重磁异常的快速均衡边界识别方法

Fast balanced edge identification method for gravity and magnetic anomalies

边界识别是位场数据解释中一项重要任务,可用于资源探测等领域,是目前研究的热点问题之一。对于深部异常体目标,采用传统的边界识别方法易出现模糊、发散、变形等问题,而改进的方法大多采用高阶导数,虽然能够很好地识别出深部异常体边界,但是计算复杂,易受噪声干扰。为了改善以上问题,提出了一种稳定的快速边界识别方法,仅利用符号函数和重磁垂直导数数据,即可均衡识别不同深度的目标,且避免了高阶导数的计算。通过理论模型的实验与对比,验证了方法的便捷性、有效性、抗斜磁化能力以及抗噪能力。同时,应用实测数据验证了方法在复杂重磁环境下,能够准确清晰地分辨出异常体,可节约相关研究人员的大量时间与精力,具有很好地应用前景。

Edge identification is an important task in the interpretation of potential field data and can be used in the field of resource detection and so on,which is one of the hot topics in current research.For deep anomalous targets,the traditional edge identification methods are prone to blur,divergence,deformation and other problems.Most of the improved methods use high-order derivatives,although they can well identify the deep anomaly boundary,the calculation is complicated and easy to be disturbed by noises.In order to improve the above problems,proposes a stable and fast edge identification method,which only uses sign function and gravity magnetic vertical derivative data,can identify the targets at different depths in a balanced manner,and avoids the calculation of higher-order derivatives.Through experiments and comparisons of theoretical models,the convenience,effectiveness,anti-oblique magnetization ability and anti-noise ability of the method were verified.At the same time,through the application of actual data,it was verified that the method can accurately and clearly distinguish abnormal objects in a complex gravity and magnetic environment,which can save a lot of time and energy of relevant researchers,and has a good application prospect.