基于地质体空间位置优化约束的航空重力梯度数据三维物性反演

重力数据的物性反演面临着严重的多解性问题，降低多解性的有效手段是加入约束条件.而边界识别、深度估计及成像方法可获取地质体的水平位置、深度范围等几何参数信息，本文将基于数据本身挖掘的地质体几何参数信息约束到物性反演中，以降低反演的多解性.通过引入基于深度信息的深度加权函数及基于水平位置的水平梯度加权函数建立优化约束条件，有效地提高了反演结果的横向及纵向分辨率.重力梯度数据包含更多的地质体空间特征信息，将优化约束反演方法应用到全张量数据的反演中，模型试验表明本文方法反演结果与理论模型更加吻合.最后对美国路易斯安那州文顿盐丘实测航空重力梯度数据的应用表明，本文方法在其他地球物理、地质资料不足的情况下获得更可靠的反演结果.

3D inversion of airborne gravity gradient data for physical properties based on optimizing constraints of spatial position of the geologic body

The inversion of gravity data for physical properties faces a serious non-uniqueness problem. The effective means to reduce such non-uniqueness is to add more constraints. The edge detecting, depth estimation and imaging methods can obtain the geometric parameters such as the horizontal position and depth range of the geological body. In this paper, the geological body geometric parameter information based on the data itself is constrained to the physical property inversion to reduce the non-uniqueness of inversion. By introducing the depth information-based depth weighting function and the horizontal position-based horizontal gradient weighting function to establish optimizing constraints, the horizontal and vertical resolution of inversion results are effectively improved. The gravity gradient data contains more information on spatial features of the geological body, and the optimizing constrained inversion method is applied to the inversion of full tensor data. Tests on a synthetic model show that the inversion results of this method are more consistent with the theoretical model. Finally, the application of this method to the airborne gravity gradient data in the Vinton Salt in Louisiana, USA shows that this approach permits to obtain more reliable inversion results in the case with insufficient other geophysical and geological data.