重力异常及其梯度张量数据快速解释技术研究
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摘要
重力勘探数据由重力异常数据及其梯度数据集构成，可以通过相关重力仪或重力梯度仪在卫星、航空、地面和海洋等重力勘探过程中获得。重力勘探数据从不同侧面反映了产生重力异常的场源的空间分布形态和密度变化规律，是由地球物理场现象解释地质对象的基本数据和研究出发点。为了更好地利用数据进行快速解释，通常需要针对不同的地质研究对象，选取不同的梯度张量分量或结合重力异常形成数据组合，建立与之相适应的解释方法。不同的梯度张量分量反映了同一地质体在不同方向的变化规律，其分辨能力和探测能力也随方向变化而存在差异。因此，本文在理论和实践环节开展解释方法技术研究工作：研究不同数据类型和组合的地质目标发现能力；研究不同数据组合针对场源的快速解释方法。
首先从理论上，通过模型正演，对重力异常数据和梯度数据进行了评估分析，为解释工作中对重力异常以及梯度张量分量的选取提供依据。在重力垂向一阶导数和重力异常之间关系的对比研究基础上，对其他张量分量与重力异常分辨能力以及各个张量分量之间的分辨能力展开了系统对比分析。研究结果表明重力梯度张量分量在相对浅部范围内具有更高的分辨能力，而相对深部探测中并不具有优势，高精度梯度张量分量的优势主要在于可以提供更多高频的细节信息，从而更加详细地对地质体进行解释。另外，从应用角度，文中分析了测线布设位置和测线间距对重力异常及其梯度的影响，发现随着测线间距的增大和测线位置偏离地质体时，梯度张量分量仍然可以较完整地给出场源的信息，而重力异常及计算梯度异常均不能提供较完整的信息。但相较于重力异常，计算所得的张量梯度分量可以从不同侧面对地质体进行更加精细的描述。可以看出，在重力异常及其梯度数据的解释工作中，梯度张量数据以及张量多分量联合解释方法具有更大的优势。
在传统解释方法基础上，本文开展快速解释方法的研究，强调同时利用更多的张量分量，优化梯度张量分量组合，从而推进多类数据联合解释技术的完善，加强解释过程中的信息融合。重力异常及其梯度数据的解释工作，通常需要从数据中获取有关场源的三个方面信息：水平位置、深度范围和物性参数。因此本论文主要从这三种参数的确定展开新方法的研究。水平位置的确定方法通常利用边界识别方法；深度范围参数的确定需要深度计算方法来完成；物性参数的获取除了传统物性反演之外，可由快速成像方法给出与物性相关的量值。
近年迅速发展的边界识别方法由于可以快速且准确地确定地质体边界位置、构造水平位置等而被广泛关注。分析表明，最常用的传统方法，如Tilt梯度（斜导数）、Theta图等方法，在深部地质体边界位置确定中误差较大，且对细节信息的提取能力不足。文中首先对二者的相互关系进行分析，论述了这两种方法的相关关系，将其统一归类为“角度边界识别方法”，在此基础上，建立其他相类似识别方法，如反正弦等角度边界识别方法。由模型计算和对比分析发现，这些方法在地质体边界识别中效果基本相同，对解释对象的细节信息提取能力不足。为了改善细节信息提取能力，提出了基于标准差计算的改进型的“角度边界识别方法”，其计算过程是：先求取重力异常三个方向梯度在窗口内的标准差，然后再按照常规角度边界识别方法求取结果。模型检验和分析表明，改进后的方法可以探测识别更多和实际情况相吻合的细节特征。将该方法应用于实际数据处理中，取得了良好的效果。为了改善传统方法在深度地质体边界识别中的偏移问题，提出了“平面全张量梯度角度边界识别方法”：将水平面视作整个与垂向方向相对的分量，根据梯度分量矢量特征，类似于角度边界识别方法进行比值计算。模型计算结果表明，由于利用了更多的张量分量，使得边界位置的确定更加准确。文中还对反双曲斜导数边界识别方法在复杂的正、负剩余密度同时存在时产生虚假边界的缺陷进行了改进，给出了重力异常和梯度分量的数据联合解释的一种途径。模型和实测数据处理表明，改进后的方法在应用中更具优势。
重力异常场源深度计算的方法经历了漫长的发展历史，形成了针对不同的场源类型和地质研究对象的不同深度计算方法。但是，在实际应用中，目前还无法找到一种包罗万象的万能方法来解决复杂的地质问题，每一种方法均有完善和改进的研究空间。文中首先基于Tilt-depth（斜导数深度计算方法）方法，推导建立了可应用于球体（点源）等三度体模型的重力异常深度计算方法，理论模型表明了该方法具有较准确的计算结果。为了更进一步体现张量分量解释手段的优势，将张量曲率矩阵引入到深度计算中，建立了基于张量曲率矩阵的深度计算方法，该方法类似于Tilt-depth方法的计算，只是将Tilt-depth方法中垂向导数替换为张量曲率矩阵的特征值，提高了水平分辨能力，从而使得深度计算结果也更加准确。另外，Tilt-depth方法以及张量曲率矩阵深度计算方法均是单独针对正或负剩余密度体进行计算，为了更快捷地对复杂地质情况进行计算，同样利用了重力异常和梯度相结合的办法，改进了张量曲率矩阵的特征值，从而可以对正、负剩余密度体同时存在的情况直接计算深度。其后建立了基于全张量不变量的深度计算方法，利用重力异常和全张量不变量的比值求取深度范围，发挥了张量不变量的优势特征，可以简单快捷地计算出地质体的埋深。建立了不同的模型试验并选取了多个实际重力数据对这些方法分别进行检验，均可以得到很好的应用结果，表明这些新方法的优越性和实用性。
快速成像方法在物性参数的计算中具有快速、耗内存小等优势，此类方法虽然不能给出真正的物性参数，但这种与物性相关的参数在地质解释中具有重要的价值。因此，本文针对传统的极值点深度计算方法（DEXP）进行了相应的评价，对其优点、误差产生的原因等进行了分析，发现DEXP方法在针对重力一阶导数计算成像时误差更小。而广义线性反演成像方法是一种基于垂向导数的成像方法，因此将DEXP方法深度加权因子引入到广义线性反演成像计算中，使得广义线性反演成像可以得到更加合理、准确的成像结果。为了更进一步发挥梯度张量分量解释的优势，在广义线性反演成像基础上推导建立了梯度张量的广义线性反演成像方法。模型试验和实测数据处理表明其分辨能力更高，结果也更加准确。
