为解决传统欧拉反褶积法中构造指数选择困难和反演解发散的问题,本文提出并应用了一种改进的倾斜角欧拉(iTilt-Euler)反褶积方法。通过与传统欧拉法和倾斜角欧拉(Tilt-Euler)法的对比分析,本文评估了改进方法在不同埋深、多个场源体以及加噪声情况下的适用性。在单个立方体模型试算中,改进Tilt-Euler法能够准确识别浅部埋深地质体的边界,随着埋深增加,边界识别略有偏差。在组合模型试算中,该方法能够有效识别多个场源体及其接触区域的边界。通过加入2%的高斯噪声进行的试算显示,改进Tilt-Euler法能够有效抑制噪声对反演结果的影响,提高了识别精度。结果表明,改进Tilt-Euler法在处理复杂地质体和噪声干扰时表现出较传统方法更强的稳定性和准确性,具有较好的实际应用前景。To solve the problems of difficult index selection and divergent inversion solutions in traditional Euler deconvolution methods, this paper proposes and applies an improved tilt angle Euler (iTilt-Euler) deconvolution method. By comparing and analyzing with the traditional Euler method and Tilt-Euler method, this paper evaluates the applicability of the improved method under different burial depths, multiple field sources, and noisy conditions. In the trial calculation of a single cube model, the improved Tilt-Euler method can accurately identify the boundaries of shallow buried geological bodies. As the burial depth increases, there is a slight deviation in boundary identification. In the combination model calculation, this method can effectively identify the boundaries of multiple field source bodies and their contact areas. The trial calculation by adding 2% Gaussian noise shows that the improved Tilt-Euler method can effectively suppress the influence of noise on the inversion results and improve the recognition accuracy. The results show that the improved Tilt-Euler method exhibits stronger stability and accuracy than tradition
