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物探与化探, 2019, 43(2): 308-319 doi: 10.11720/wtyht.2019.1112

方法研究·信息处理·仪器研制

正则化方法在比值类位场边缘识别方法中的研究

何涛1,2,3, 王万银1,2,3, 黄金明4, 张明华4, 杨敏1,2,3,5

1. 长安大学 重磁方法技术研究所,陕西 西安 710054

2. 长安大学 地质工程与测绘学院,陕西 西安 710054

3. 长安大学 西部矿产资源与地质工程教育部重点实验室,陕西 西安 710054

4. 中国地质调查局发展研究中心,北京 100037

5. 纽芬兰纪念大学 地球科学系,加拿大

The research of the regularization method in the ratio methods of edge recognition by potential field

HE Tao1,2,3, WANG Wan-Yin1,2,3, HUANG Jin-Ming4, ZHANG Ming-Hua4, YANG Min1,2,3,5

1. Gravity & Magnetic Institute of Chang’an University,Xi’an 710054,China;

2. College of Geology Engineering and Geomatics,Chang’an University,Xi’an 710054,China;

3. Key Laboratory of Western China’s Mineral Resources and Geological Engineering,Ministry of Education,Chang’an University,Xi’an 710054,China;

4. China Geological Survey Development Research Center, Beijing 100037, China

5. Department of Earth Sciences, Memorial University of Newfoundland, St. Johns, NF, Canada

责任编辑: 王萌

收稿日期: 2018-12-3   修回日期: 2019-02-20   网络出版日期: 2019-04-20

基金资助: 国家重点研发计划项目2017YFC0602200之课题“航空地球物理综合处理解释方法研究及软件开发”.  2017YFC0602202
中国地质调查局发展研究中心“智能地质调查系统开发与推广”项目.  121201004000150014

Received: 2018-12-3   Revised: 2019-02-20   Online: 2019-04-20

作者简介 About authors

何涛(1994-),男,在读硕士研究生,研究方向是重、磁方法理论及应用。Email:hetaochd@163.com

摘要

位场边缘识别方法有很多种,其中归一化标准差法(NSTD)、倾斜角法(Ta)和Theta Map(cosθ)等方法属于比值类方法。比值类方法在计算过程中会出现分母接近于0或者等于0这种情况,致使计算结果不稳定,并产生错误的边缘识别结果。为此,对比值类边缘识别方法计算公式中的分母加一个大于零的正则化因子,不但解决了比值类方法的数值计算稳定性问题,而且提高了部分比值类边缘识别方法识别结果的精度。通过理论模型和实际资料检验了新方法的稳定性、精度以及有效性。正则化因子的引入同样可以改善以比值类方法为基础构建的二阶导数类边缘识别方法的识别效果,如倾斜角总水平导数(Ta-THDR)的识别效果。正则化这一思想不但可以解决比值类位场边缘识别方法的数值计算问题,而且可以解决比值类方法的数值计算问题。

关键词: 边缘识别 ; 比值类方法 ; 正则化方法 ; 稳定性 ; 精度

Abstract

The ratio methods are one sort of edge recognition methods by using potential field, which contains the Normalized Standard Deviation method (NSTD), Tilt Angle method (Ta) and Theta Map (cosθ). If the denominator of ratio method closes or even equals to zero in the process of calculation, the result obtaining from ratio methods is unstable and may even bear little resemblance to the true geology. In order to relief this problem, a regularization factor, which is greater than zero, is added in the denominator of the ratio methods’ formula, which not only enhances the numerical stability of the ratio methods but also improves the accuracy of some ratio edge recognition methods. The stability, accuracy and effectiveness of the new method is verified by testing synthetic models and calculating real data. Also, the introduction of the regularization factor also can improve the effect of recognizing edge by the second-derivative edge recognition methods, which is based on the ratio methods, such as the Total Horizontal Derivative of the Tilt Angle (Ta-THDR). The idea of regularization can not only solve the numerical calculation problem of the ratio methods of edge recognition for potential field, but also solve the numerical calculation problem of all ratio methods.

Keywords: edge recognition ; ratio methods ; regularization method ; stability ; accuracy

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本文引用格式

何涛, 王万银, 黄金明, 张明华, 杨敏. 正则化方法在比值类位场边缘识别方法中的研究. 物探与化探[J], 2019, 43(2): 308-319 doi:10.11720/wtyht.2019.1112

HE Tao, WANG Wan-Yin, HUANG Jin-Ming, ZHANG Ming-Hua, YANG Min. The research of the regularization method in the ratio methods of edge recognition by potential field. Geophysical and Geochemical Exploration[J], 2019, 43(2): 308-319 doi:10.11720/wtyht.2019.1112

0 引言

利用重、磁异常识别地质体的边缘位置有很多类方法,其中有一类方法为比值类方法。如倾斜角方法(Ta)和Theta Map方法(cosθ)以及归一化标准差(NSTD)方法等。

