深地质体的分辨率.磁张量数据深度成像技术根据实测张量数据与假定模型张量数据的相关系数来给定地质体的深度,综合利用多参量数据联合反演提高了反演结果的准确性,且无需进行复杂的反演运算,是大数据量张量数据解释的有效方法.理论模型试验证明：磁张量数据均衡边界识别技术可清晰和准确地识别地质体的水平范围,受倾斜磁化干扰小;磁张量数据深度成像技术可准确地获得地质体的深度信息,具有较强的抗噪性.将上述方法应用于铁矿区实测航磁张量梯度数据解释,获得了铁矿体水平分布与埋深,深度结果与张量欧拉反褶积法计算结果一致.     

Interpretation of magnetic and gravity gradient tensor data using normalized source strength – A case study from McFaulds Lake,Northern Ontario,Canada

In this paper, we present a case study on the use of the normalized source strength (NSS) for interpretation of magnetic and gravity gradient tensors data. This application arises in exploration of nickel, copper and platinum group element (Ni‐Cu‐PGE) deposits in the McFaulds Lake area, Northern Ontario, Canada. In this study, we have used the normalized source strength function derived from recent high resolution aeromagnetic and gravity gradiometry data for locating geological bodies. In our algorithm, we use maxima of the normalized source strength for estimating the horizontal location of the causative body. Then we estimate depth to the source and structural index at that point using the ratio between the normalized source strength and its vertical derivative calculated at two levels; the measurement level and a height h above the measurement level. To discriminate more reliable solutions from spurious ones, we reject solutions with unreasonable estimated structural indices. This method uses an upward continuation filter which reduces the effect of high frequency noise. In the magnetic case, the advantage is that, in general, the normalized magnetic source strength is relatively insensitive to magnetization direction, thus it provides more reliable information than standard techniques when geologic bodies carry remanent magnetization. For dipping gravity sources, the calculated normalized source strength yields a reliable estimate of the source location by peaking right above the top surface. Application of the method on aeromagnetic and gravity gradient tensor data sets from McFaulds Lake area indicates that most of the gravity and magnetic sources are located just beneath a 20 m thick (on average) overburden and delineated magnetic and gravity sources which can be probably approximated by geological contacts and thin dikes, come up to the overburden.     

Improved Local Wavenumber Methods in the Interpretation of Potential Field Data

We present two new potential-inversion methods for estimating the depth and the nature (structural index) of the source, which use various combinations of different forms of local wavenumbers and the information about the horizontal location to estimate individually the depth and the nature of a magnetic source. The improved local wavenumber methods only use the horizontal offset and vertical offset of local wavenumbers to estimate the depth and the structural index of the source, so they yield more stable results compared with the results obtained by current methods that require the derivatives of local wavenumbers. Tests conducted with synthetic noise-free and noise-corrupted magnetic data show that the proposed methods can successfully estimate the depth and the nature of the geologic body. However, our methods are sensitive to high-wavenumber noise present in the data, and we reduced the noise effect by upward continuing the noise-corrupted magnetic data. The practical application of the new methods is tested on a real magnetic anomaly over a dike whose source parameters are known and the inversion results are consistent with the true values.     

Fast local wavenumber (FLW) method for the inversion of magnetic source parameters

The current local wavenumber methods for the interpretation of magnetic anomalies compute the locations of geological bodies by solving complex matrices. Presently, such methods require to know the structural index, which is a parameter that represents the source type. The structural index is hard to know in real data; consequently, the precision of current methods is low. We present the fast local wavenumber (FLW) method, and define the squared sum of the horizontal and vertical local wavenumbers as the cumulative local wavenumber. The FLW method is the linear combination of the umulative local wavenumberand other wavenumbers, and is used to compute the locations and structural index of the source without a priori information and matrix solution. We apply the FLW method to synthetic magnetic anomalies, and the results suggest that the FLW method is insensitive to background and oblique magnetization. Next, we apply the FLW method to real magnetic data to obtain the location and structural index of the source.     