这些新的解释方法旨在实现重力异常及其梯度数据的快速解释工作，文中的模型数据和实际数据分析表明，利用这些方法可以从水平位置、深度范围和物性参数的计算三个方面对场源体进行快速的解释，且均可以得到高精度的结果，说明文中所建立的方法具有很好的应用价值。
Gravity prospecting data is composed of gravity anomaly data and full tensorgradient (FTG) data. It can be obtained by using satellite, airborne, ground and marinegravimeter and gradiometer. The gravity data reflect the information of spatialdistribution and density variation of geologic source. It can be used as the basis dataand starting point to interpret the geologic objects. In order to interpret the gravity andgravity gradient data rapidly, it is needed to select different gradient tensorcomponents or combine gravity anomaly to establish interpretation method fordifferent geological research objects. The response of different gradient tensorcomponents are not identical, which from the same geological source. The resolutionand detection ability are also different from each components. Therefore, in this paper,we aim to study on the interpretation method from theory and practice: to study on thedetectably of different data components, and to study on the rapid interpretationmethod from the combination of different components.
Firstly, we evaluate and analyze the gravity anomaly and gravity gradient tensor(GGT) data by using forward model. These can provide the basis for the selection ofgravity and the gradient components. Based on the comparative research of therelationship between the gravity anomaly and the vertical derivative, we also make acomparative analysis of the resolution between the gravity anomaly and the gradientcomponents. And the study of resolution between each tensor components is alsoanalyzed. The results show that GGT components have higher resolution within thescope of the relatively shallow, but do not have advantage in the relatively deeperexploration. The superiorities of gradient tensor components lie in that they canprovide more details information of high frequency so that geological body can beexplained in detail. In addition, in this paper, we analyze the influence of the linelayout position and line spacing for the gravity anomaly and gradient components.The results show that with the increase of line spacing and line position deviationfrom the geologic sources, gradient tensor components can still give the relativelyintact geological information. The calculation results of the gradient tensorcomponents cannot provide more information. But they can give more detaileddescription of geological body from different sides. As a result, it can be seen in theinterpretation of the gravity anomaly and the gradient tensor data, gradient tensor data and multi-component joint interpretation method have more advantages.
