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位场导数换算是重磁数据处理与解释的基本方法,但其不稳定性限制了在实际资料中的应用,且目前的改进措施并未能较好地解决导数计算精度和不稳定性之间的矛盾问题.针对于此,本文在波数域导数迭代法基础上,提出了迭代差分视导数.该方法是在导数迭代法的信号压制区内,通过对不同迭代次数计算结果之差进行合理修正实现的;同时对比分析了视导数与常规导数算子的滤波特性;并通过导数模型实验验证了视导数具有较强的计算稳定性和较高的异常分辨率.另外,本文还对三种常用边界识别方法进行了改进来进一步突出场源边界的异常特征,并将视导数应用到了这些边界识别方法之中.组合模型试验表明,本文提出的边界识别方法改进措施有效地提高了原方法对边界的精细检测能力,基于视导数的边界识别方法则不仅具有较强的抗干扰能力,而且更加精确地检测出了地质体的边界.最后,将视导数和基于视导数的边界识别方法应用到了黑龙江虎林盆地重力异常中,结果显示视导数不仅具有较强的计算稳定性,而且清晰地展示出了异常间的相互关系;同时,基于视导数的边界识别方法准确、清晰地识别出了地质体的边界,还展示出了更多的边界细节信息.
The conversion of bit field derivation is the basic method of data processing and interpretation of gravity and magnetic data. However, its instability limits the application in actual data, and the current improvement measures do not solve the problem of precision and instability of derivative calculation In this paper, based on the wave number domain derivative iterative method, this paper proposes an iterative differential visual derivative, which is based on the derivative of the derivative iterative method, through the reasonable correction of the difference between the calculated results of different iterations And the filtering characteristics of the apparent derivative and the normal derivative operator are compared and analyzed at the same time. The derivative of the derivative model shows that the apparent derivative has strong computational stability and high resolution. In addition, The boundary identification method is improved to further highlight the abnormal characteristics of the field source boundary and the apparent derivative is applied to these boundary identification methods.Mixing model tests show that the proposed method of boundary recognition improves the efficiency of the original method to the boundary Of the fine detection ability, based on visual derivatives of the boundary recognition method not only has a strong anti-interference ability, but also more accurate inspection The boundary of geologic body was detected.Finally, the method of boundary-recognition based on apparent-derivative and apparent-derivative was applied to the gravity anomalies in the Hulin basin of Heilongjiang Province. The results show that the apparent derivative not only has strong computational stability but also clearly shows At the same time, the method of boundary recognition based on visual derivatives identifies the boundaries of geologic bodies accurately and clearly, and shows more details of the boundaries.