Miller和Singh[1]首次提出了倾斜角法(Ta),该方法计算垂向导数(VDR)[2,3]与总水平导数(THDR)[4]比值的反正切值,并利用零值线位置识别地质体的边缘位置。Wijns等[5]首次提出了Theta Map(cosθ)方法,该方法利用总水平导数与解析信号振幅(ASM)[6]比值的极大值位置识别地质体的边缘位置。Cooper和Cowan[7]首次提出归一化标准差方法(NSTD),该方法计算滑动窗口内垂向一阶导数的标准差与水平方向和垂向方向一阶导数标准差总和的比值,并将该比值记为滑动窗口中心点的归一化标准差值,最后利用极大值位置识别地质体的边缘位置。王万银[8]研究认为倾斜角、Theta Map与VDR的识别结果完全相同,并且当总水平导数等于零时倾斜角存在“解析奇点”,解析信号振幅等于零时Theta Map存在“解析奇点”,这会使计算结果不稳定,但没有给出解决这一问题的方法。一些学者通过不同的导数组合构建了类似于倾斜角与Theta Map形式的比值类边缘识别方法[9,10,11,12,13,14,15],在模型试算和实际资料处理中取得了很好的识别效果,但是均没有考虑其在计算过程中分母为零或者接近零时计算的不稳定性问题。一些学者同样也构建了一些形如倾斜角和Theta Map的归一化边缘识别方法[12,14,16-17],通过在分母中引入一个常量,提高计算稳定性,该常量实质就是正则化因子,但是均没有系统的分析引入正则化因子对于原方法识别结果的影响。

正则化思想在重、磁数据的处理和解释中有着重要的作用。Tikhonov 和 Glasko[18]在解决反演的非线性问题中首次提出正则化方法,后续的一些学者将正则化思想应用到重、磁数据的处理与转换中,有效的解决了处理与转化中出现的不稳定问题,例如引入正则化因子解决频率域垂向导数[19,20]和向下延拓[21,22,23,24,25,26]计算时的不稳定性问题。

边缘识别的比值类方法在分母为零或者接近零时,使计算结果不稳定,产生错误的识别边界,对于我们识别正确的边界造成干扰。本文依据正则化的思想,通过在分母加大于零的正则化因子来解决比值类方法在分母为零或者接近零时计算的不稳定性问题。正则化因子的引入同样可以提高以比值类方法为基础构建的二阶导数类边缘识别方法的计算稳定性,如倾斜角总水平导数(Ta-THDR)[27]

1 基于正则化方法的比值类位场边缘识别方法

基于正则化方法的比值类位场边缘识别方法就是根据正则化方法的思想,在比值类边缘识别方法的分母上加入正则化因子。正则化因子取大于零的正则化调节因子α乘以相应分母的最大值,通过α来调节正则化因子的大小。

1.1 正则化倾斜角(R-Ta)

倾斜角(Ta)边缘识别方法的计算公式[1]

Ta=tan-1(VDRTHDR),

其中:VDR= fz,THDR= (fx)2+(fy)2,f为某一平面的位场数据。当THDR值为0或者接近零时, VDRTHDR的计算变的不稳定。为了解决这一问题,引入正则化因子对倾斜角方法进行改进,改进后的方法称为正则化倾斜角(R-Ta)方法,其计算公式为

R-Ta=tan-1(VDRTHDR+αTHDRmax),

其中,THDRmaxTHDR的极大值。倾斜角利用零值位置识别地质体边缘,所以在分母上增加αTHDRmax不会改变倾斜角的零值点位置,即不会改变Ta的识别精度,但是能够有效的解决倾斜角边缘识别方法中分母为零或者接近零时的计算不稳定性问题。正则化因子的引入提高了Ta法的稳定性,相应也会提高以Ta为基础构建的二阶导数方法Ta-THDR法的稳定性。

1.2 正则化Theta Map(R-cosθ)

cosθ边缘识别方法的计算公式[5]

cosθ=THDRASM,

其中,ASM= THDR2+VDR2。当ASM=0时或者接近0时, THDRASM计算变的不稳定。为了解决这一问题,引入正则化因子对cosθ法进行改进,改进后的方法称为正则化Theta Map(R-cosθ)方法,其计算公式为

R⁃cosθ=THDRASM+αASMmax,

其中,ASMmaxASM的极大值。

由于cosθ方法是利用极大值位置识别地质体的边缘位置,加入正则化因子会改变其极值位置,因此我们需要研究cosθ和R-cosθ两种方法的极大值位置。根据求取极大值的必要条件,对cosθ求导,并令其为0得

(cosθ)'=VDR·(VDRTHDR)'ASM3·THDR2=0,

当且仅当VDR=0时,(cosθ)'=0,即VDR的零值点位置对应cosθ的极值点位置,所以cosθ法和VDR法的识别结果相同。

同样对R-cosθ求导得

(R⁃cosθ)'=(THDR)'·αASMmax(ASM+αASMmax)2·ASM+VDR·(THDR'·VDR-THDR·VDR')(ASM+αASMmax)2·ASM

