逐步逼近曲化平方法研究

Reduction of potential field data to a horizontal plane by a successive approximation procedure

位场资料的常规处理解释方法是建立在平面数据理论之上的,然而实际的位场数据大多为曲面数据,若把曲面数据当成平面数据进行处理,必然导致很大的误差,因此有必要进行"曲化平"处理.曲化平目前存在的主要问题是计算精度低、计算量大,因此,研究快速、精度高且适合大数据量处理的曲化平方法具有重要的价值.本文在已有的泰勒级数曲化平方法基础上提出了逐步逼近技术和平均平面技术,使得曲面位场资料处理的精度得到了很大提高.最后通过理论模型和实际资料的处理验证了该方法的应用效果.

Most existing techniques for processing potential field data still require data on a horizontal plane. However, almost all the potential field data observed are on an irregular surface. In order to avoid errors we cannot simply take the data observed on an irregular surface and process them as they are on a horizontal plane A reduction process to a horizontal plane is necessary. At present we need to overcome two technical problems in the current reduction process, low accuracy and high computing cost. It is imperative to develop a method being able to process a large number of data fast and accurately. This paper presents two techniques, Successive Approximation Procedure and selecting Average Plane based on the existing Taylor＇s Series method. These two techniques have greatly improved the accuracy of the potential field data analyses. The theoretical modeling and data processing procedure employing these two techniques are included in this paper.