In view of this, in order to realize the perfect rapid interpretation method in thispaper, we establish the rapid interpretation method based on the traditionalinterpretation method to consider using more tensor component and optimize thegradient tensor component combination. To complete the interpretation work of thegravity anomaly and gradient tensor data, it is usually needed to obtain information ofgeologic source on the three aspects: horizontal position, depth scope and physicalparameters. Therefore, the mainly research theme of this thesis is about new methodsto determine this three parameters. Horizontal position usually is determined by edgedetection method, the depth scope parameters calculated by depth calculation method,and acquisition of physical parameters by traditional inversion method or by rapidimaging approach to obtain the related physical properties.
The edge detection methods are widely used for they play an important role ingeologic interpretation, and the method has a great development in recent years. Themost commonly used traditional methods such as Tilt angle, Theta map method cangenerate lager error in deep geological edge detection, and they also lack the ability toextract more detail information. In this paper, we firstly analyze the relationshipbetween the two methods, and discuss the same theoretical framework, and then weuniform them as angle edge detection method. Based on this, we establish the otherangle edge detection methods such as arcsine angle edge detection method. Themodel tests show that all of these methods have same effect in edge detection. Inorder to improve the precision and the detectability of details, the angle edge detectionmethod is established based on a standard deviation calculation involving followingtwo steps: step1is calculation of standard deviation of the three directionalderivatives within windows, while step2is calculation of the trigonometric as normalangle edge detection. The model tests show that the new method can detect moredetail information which coincides with the real situation. Then we apply the methodon real field data, and good results have been achieved. In order to improve the offsetproblem of traditional angle method in deep geological edge detection, a new planefull tensor gradient angle edge detection method is established: Regarding horizontalplane as a whole relative to the vertical component, we perform a similar ratiocalculation of Tilt angle and Theta map, and propose a plane full tensor gradient angleedge detection and enhanced approach. Because of using more tensor component,made it more accurate to determine the edges of geologic sources. In this paper, theimproved inverse hyperbolic angle method overcomes the limitation of the original method can produce false edges when positive and negative residual density exist atthe same time. The new improved method is established by combining the gravityanomaly and gradient components. And the model tests and measured data processingresults demonstrate that the superiority of the improved method.
There are many depth calculation methods for geologic sources, because of thedifferent types of geologic body and the research object need different depthcalculation methods. In this paper, we firstly establish an improved Tilt-depth method,which can be used to calculate the three-dimensional model such as sphere (pointsource) model. The model tests show that the method can be used to calculate thedepth accurately. To further display the advantage of gradient tensor componentinterpretation method, the curvature tensor matrix (CGTM) is introduced into thedepth calculation. We established a new depth calculation method based on thecurvature tensor matrix. The method is similar to tilt-depth method, and ourimprovement to this method is that the vertical derivative of the tilt angle is replacedby an eigenvalue of the CGTM. The improvement of horizontal resolution, so as tomake the depth calculation results more accurate. Both of the Tilt-depth method andthe CGTM-depth method are calculated separately in view of the positive or negativeresidual density body. In order to calculation the depth of geologic sources morequickly on the complicated geological conditions. We also use the gravity anomalycombined with the gravity gradient components, and improve the eigenvalues ofCGTM. Thus the improved approach can be used to directly calculate the depth ofgeologic sources exist both the positive and negative densities. Finally, we establisheda new depth calculation method based on the full tensor invariant. The depth range iscalculated using the ratio of gravity anomaly and the tensor invariant. It can amplifythe superiority of the tensor invariant in the gradient tensor data interpretation. Andthe new method also is a quick and simple method to obtain the depth of geologicsources. We use different model data and the filed data to test the method,respectively. And all of the results show that the method can get good applicationresults. They show the superiority and practicability of the new method.
The rapid imaging method is usually used in the calculation of physicalparameters for the advantages such as they are fast and need small internal storage.Although these imaging method cannot give the real physical parameters, this resultswhich is related to the physical parameters are very useful in the geologicinterpretation. Therefore, in this paper, we firstly analyze the conventional DEXPmethod aimed to make certain the advantages, the causes of error. We find that it can get more little error when use the vertical derivative to calculate the imaging results.Based on this, the weighted factor is introduced into the generalized linear inversionimaging depth calculation, so as to make the generalized linear inversion imaging canbe more reasonable and accurate imaging results. To further develop the advantagesof gradient tensor component, based on the generalized linear inversion imaging, weestablish the gradient tensor generalized linear inversion imaging method. The modeltests and real data processing results show that its resolution is higher, and the result ismore accurate.