无法直接从上式判断出(R-cosθ)'=0的点,所以分两种情况对(R-cosθ)'进行讨论:

①当VDR=0时:

(R-cosθ)'= (THDR)'·αASMmax(ASM+αASMmax)2·ASM>0;

②当THDR'=0时:

(R-cosθ)'=- VDR·THDR·VDR'(ASM+αASMmax)2·ASM<0。

那么(R-cosθ)'=0的点位于VDR的零值点与THDR的极大值点之间,即R-cosθ的识别结果位于VDR法识别结果与THDR法识别结果之间,所以R-cosθ提高了cosθ的识别精度。

随着α增大,- VDR·THDR·VDR'(ASM+αASMmax)2·ASM增大,THDR的极值点与R-cosθ法极值点之间的距离减小,R-cosθ法的识别结果越接近THDR法识别结果,R-cosθ法的识别精度也就变得越高,但是α取值太大时,R-cosθ法的计算值就会很小,降低识别边界的分辨率,所以要合适选择α

1.3 正则化归一化标准差(R-NSTD)

归一化标准差的公式为[7]:

NSTD=σ(fz)σ(fx)+σ(fy)+σ(fz),

其中:σ(fx),σ(fy),σ(fz)分别为位场数据fx方向,y方向,z方向的一阶导数的标准差。当σ(fx)+σ(fy)+σ(fz)=0或者接近零时, σ(fz)σ(fx)+σ(fy)+σ(fz)计算变的不稳定。为了解决这个问题,引入正则化因子对NSTD法进行改进,改进后的方法称为正则化归一化标准差方法(R-NSTD)(式8):

其中:(σ(fx)+σ(fy)+σ(fz))max是位场数据在x方向,y方向,z方向一阶导数的标准差和极大值。 NSTD法属于数理统计类方法,不能通过解析式来研究在分母增加正则化因子后极值位置的变化,只能通过模型试算研究其极值位置的变化。

2 模型测试

本次实验选用了4个重力异常模型和1个磁力异常模型进行模型测试,各个模型参数见表1。通过对比正则化方法识别结果与比值类方法识别结果,验证本文提出的正则化方法的有效性。所有图中白色线框均表示模型体边界投影到平面上的位置,Ta方法与R-Ta方法图中白色虚线表示识别的边界。

R⁃NSTD=σ(fz)σ(fx)+σ(fy)+σ(fz)+α(σ(fx)+σ(fy)+σ(fz))max,

表1   使用模型参数说明

Table1  The parameters of models

模型类别形体个数长/m宽/m埋深/m间隔/m模型设计目的
模型A重力模型11608010~50测试比值类方法加入正则
化因子后的适用性
模型B重力模型21609010~5020测试比值类方法加入正则化
因子后,对于横向分辨率
的影响
1609010~50
模型C重力模型31604010~5090测试比值类方法加入正则
化因子后,对于不同埋深地
质体边缘识别的影响
1604025~65
1604040~80
模型D磁力模型11608010~50测试比值类方法加入正则化因子
后,对于磁力异常的适用性
模型E加噪(1%)
重力模型
11608010~50测试比值类方法加入正则
化因子后的稳定性

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2.1 模型A——单一直立六面体重力模型

图1为模型A的重力异常图,图2图1的比值类方法边缘识别结果图,图3图1的倾斜角总水平导数边缘识别结果图。通过模型A的试算,可以看出常规方法(即α=0)中的Ta法(图2a)和cosθ法(图2d)识别出的边界大于真实形体的边界;NSTD法(图2g)和Ta-THDR法(图3a)识别出的边界与真实形体边界基本一致,两个方法均在测网边部产生了由假极值引起的虚假边界,NSTD法中的假极值的幅值接近形体边界对应的真实极值的幅值。加入正则化因子后,R-Ta法的零值线位置没有变化(图2b);R-cosθ法的极值位置向形体真实边界靠近(图2e);R-NSTD法(图2h)和R-Ta-THDR法(图3b)的极值位置也向形体真实边界靠近,由于NSTD法和Ta-THDR法自身识别精度很高,所以R-NSTD法和R-Ta-THDR法的极值位置的变化不是很明显;R-NSTD法中的假极值幅值变小,但假极值仍然存在,假极值位置向形体边界靠近(图2h);R-Ta-THDR法消除了Ta-THDR中的假极值(图3b)。由此可以看出,正则化因子的引入,提高了cosθ法、NSTD法、Ta-THDR法的识别精度;削弱了NSTD法产生的虚假边界;消除了Ta-THDR法中的虚假边界;没有改变Ta法的识别精度。对比α=0.2与α=0.5的识别结果可以看出,随着正则化调节因子α取值增大,R-Ta法(图2c)的识别结果不变,R-cosθ法(图2f)、R-NSTD法(2l)、R-Ta-THDR法(图3c)的识别结果越接近真实边界,R-NSTD法(图2l)的假极值的幅值会减小,但假极值不会被消除,假极值的位置也不发生变化。但是α取值过大,则会改变比值类方法的均衡特性,使深部形体对应的极值的幅值变得更小,较小的极值会使深部形体的识别边界变宽缓、模糊。因此在后续的模型试算与实际资料处理中,R-Ta法、R-cosθ法、R-NSTD法的正则化调节因子α均选择0.5;由于R-Ta-THDR属于二阶导数类方法,其计算的极值较小,所以其正则化调节因子α选择0.2。

