最小曲率模型的航空重力数据噪声压制方法研究  

Noise suppression of airborne gravity data with minimum curvature model

作　　者：王皓 熊盛青 何涛 王万银[1,3,4] WANG Hao;XIONG ShengQing;HE Tao;WANG WanYin(School of Geological Engineering and Surveying,Chang'an University,Xi'an 710054,China;China Natural Resources Aviation Geophysical and Remote Sensing Center,Key Laboratory of Aviation Geophysics and Remote Sensing Geology of the Ministry of Natural Resources,Beijing 100083,China;National Engineering Research Center for Offshore Oil and Gas Exploration,Beijing 100028,China;Key Laboratory of Marine Geology and Environment,Chinese Academy of Sciences,Qingdao 266071,China;Rocket Force University of Engineering,Xi'an 710025,China)

机构地区：[1]长安大学地质工程与测绘学院,西安710054 [2]中国自然资源航空物探遥感中心,自然资源部航空地球物理与遥感地质重点实验室,北京100083 [3]海洋油气勘探国家工程研究中心,北京100028 [4]中国科学院海洋地质与环境重点实验室,青岛266071 [5]火箭军工程大学,西安710025

出　　处：《地球物理学报》2024年第10期3959-3972,共14页Chinese Journal of Geophysics

基　　金：国家重点研发计划项目(2017YFC0602200)之课题“航空地球物理数据综合处理解释方法研究及软件开发”(2017YFC0602202)资助。

摘　　要：航空重力是近几十年来快速发展起来的一种地球物理勘探方法,在数据采集时会受到飞机震动、颠簸以及气流变化引起的飞机高度变化等因素产生的噪声影响,使得采集的重力数据中由地质体引起的重力异常远远小于噪声,对后续的处理和解释带来了很大困难.航空重力数据噪声压制一直是航空重力数据处理的难题,也是地球物理学家一直致力研究的课题.本文将最小曲率方法用于航空重力数据噪声压制,在已有显式和隐式单步长、叠加步长、多重单步长和多重叠加步长迭代的基础上,提出了松弛迭代技术,解决了显式单步长和显式多重单步长迭代不收敛的问题.利用Fourier频谱分析理论,研究了松弛迭代格式的收敛性,并给出了松弛因子选择方法;通过仿真数据和实测数据测试了最小曲率方法在航空重力数据噪声压制的效果.研究结果表明,最小曲率方法是一种有效的航空重力数据噪声压制方法,能够提高航空重力数据的质量,也为进一步处理和解释提供了可靠的数据.最小曲率噪声压制方法还可用于地面、船载以及卫星重力数据的噪声压制以及其他数据的噪声压制,具有广泛的推广应用前景.Airborne gravity, a rapidly advancing geophysical exploration method in recent decades, encounters significant noise interference during data acquisition stemming from factors such as aircraft vibrations, turbulence, and changes in altitude due to variations in airflow. This results in the gravity anomalies induced by geological bodies in the collected data being substantially smaller than the noise, posing considerable challenges for subsequent processing and interpretation. Noise suppression in airborne gravity data has always been a challenge in data processing and a topic that geophysicists have been dedicated to researching. This study applies the minimum curvature method to noise suppression in airborne gravity data. Building upon existing explicit and implicit single-step, superposition-step,multiple single-step, and multiple superposition-step iterations, a relaxation iteration technique is proposed to address the convergence issues of explicit single-step and explicit multiple single-step iterations. By utilizing Fourier spectrum analysis, the convergence of the relaxation iteration format is investigated, and a method for selecting relaxation factors is provided. The effectiveness of the minimum curvature method in noise suppression in airborne gravity data is tested using simulated and real data. The research findings demonstrate that the minimum curvature method is an effective noise suppression method for airborne gravity data, capable of enhancing quality of airborn gravity data and providing reliable data for further processing and interpretation. Importantly, the versatility of this noise suppression method extends its applicability beyond airborne data, accommodating various other datasets, including ground, ship, and satellite gravity data. As such, it showcases a broad range of potential applications in the field of geophysical exploration.

关 键 词：航空重力数据 最小曲率 噪声压制 松弛迭代技术 

分 类 号：P631[天文地球—地质矿产勘探]