All of the new interpretation methods are designed to realize the rapidinterpretation work of the gravity anomaly and the gradient tensor data. In this paper,the model data and real data analysis indicate that these methods can be used to makea rapid interpretation of the data from three aspects include the horizontal position,depth scope and physical property parameters of the geologic source. All of the newmethods can get high precision results, it demonstrated that the new methods havegood application value.
首先从理论上，通过模型正演，对重力异常数据和梯度数据进行了评估分析，为解释工作中对重力异常以及梯度张量分量的选取提供依据。在重力垂向一阶导数和重力异常之间关系的对比研究基础上，对其他张量分量与重力异常分辨能力以及各个张量分量之间的分辨能力展开了系统对比分析。研究结果表明重力梯度张量分量在相对浅部范围内具有更高的分辨能力，而相对深部探测中并不具有优势，高精度梯度张量分量的优势主要在于可以提供更多高频的细节信息，从而更加详细地对地质体进行解释。另外，从应用角度，文中分析了测线布设位置和测线间距对重力异常及其梯度的影响，发现随着测线间距的增大和测线位置偏离地质体时，梯度张量分量仍然可以较完整地给出场源的信息，而重力异常及计算梯度异常均不能提供较完整的信息。但相较于重力异常，计算所得的张量梯度分量可以从不同侧面对地质体进行更加精细的描述。可以看出，在重力异常及其梯度数据的解释工作中，梯度张量数据以及张量多分量联合解释方法具有更大的优势。
在传统解释方法基础上，本文开展快速解释方法的研究，强调同时利用更多的张量分量，优化梯度张量分量组合，从而推进多类数据联合解释技术的完善，加强解释过程中的信息融合。重力异常及其梯度数据的解释工作，通常需要从数据中获取有关场源的三个方面信息：水平位置、深度范围和物性参数。因此本论文主要从这三种参数的确定展开新方法的研究。水平位置的确定方法通常利用边界识别方法；深度范围参数的确定需要深度计算方法来完成；物性参数的获取除了传统物性反演之外，可由快速成像方法给出与物性相关的量值。
近年迅速发展的边界识别方法由于可以快速且准确地确定地质体边界位置、构造水平位置等而被广泛关注。分析表明，最常用的传统方法，如Tilt梯度（斜导数）、Theta图等方法，在深部地质体边界位置确定中误差较大，且对细节信息的提取能力不足。文中首先对二者的相互关系进行分析，论述了这两种方法的相关关系，将其统一归类为“角度边界识别方法”，在此基础上，建立其他相类似识别方法，如反正弦等角度边界识别方法。由模型计算和对比分析发现，这些方法在地质体边界识别中效果基本相同，对解释对象的细节信息提取能力不足。为了改善细节信息提取能力，提出了基于标准差计算的改进型的“角度边界识别方法”，其计算过程是：先求取重力异常三个方向梯度在窗口内的标准差，然后再按照常规角度边界识别方法求取结果。模型检验和分析表明，改进后的方法可以探测识别更多和实际情况相吻合的细节特征。将该方法应用于实际数据处理中，取得了良好的效果。为了改善传统方法在深度地质体边界识别中的偏移问题，提出了“平面全张量梯度角度边界识别方法”：将水平面视作整个与垂向方向相对的分量，根据梯度分量矢量特征，类似于角度边界识别方法进行比值计算。模型计算结果表明，由于利用了更多的张量分量，使得边界位置的确定更加准确。文中还对反双曲斜导数边界识别方法在复杂的正、负剩余密度同时存在时产生虚假边界的缺陷进行了改进，给出了重力异常和梯度分量的数据联合解释的一种途径。模型和实测数据处理表明，改进后的方法在应用中更具优势。
重力异常场源深度计算的方法经历了漫长的发展历史，形成了针对不同的场源类型和地质研究对象的不同深度计算方法。但是，在实际应用中，目前还无法找到一种包罗万象的万能方法来解决复杂的地质问题，每一种方法均有完善和改进的研究空间。文中首先基于Tilt-depth（斜导数深度计算方法）方法，推导建立了可应用于球体（点源）等三度体模型的重力异常深度计算方法，理论模型表明了该方法具有较准确的计算结果。为了更进一步体现张量分量解释手段的优势，将张量曲率矩阵引入到深度计算中，建立了基于张量曲率矩阵的深度计算方法，该方法类似于Tilt-depth方法的计算，只是将Tilt-depth方法中垂向导数替换为张量曲率矩阵的特征值，提高了水平分辨能力，从而使得深度计算结果也更加准确。另外，Tilt-depth方法以及张量曲率矩阵深度计算方法均是单独针对正或负剩余密度体进行计算，为了更快捷地对复杂地质情况进行计算，同样利用了重力异常和梯度相结合的办法，改进了张量曲率矩阵的特征值，从而可以对正、负剩余密度体同时存在的情况直接计算深度。其后建立了基于全张量不变量的深度计算方法，利用重力异常和全张量不变量的比值求取深度范围，发挥了张量不变量的优势特征，可以简单快捷地计算出地质体的埋深。建立了不同的模型试验并选取了多个实际重力数据对这些方法分别进行检验，均可以得到很好的应用结果，表明这些新方法的优越性和实用性。
快速成像方法在物性参数的计算中具有快速、耗内存小等优势，此类方法虽然不能给出真正的物性参数，但这种与物性相关的参数在地质解释中具有重要的价值。因此，本文针对传统的极值点深度计算方法（DEXP）进行了相应的评价，对其优点、误差产生的原因等进行了分析，发现DEXP方法在针对重力一阶导数计算成像时误差更小。而广义线性反演成像方法是一种基于垂向导数的成像方法，因此将DEXP方法深度加权因子引入到广义线性反演成像计算中，使得广义线性反演成像可以得到更加合理、准确的成像结果。为了更进一步发挥梯度张量分量解释的优势，在广义线性反演成像基础上推导建立了梯度张量的广义线性反演成像方法。模型试验和实测数据处理表明其分辨能力更高，结果也更加准确。
这些新的解释方法旨在实现重力异常及其梯度数据的快速解释工作，文中的模型数据和实际数据分析表明，利用这些方法可以从水平位置、深度范围和物性参数的计算三个方面对场源体进行快速的解释，且均可以得到高精度的结果，说明文中所建立的方法具有很好的应用价值。