图1

图1   模型A重力异常

Fig.1   Gravity anomaly of model A


图2

图2   A模型比值类方法边缘识别结果对比

Fig.2   The ratio methods edge recognition results comparison map based on model A

a—Ta(α=0);b—R-Ta(α=0.2);c—R-Ta(α=0.5);d—cosθ(α=0);e—R-cosθ(α=0.2);f—R-cosθ(α=0.5);g—NSTD(α=0);h—R-NSTD(α=0.2);i—R-NSTD(α=0.5)


图3

图3   A模型倾斜角总水平导数边缘识别结果对比

Fig.3   The Ta-THDR method edge recognition results comparison map based on model A

a—Ta-THDR(α=0);b—R-Ta-THDR(α=0.2);c—R-Ta-THDR(α=0.5)


2.2 模型B——两个直立六面体组合重力模型

图4为模型B重力异常图,图5图4的比值类方法的边缘识别结果图,图6图4的倾斜角总水平导数方法边缘识别结果图。

图4

图4   模型B重力异常

Fig.4   Gravity anomaly of model B


图5

图5   B模型比值类方法边缘识别结果对比

Fig.5   The ratio methods edge recognition results comparison map based on model B

a—Ta;b—R-Ta;c—cosθ;d—R-cosθ;e—NSTD;f—R-NSTD


通过模型B的试算,可以看出Ta法(图5a)和cosθ法(图5c)识别出的相邻侧边界发生重叠,难以刻画两形体相邻边界;NSTD法(图5e)、Ta-THDR法(图6a)识别出的外侧边界均与真实形体外侧边界基本一致,识别出的内侧边界略微偏向形体内侧,两个方法都出现了由假极值引起的虚假边界,而且Ta-THDR法在相邻的形体之间产生了由计算不稳定性引起的局部突起(图6a)。加入正则化因子后,R-Ta法仍然识别不了内侧边界(图5b),R-cosθ法识别出的内侧边界与形体真实边界一致(图5d),R-NSTD法识别出的内侧边界更接近真实形体边界(图5f),R-Ta-THDR法消除了内侧边界之间的突起(图6b)。通过以上的对比研究发现,正则化因子的引入提高了R-cosθ法、NSTD法、Ta-THDR法的水平分辨率,但没有改变Ta法的水平分辨率。

图6

图6   B模型倾斜角总水平导数边缘识别结果对比

Fig.6   The Ta-THDR method edge recognition results comparison map based on model B

a—Ta-THDR;b—R-Ta-THDR


2.3 模型C——三个直立六面体组合重力模型

图7为模型C重力异常图,图8为模型C的比值类方法的边缘识别结果图。图9为模型C的倾斜角总水平导数方法的边缘识别结果图。

通过模型C的试算可以看出,随着形体埋深的增大,Ta法(图8a)、cosθ法(图8c)、NSTD法(图8e)、Ta-THDR法(9a)识别的边界逐渐外扩,距离真实形体的边界越来越远。NSTD法产生了假极值引起的虚假边界(图8e),Ta-THDR法在相邻的形体之间产生了由计算不稳定性引起的局部突起,并在测网边部存在虚假边界(图9a)。加入正则化因子后,没有改变R-Ta法对深部形体的识别能力;R-cosθ法(图8b)、R-NSTD法(图8f)、R-Ta-THDR法(图9b)识别出的深部形体边界与真实深部形体边界基本一致,但是识别的边界变得宽缓、模糊,这主要是因为正则化因子的引入改变了比值类方法的均衡特性,使深部形体对应极值的幅值变得更小。由此可以看出,正则化因子的引入,提高了cosθ法、NSTD法、Ta-THDR法对于深部形体的识别能力。

