航空与地面一体化重力数据协同高分辨率场源位置和密度反演方法研究

面向深部资源勘查的航空与地面(简称空-地)一体化重力探测，研发高精度和高分辨率空-地重力协同场源位置和密度反演方法，攻关数据转换及协同反演策略，充分利用空-地数据纵向特征及与深浅场源对应关系准确获取场源分布和提升纵向分辨率，并研发更合理、便捷起伏地形和高效密度反演方法来增强实用性，开展①深度学习的空间不同阶导数特征值成像方法准确获取场源位置，并开发空-地重力频谱的多源等效层延拓方法为成像提供准确空间数据；②空间异常权和场分离的空-地重力协同高分辨率密度反演方法，场分离突出空-地重力体现不同深度场源的性质来提升纵向分辨率，空间异常为权函数来提升水平分辨率，并以位置为约束提升精度；③起伏地形密度反演的结构和非结构网格组合等维剖分算法，可更合理便捷地完成反演；④多项式拟合的密度反演方法来减少求解参量，并引入Krylov快速矩阵算法实现高效反演。课题将推动空-地一体化重力探测体系在资源勘查中应用。

Facing the airborne and ground (abbreviation as airborne-ground) integrated gravity exploration of deep resource survey to study high precision and high resolution airborne-ground gravity data cooperative source location and density inversion method, and tackle data transformation and cooperative inversion strategy to obtain the accurate source distribution and improve vertical resolution by fully using the vertical feature of airborne-ground data and corresponding relationship between deep-shallow sources and airborne-ground data, and develop the reasonable and fast rugged topography inversion and high efficiency inversion algorithm to enhance the practicality, carry out (1) spatial different derivative characteristic value imaging method of deep learning to accurately compute source location, and develop multiple source equivalent layer continuation method of airborne-ground gravity spectrum to provide accurate spatial data for imaging. (2) airborne-ground gravity high resolution density inversion method based on spatial anomaly weight and field separation way, and the field separation can highlight the property that the airborne-ground gravity data reflect field sources with different depths to improve the vertical resolution, and introduce the spatial anomaly as weight function to enhance the horizontal resolution, and use the location information as a constraint to improve the accuracy.(3) the same dimensional division method of structure and non-structure combination mesh to accomplish the density inversion of the anomaly with rugged topography, which can be more reasonable and fast to complete the inversion.(4) polynomial fitting density inversion method to reduce the solution parameters, and introduce Krylov fast matrix solution algorithm to realize high efficiency density inversion. This project will promote airborne-ground gravity cooperative exploration technology system in the application of resource exploration.