Gravity prospecting data is composed of gravity anomaly data and full tensorgradient (FTG) data. It can be obtained by using satellite, airborne, ground and marinegravimeter and gradiometer. The gravity data reflect the information of spatialdistribution and density variation of geologic source. It can be used as the basis dataand starting point to interpret the geologic objects. In order to interpret the gravity andgravity gradient data rapidly, it is needed to select different gradient tensorcomponents or combine gravity anomaly to establish interpretation method fordifferent geological research objects. The response of different gradient tensorcomponents are not identical, which from the same geological source. The resolutionand detection ability are also different from each components. Therefore, in this paper,we aim to study on the interpretation method from theory and practice: to study on thedetectably of different data components, and to study on the rapid interpretationmethod from the combination of different components.
Firstly, we evaluate and analyze the gravity anomaly and gravity gradient tensor(GGT) data by using forward model. These can provide the basis for the selection ofgravity and the gradient components. Based on the comparative research of therelationship between the gravity anomaly and the vertical derivative, we also make acomparative analysis of the resolution between the gravity anomaly and the gradientcomponents. And the study of resolution between each tensor components is alsoanalyzed. The results show that GGT components have higher resolution within thescope of the relatively shallow, but do not have advantage in the relatively deeperexploration. The superiorities of gradient tensor components lie in that they canprovide more details information of high frequency so that geological body can beexplained in detail. In addition, in this paper, we analyze the influence of the linelayout position and line spacing for the gravity anomaly and gradient components.The results show that with the increase of line spacing and line position deviationfrom the geologic sources, gradient tensor components can still give the relativelyintact geological information. The calculation results of the gradient tensorcomponents cannot provide more information. But they can give more detaileddescription of geological body from different sides. As a result, it can be seen in theinterpretation of the gravity anomaly and the gradient tensor data, gradient tensor data and multi-component joint interpretation method have more advantages.
In view of this, in order to realize the perfect rapid interpretation method in thispaper, we establish the rapid interpretation method based on the traditionalinterpretation method to consider using more tensor component and optimize thegradient tensor component combination. To complete the interpretation work of thegravity anomaly and gradient tensor data, it is usually needed to obtain information ofgeologic source on the three aspects: horizontal position, depth scope and physicalparameters. Therefore, the mainly research theme of this thesis is about new methodsto determine this three parameters. Horizontal position usually is determined by edgedetection method, the depth scope parameters calculated by depth calculation method,and acquisition of physical parameters by traditional inversion method or by rapidimaging approach to obtain the related physical properties.