2.4 模型D——单一直立六面体磁力模型

模型D 为磁力模型。所有比值类位场边缘识别方法均受到磁化方向和磁力异常分量方向影响,所以基于比值类方法改进的正则化边缘识别方法也受磁化方向和磁力异常分量方向的影响。使用磁力异常进行边缘识别时,需要将磁异常转换为伪重力异常或者化极磁异常。图10a和图10b分别是该模型体磁力异常和化极磁力异常。图11为模型D采用比值类方法对其化极磁力异常进行边缘识别的结果图。图12为模型D的倾斜角总水平导数边缘识别结果图。通过模型D的试算可以看出磁力异常的Ta法(图11a)、cosθ法(图11c)、NSTD法(图11e)、Ta-THDR法(图12a)的识别结果都存在严重的虚假边界的影响,这是因为磁力异常值有正有负。其中,cosθ法产生的假极值的幅值与真实极值基本接近(图11c),NSTD法产生的假极值的幅值大于真实极值的幅值(图11e)。加入正则化因子后,R-Ta法识别边界没有变化(图11b);R-cosθ法(图11d)、R-NSTD法(图11f)仍然存在假极值,但是假极值幅值变小,假极值位置向形体边界靠近;R-Ta-THDR法消除了假极值引起的虚假边界(图12b)。由此可以看出,正则化因子的引入,削弱了cosθ法、NSTD法产生的虚假边界,消除了Ta-THDR法的虚假边界,没有改变Ta法的识别结果。

图7

图7   模型C重力异常

Fig.7   Gravity anomaly of model C


图8

图8   C模型比值类方法边缘识别结果对比

Fig.8   The ratio methods edge recognition results comparison map based on model C

a—Ta;b—R-Ta;c—cosθ;d—R-cosθ;e—NSTD;f—R-NSTD


图9

图9   C模型倾斜角总水平导数边缘识别结果对比

Fig.9   The Ta-THDR method edge recognition results comparison map based on model C

a—Ta-THDR;b—R-Ta-THDR


图10

图10   模型D磁力异常图与化极磁异常a—原始磁力异常;b—化极磁力异常

Fig.10   Magnetic anomaly and RTP magnetic anomaly map

a—magnetic anomaly map;b—RTP magnetic anomaly map


图11

图11   D模型比值类方法边缘识别结果对比

Fig.11   The ratio methods edge recognition results comparison map based on model D

a—Ta;b—R-Ta;c—cosθ;d—R-cosθ;e—NSTD;f—R-NSTD


图12

图12   D模型倾斜角总水平导数边缘识别结果对比

Fig.12   The Ta-THDR method edge recognition results comparison map based on model D

a—Ta-THDR;b—R-Ta-THDR


2.5 单一直立六面体加噪重力模型

图13为模型E的重力异常图,图14图13的比值类方法的边界识别结果图。图15图13的倾斜角总水平导数方法的边界识别结果图。在含噪模型E的试算中,计算各项导数时采用向上延拓提高导数计算的稳定性。

图13

图13   模型E重力异常

Fig.13   Gravity anomaly of model E


图14

图14   E模型比值类方法边缘识别结果对比

Fig.14   The ratio methods edge recognition results comparison map based on model E

a—Ta;b—R-Ta;c—cosθ;d—R-cosθ;e—NSTD;f—R-NSTD


图15

图15   E模型倾斜角总水平导数边缘识别结果对比

Fig.15   The Ta-THDR method edge recognition results comparison map based on model E

a—Ta-THDR;b—R-Ta-THDR


通过模型E的试算,可以看出加入噪声后, Ta法(图14a)、cosθ法(图14c)、NSTD法(图14e)、Ta-THDR法(图15a)均能识别出形体边界,但是在形体平面位置的四周出现了突起的噪声干扰,尤其以NSTD法(图14e)和Ta-THDR法(图15a)最为严重。加入正则化因子后,很好地压制了4种方法的噪声干扰,尤其是R-Ta-THDR中(图15b)的噪声干扰。当实际资料存在较大的噪声干扰时,应对实际数据进行适当的光滑,然后采用正则化方法进行边缘识别。

3 实际资料处理

图16显示的是中国南海某地卫星实测重力异常,图17图16比值类方法边缘识别结果图,图18图16的倾斜角总水平导数方法的边界识别结果。Ta法与R-Ta法图中白线虚线为识别出的地质体边界。

图16

图16   实测重力异常

Fig.16   Real gravity anomaly map


图17

图17   实测重力异常比值类方法边缘识别结果对比

Fig.17   The ratio methods edge recognition results comparison map based on real dataa—Ta;b—R-Ta;c—cosθ;d—R-cosθ;e—NSTD;f—R-NSTD


图18

图18   实测重力异常倾斜角总水平导数边缘识别结果对比

Fig.18   The Ta-THDR method edge recognition results comparison map based on real dataa—Ta-THDR;b—R-Ta-THDR


通过实际资料的处理可以看出,cosθ法(图17c)、NSTD法(图17e)和Ta-THDR法(图18a)产生由假极值引起的虚假边界,尤其NSTD法产生的虚假边界的影响最为严重,不能识别出地质体的真实边界(图17e)。加入正则化因子后,R-Ta法识别出的边界位置没有改变(图17b),R-cosθ法(图17d)、R-NSTD法(图17f)产生的虚假边界被削弱了,R-Ta-THDR消除了虚假边界,但同时也消除了一些细节信息(图18b)。实际资料的处理结果表明基于正则化方法的比值类位场边缘识别技术对于地质体边缘有较好的识别效果。水平分辨率从高到低依次是R-Ta-THDR、R-cosθ、R-NSTD、R-Ta。

