梯度反褶积法及其在矿产勘探中的应用

Gradient Deconvolution Method and Its Application in Mineral Exploration

梯度探测技术以其信息量大、精度高、干扰小等优点在地球物理领域中得到广泛应用,但现今针对梯度数据的反演方法还比较少。笔者提出一种新的梯度数据解释方法——梯度反褶积法,该方法以梯度数据为基础获得场源体的位置信息,在计算公式中消除了构造指数,避免了因构造指数选取不当引起的误差。通过理论模型试验证明,梯度反褶积法能有效地完成目标体的反演工作,反演结果与理论值之间的误差小于5%,且相对于常规欧拉反褶积法更加稳定、准确。将梯度反褶积法应用于实测航磁梯度异常的解释,获得了地下铁矿的分布状态。

Gradient detection technology is widely used in the geophysical measurement for its great capacity, high precision and low noise level et al, but there are few methods for interpreting gradient data now. The authors presented a new gradient interpretation method here, called gradient deconvolution method. The new method can obtain the locations of the causative sources with gradient data, and eliminate structural index from the calculation equation and thus avoids the errors produced by improper structural index selection. We tested the gradient deconvolution method with synthetic potential data. The inversion results show that the misfit between the theory and inversion result is less than 5%, and the inversion results are more stable and correct compared to the conventional Euler deconvolution method. At last, we applied the gradient Euler deconvolution method to measured aeromagnetic gradient data, and obtained the distribution of underground iron mine.