Depth and structural index estimation of 2D magnetic source using correlation coefficient of analytic signal

We presented using the correlation coefficient of the analytic signal of real data and the analytic signal of synthetic data generated by the assumed source to estimate the structural index and the depth of the source. First, we assumed that the causative sources are located at different locations in the underground and the structural index of the assumed source is changed from 0 to 3, and then we separately compute the correlation coefficients of the analytic signal of the measured data and the analytic signal of the anomaly generated by each assumed source, the correlation coefficient can get the maximum value when the location and structural index of the assumed source are consistent with the real source. We tested the correlation coefficient method on synthetic noise-free and noise-corrupted magnetic anomalies, and the inversion results indicate that the new method can successfully finish the inversion of magnetic data. We also applied it to measured magnetic data, and we obtain the structural index and the location of the source.     

基于二阶导数的磁源边界与顶部深度快速反演

为实现磁异常反演,首先提出了磁异常非参数快速反演的概念,即无需提供先验信息.在Nabighian提出的磁场通用梯度公式的基础上,推导实现了基于磁异常垂向二阶导数的非参数快速反演(V2D_depth).它不仅可以获取场源的边界信息,同时可以反演场源的埋深.通过与Tilt_depth方法对比,本文方法计算的场源边界更清晰,反演的深度也更接近真实深度,同时较大程度上克服了Tilt_depth方法受叠加异常的影响.理论模型验证了方法的有效性,并通过准噶尔盆地某区块磁异常数据的处理,提取了受强大的区域背景场掩盖的石炭系火成岩产生的弱异常,突出了构造分区、断裂分布等信息,获取了火成岩的位置及埋深参数,为该区的火成岩油气藏勘探提供了有效的处理途径.     

Application of balanced edge detection filters to estimate the location parameters of the causative sources using potential field data

Balanced edge detection filters can recognize the edges of the shallow and deep bodies simultaneously, and are commonly used in the edge detection of potential field data. In this paper, we present using the balanced edge detection filters to estimate source locations, and derive two linear equations based on the balanced edge detection filters that can estimate the locations of the source without any priori information about the nature (structural index) of the source. The proposed methods are demonstrated on synthetic gravity anomalies, and the inversion results show that the proposed methods can successfully estimate location parameters of the sources. I also apply the proposed methods to real magnetic data, and the inversion results estimated by the proposed methods are consistent with the results estimated by the other similar method.     

Depth and structural index from normalized local wavenumber of 2D magnetic anomalies

Recent improvements in the local wavenumber approach have made it possible to estimate both the depth and model type of buried bodies from magnetic data. However, these improvements require calculation of third‐order derivatives of the magnetic field, which greatly enhances noise. As a result, the improvements are restricted to data of high quality. We present an alternative method to estimate both the depth and model type using the first‐order local wavenumber approach without the need for third‐order derivatives of the field. Our method is based on normalization of the first‐order local wavenumber anomalies and provides a generalized equation to estimate the depth of some 2D magnetic sources regardless of the source structure. Information about the nature of the sources is obtained after the source location has been estimated. The method was tested using synthetic magnetic anomaly data with random noise and using three field examples.     

Interpretation of magnetic anomalies by horizontal and vertical derivatives of the analytic signal

Magnetic anomalies are often disturbed by the magnetization direction, so we can’t directly use the original magnetic anomaly to estimate the exact location and geometry of the source. The 2D analytic signal is insensitive to magnetization direction. In this paper, we present an automatic method based on the analytic signal horizontal and vertical derivatives to interpret the magnetic anomaly. We derive a linear equation using the analytic signal properties and we obtain the 2D magnetic body location parameters without giving a priori information. Then we compute the source structural index (expressing the geometry) by the estimated location parameters. The proposed method is demonstrated on synthetic magnetic anomalies with noise. For different models, the proposed technique can both successfully estimate the location parameters and the structural index of the sources and is insensitive to noise. Lastly, we apply it to real magnetic anomalies from China and obtain the distribution of unexploited iron ore. The inversion results are consistent with the parameters of known ore bodies.