4 结论

基于正则化的比值类位场边缘识别方法通过加入正则化因子,提高了比值类方法计算的稳定性,削弱了比值类方法受虚假边界的影响;同样提高了以比值类方法为基础构建的二阶导数方法的计算稳定性,如消除了Ta-THDR法虚假边界的影响。

本文通过理论推导证明了在比值类边缘识别方法中引入正则化因子没有改变Ta法的识别精度,但是提高了cosθ法的识别精度;通过模型试算发现在比值类边缘识别方法中引入正则化因子,提高了cosθ法、NSTD法、Ta-THDR法的识别精度、水平分辨率和对深部地质体的边界识别能力,降低了Ta法、cosθ法、NSTD法、Ta-THDR法受噪声干扰的影响;通过实际资料处理发现,正则化因子的引入,明显改善了cosθ、NSTD法、Ta-THDR的地质体边缘识别效果。

正则化边缘识别方法可以直接使用于重力异常,在使用于磁力异常时,由于受磁化方向和磁力异常分量方向影响,所以要将磁力异常转换为化极磁力异常或者伪重力异常,然后进行边缘识别。

The authors have declared that no competing interests exist.
作者已声明无竞争性利益关系。

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Evaluation of higher derivatives (gradients) of potential fields plays an important role in geophysical interpretation (qualitative and/or quantitative), as has been demonstrated in many approaches and methods. On the other hand, numerical evaluation of higher derivatives is an unstable process it has the tendency to enlarge the noise content in the original data (to degrade the signal-to-noise ratio). One way to stabilize higher derivative evaluation is the utilization of the Tikhonov regularization. In the submitted contribution we present the derivation of the regularized derivative filter in the Fourier domain as a minimization task by means of using the classical calculus of variations. A very important part of the presented approach is the selection of the optimum regularization parameter we are using the analysis of the C-norm function (constructed from the difference between two adjacent solutions, obtained for different values of regularization parameter). We show the influence of regularized derivatives on the properties of the classical 3D Euler deconvolution algorithm and apply it to high-sensitivity magnetometry data obtained from an unexploded ordnance detection survey. The solution obtained with regularized derivatives gives better focused depth-estimates, which are closer to the real position of sources (verified by excavation of unexploded projectiles).

曾小牛, 李夕海, 贾维敏 , .

位场各阶垂向导数换算的新正则化方法

[J]. 地球物理学报, 2015,58(4):1400-1410.

DOI:10.6038/cjg20150426      URL     Magsci     [本文引用: 1]

<p>位场垂向导数大量应用于位场数据处理与解释中.当前广泛采用的位场各阶垂向导数换算方法为基于Laplace方程并结合波数域和空间域方法的具有递推特性的ISVD(integrated second vertical derivative)算法.本文在位场垂向导数换算的正则化方法和径向平均功率谱的基础上,提出一种位场各阶垂向导数换算的新正则化方法.新正则化方法仅需通过分析位场径向平均功率谱来确定一个截止波数,即可稳定换算位场各阶垂向导数.理论模型和实测数据实验结果表明:(1)新正则化方法物理意义明确、计算简单,且各阶垂向导数换算的稳定性和精度明显优于ISVD算法;(2)在用新正则化方法求得各阶垂向导数的基础上,利用泰勒级数法可以获得大深度、高精度的位场向下延拓结果.</p>

Zeng X N, Li X H, Su J .

An adaptive iteration method for downward continuation of potential-field data from a horizontal plane:

Geophysics, 2015,58(4):1400-1410.

Magsci     [本文引用: 1]

栾文贵 .

场位解析延拓的稳定化算法

[J]. 地球物理学报, 1983,26(3):263-273.

DOI:      URL     Magsci     [本文引用: 1]

本文讨论场位解析延拓的稳定化算法。首先叙述问题的古典提法,并且为以后作准备,将它化成另一类不适定问题。接着建立问题解的连续依赖性估计。然后根据这个估计式,将问题化成求解一个条件变分问题。最后利用正则化方法解这个变分问题,得到问题解的一个稳定化的计算公式。

Luan W G .

Stabilization algorithm for analytical continuation of potential field

[J]. Chinese Journal of Geophysics, 1983,26(3):263-273.

Magsci     [本文引用: 1]

梁锦文 .

位场向下延拓的正则化方法

[J]. 地球物理学报, 1989,33(5):600-608.

URL     [本文引用: 1]

The four frequency response formulas of rcgularization methods for downward continuation of potential fields are discussed and their characteristics are analyzed. These methods can effectively restrict the oscillations due to the measuring errors or the high frequency disturbances. The trend of downward continuation is stable. The results of various trials are given.

Liang J W .

Regularization method for downward continuation of potential field

[J]. Chinese Journal of Geophysics, 1989,33(5):600-608.

[本文引用: 1]

Pašteka R, Karcol R, Kuŝnirák D , et al. Regcont: A Matlab based program for stable downward continuation of geophysical potential fields using Tikhonov regularization[J]. Computers & Geosciences, 2012(49):278-289.