The edge detection methods are widely used for they play an important role ingeologic interpretation, and the method has a great development in recent years. Themost commonly used traditional methods such as Tilt angle, Theta map method cangenerate lager error in deep geological edge detection, and they also lack the ability toextract more detail information. In this paper, we firstly analyze the relationshipbetween the two methods, and discuss the same theoretical framework, and then weuniform them as angle edge detection method. Based on this, we establish the otherangle edge detection methods such as arcsine angle edge detection method. Themodel tests show that all of these methods have same effect in edge detection. Inorder to improve the precision and the detectability of details, the angle edge detectionmethod is established based on a standard deviation calculation involving followingtwo steps: step1is calculation of standard deviation of the three directionalderivatives within windows, while step2is calculation of the trigonometric as normalangle edge detection. The model tests show that the new method can detect moredetail information which coincides with the real situation. Then we apply the methodon real field data, and good results have been achieved. In order to improve the offsetproblem of traditional angle method in deep geological edge detection, a new planefull tensor gradient angle edge detection method is established: Regarding horizontalplane as a whole relative to the vertical component, we perform a similar ratiocalculation of Tilt angle and Theta map, and propose a plane full tensor gradient angleedge detection and enhanced approach. Because of using more tensor component,made it more accurate to determine the edges of geologic sources. In this paper, theimproved inverse hyperbolic angle method overcomes the limitation of the original method can produce false edges when positive and negative residual density exist atthe same time. The new improved method is established by combining the gravityanomaly and gradient components. And the model tests and measured data processingresults demonstrate that the superiority of the improved method.
There are many depth calculation methods for geologic sources, because of thedifferent types of geologic body and the research object need different depthcalculation methods. In this paper, we firstly establish an improved Tilt-depth method,which can be used to calculate the three-dimensional model such as sphere (pointsource) model. The model tests show that the method can be used to calculate thedepth accurately. To further display the advantage of gradient tensor componentinterpretation method, the curvature tensor matrix (CGTM) is introduced into thedepth calculation. We established a new depth calculation method based on thecurvature tensor matrix. The method is similar to tilt-depth method, and ourimprovement to this method is that the vertical derivative of the tilt angle is replacedby an eigenvalue of the CGTM. The improvement of horizontal resolution, so as tomake the depth calculation results more accurate. Both of the Tilt-depth method andthe CGTM-depth method are calculated separately in view of the positive or negativeresidual density body. In order to calculation the depth of geologic sources morequickly on the complicated geological conditions. We also use the gravity anomalycombined with the gravity gradient components, and improve the eigenvalues ofCGTM. Thus the improved approach can be used to directly calculate the depth ofgeologic sources exist both the positive and negative densities. Finally, we establisheda new depth calculation method based on the full tensor invariant. The depth range iscalculated using the ratio of gravity anomaly and the tensor invariant. It can amplifythe superiority of the tensor invariant in the gradient tensor data interpretation. Andthe new method also is a quick and simple method to obtain the depth of geologicsources. We use different model data and the filed data to test the method,respectively. And all of the results show that the method can get good applicationresults. They show the superiority and practicability of the new method.
The rapid imaging method is usually used in the calculation of physicalparameters for the advantages such as they are fast and need small internal storage.Although these imaging method cannot give the real physical parameters, this resultswhich is related to the physical parameters are very useful in the geologicinterpretation. Therefore, in this paper, we firstly analyze the conventional DEXPmethod aimed to make certain the advantages, the causes of error. We find that it can get more little error when use the vertical derivative to calculate the imaging results.Based on this, the weighted factor is introduced into the generalized linear inversionimaging depth calculation, so as to make the generalized linear inversion imaging canbe more reasonable and accurate imaging results. To further develop the advantagesof gradient tensor component, based on the generalized linear inversion imaging, weestablish the gradient tensor generalized linear inversion imaging method. The modeltests and real data processing results show that its resolution is higher, and the result ismore accurate.
All of the new interpretation methods are designed to realize the rapidinterpretation work of the gravity anomaly and the gradient tensor data. In this paper,the model data and real data analysis indicate that these methods can be used to makea rapid interpretation of the data from three aspects include the horizontal position,depth scope and physical property parameters of the geologic source. All of the newmethods can get high precision results, it demonstrated that the new methods havegood application value.
引文
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