[本文引用: 1]

Abedi M, Gholami A, Norouzi G H .

A stable downward continuation of airborne magnetic data: A case study for mineral prospectivity mapping in Central Iran

[J]. Computers & Geosciences, 2013, ( 52):269-280.

[本文引用: 1]

Li Y G, Sarah G R D, Richard A K , et al.

Enhancemant of magnetic data by stable downward continuation for UXO application

[J]. IEEE transactions on Geoscience and Remote Sensing, 2013,51(6):3605-3614.

DOI:10.1109/TGRS.2012.2220146      URL     [本文引用: 1]

The magnetic method has been proven to be a successful geophysical tool for the detection of unexploded ordnance (UXO). Aeromagnetic surveys are advantageous since they can acquire data over large areas. The downside is that magnetic anomalies due to multiple metallic targets can overlap significantly due to flight height restrictions. Such overlap combined with the acquisition noise may significantly decrease the signal-to-noise ratio of data. These adverse effects can mask the true level of contamination at a site during the initial assessment based on the magnetic method as well as decrease the overall effectiveness of discrimination during the active clearance stage. We propose a method to ameliorate these difficulties using stable downward continuation, which reconstructs the field at a lower observation height from the observed data. The stable algorithm formulates the downward continuation as an inverse problem and incorporates the expected power spectrum of UXO anomalies. The power spectrum preserves the spectral properties and subdues the amplification of high-frequency noise. Synthetic and field examples show that the algorithm can reliably reconstruct the magnetic anomaly at the ground surface within the limitation imposed by the noise. The reconstructed field exhibits significant enhancement compared to the original data.

赵亚博, 刘天佑 .

迭代Tikhonov正则化位场向下延拓方法及其在尕林铁矿的应用

[J]. 物探与化探, 2015,39(4):743-748.

DOI:10.11720/wtyht.2015.4.14      URL     Magsci     [本文引用: 1]

<p>解析延拓是一种广泛应用的位场处理方法,向下延拓可以压制深部地质体的影响,突出浅部异常。但是,向下延拓滤波因子是一个高通滤波器,会造成下延结果震荡,从而限制了该方法在实际资料中的应用。文中详细介绍并实现了迭代Tikhonov正则化向下延拓方法,在理论模型上将该方法与传统频率域延拓方法进行对比,表明迭代Tikhonov正则化向下延拓方法的有效性;并将该方法应用于青海尕林格铁矿区磁测资料的处理解释中,下延结果与钻探情况相符,说明在厚覆盖层的勘查区中,运用迭代Tikhonov正则化向下延拓方法能够有效地提高资料处理解释的效果。</p>

Zhao Y B, Liu T Y .

The iterative regularization method for downward continuation of potential fields and its application to the Galinge iron deposit

[J]. Geophysical and Geochemical Exploration, 2015,39(4):743-748.

Magsci     [本文引用: 1]

Verduzco B, Fairhead J D, Green C M, Mackenzie C .

The meter reader-New insights into magnetic derivatives for structural mapping

[J]. The Leading Edge, 2004,23(2):116-119.

DOI:10.1190/1.1651454      URL     [本文引用: 1]

王万银, 邱之云, 杨永 , .

位场边缘识别方法研究进展

[J]. 地球物理学进展, 2010,25(1):196-210.

DOI:10.3969/j.issn.1004-2903.2010.01.027      URL     Magsci    

<FONT face=Verdana>研究地质体的边缘位置是重、磁位场数据解释永恒的主题,也是其优势.最近几年,国内外利用重、磁位场进行地质体边缘识别研究的文章明显增多,但没有作者系统整理和对比各方法的优点和缺点,给使用者带来诸多不便.本文首先将现有重、磁位场边缘识别方法分为数理统计、数值计算和其他三大类,并概述了各类方法的研究现状;之后较详细总结了数值计算类中垂向导数、总水平导数、解析信号振幅、倾斜角、<EM>θ</EM>图这5种基本的边缘识别方法以及在这些基本方法之上发展起来的诸如倾斜角总水平导数、增强解析信号振幅等方法的研究历史和应用效果;并用理论模型对比了几种主要边缘识别方法的识别效果.通过以上总结、对比和分析,指出了重、磁位场边缘识别方法使用中需要注意的问题以及将来的研究重点及发展方向.</FONT>

Wang W Y, Qiu Z Y, Yang Y , et al.

Some advances in the edge recognition of the potential field

[J]. Progress in Geophysics, 2010,25(1):196-210.

Magsci    

Ma G Q, Huang D N, Cai Liu .

Step-edge detection filters for the Interpretation of potential field data

[J]. Pure and Applied Geophysics, 2016,173:795-803.

DOI:10.1007/s00024-015-1053-6      URL    

Edge detection is a useful tool in the interpretation of potential field data, and the existing edge detection filters are almost functions of first-order horizontal and vertical derivatives. We propose step-edge detection filters to improve the resolution of edge detection results, which use the functions of different-order derivatives to accomplish the edge detection task. We demonstrate the proposed filters on synthetic potential field data, and the results show that the new methods can recognize the edges of the sources more precisely and clearly. We also discuss the application effect of different step-edge detection filters. Lastly, we apply the proposed filters to real potential field data, and the recognized edges of the stratigraphic markers are more precise and clear.

Ma G. Q .

Edge detection of potential field data using improved local phase filter

[J]. Exploration Geophysics, 2013,44:36-41.

DOI:10.1071/EG12022      URL    

Edge detection is a requisite task in the interpretation of potential field data. There are many high-pass filters based on horizontal and vertical derivatives in use, such as total horizontal derivative, tilt angle, theta map, et al. In this paper, we present a new edge detection filter, which uses the combination of the different order horizontal derivatives to delineate the edges of the sources, called improved local phase (ILP) filter. The new filter is computationally stable, as it does not need the computation of the vertical derivatives of potential field data. The new filter is tested on synthetic and real potential field data. The resolving power of the ILP filter is tested by comparing the results with those obtained by the other filters. The advantage of the ILP filter in the edge detection of potential field data is due to the fact that it can display the edges of the causative sources more precisely and clearly, and can bring out more subtle details.

周帅, 黄大年, 焦健 .

基于三维构造张量的位场边界识别滤波器

[J]. 地球物理学报, 2016,59(10):3847-3858.

DOI:10.6038/cjg20161028      URL    

地质体构造边界位置的确定是位场数据解释中的一项重要工作,现有很多基于位场梯度张量数据的边界检测滤波器,但存在识别边界位置模糊且无法均衡深浅地质体异常的缺点.本文定义了位场数据的三维构造张量,并提出基于位场构造张量的边界滤波器.为了同时显示不同振幅异常的边界位置,对新定义的滤波器进行归一化处理.在高阶均衡滤波器的计算中需要计算位场的垂向高阶导数,本文引入一种计算的稳定算法,基于拉普拉斯方程利用位场水平导数求解垂向导数,可减小垂向导数计算中产生的误差.将定义的滤波器应用到合成的重磁数据中证明了新方法相比传统的滤波器能更加清晰、准确地圈定边界位置,而且针对同时含有正负异常的地质情况,可避免产生额外的错误边界.最后将新的滤波器应用到实测的重磁数据的解释中,结果显示基于构造张量的滤波器可更准确清晰地划分出断裂的边界位置,发现更多的构造细节.

Zhou S, Huang D N, Jiao J .

Construction of potential Field Boundary recognition filter based on three-dimensional Construction of Zhang Liang

[J]. Journal of Geophysics, 2016,59(10):3847-3858.

颜廷杰, 吴燕冈, 袁园 , .

应用加强解析信号倾斜角进行位场数据的边界检测

[J]. 地球物理学报, 2016,59(7):2694-2702.

URL    

边界检测在地球物理位场数据解释中占有重要位置.现有的传统边界识别方法有的不能同时显示不同振幅的异常边界,有的虽然能均衡不同振幅的异常,但识别出来的边界信息中含有一些额外的错误的边界信息,尤其是当测量的异常中同时含有正异常和负异常时.目前已有的去除额外错误边界信息的方法存在着一定的人为主观性.为了解决这些问题,本文定义了加强解析信号倾斜角来进行地质体边界识别.通过模型试验证明了该方法不仅能同时清晰地识别深部和浅部地质体的边界,而且能有效地避免引入一些错误边界信息.最后将该方法应用到四川盆地的重力异常数据中,并取得了良好边界结果.

Yan T J, Wu Y G, Yuan Y , et al.

Boundary Detection of potential Field data by strengthening the inclination Angle of Analytic signal

[J]. Journal of Geophysics, 2016,59(7):2694-2702.

陈国强, 马国庆 .

位场数据解释的Theta-Depth法

[J]. 地球物理学报, 2016,59(6):2225-2231.

DOI:10.6038/cjg20160625      URL    

Theta图是利用位场(重磁)数据识别边界的常用方法,其表达式为重磁异常水平变化与垂直变化的比值函数.该方法计算浅源地质体边界的效果较好,而由于深源位场数据在换算过程中会产生趋同效应,在深源地质体识别应用中计算结果不准确,为此,本文提出Theta-Depth法并进行地质体埋深的计算.首先给出直接利用Theta图像进行场源体深度估算的方法,然后推导出基于Theta导数的线性方程来自动估算场源位置参数,本文方法可有效地利用Theta图像的特征为约束条件来提高反演结果的精度.理论模型试验证明本文提出的Theta-Depth法能有效地计算出场源体位置和深度.将该方法应用于满都拉地区实测磁数据的解释,帮助圈定了矿脉的分布.

Chen G Q, Ma G Q .

Theta-Depth method for potential Field data interpretation

[J]. Journal of Geophysics, 2016,59(6):2225-2231.

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