Thin elongated sources, such as dykes, sills, chimneys, inclined sheets, etc., often encountered in volcano gravimetric studies, pose great challenges to gravity inversion methods based on model exploration and growing sources bodies. The Growth inversion approach tested here is based on partitioning the subsurface into right-rectangular cells and populating the cells with differential densities in an iterative weighted mixed adjustment process, in which the minimization of the data misfit is balanced by forcing the growing subsurface density distribution into compact source bodies. How the Growth inversion can cope with thin elongated sources is the subject of our study. We use synthetic spatiotemporal gravity changes caused by simulated sources placed in three real volcanic settings. Our case studies demonstrate the benefits and limitations of the Growth inversion as applied to sparse and noisy gravity change data generated by thin elongated sources. Such sources cannot be reproduced by Growth accurately. They are imaged with smaller density contrasts, as much thicker, with exaggerated volume. Despite this drawback, the Growth inversion can provide useful information on several source parameters even for thin elongated sources, such as the position (including depth), the orientation, the length, and the mass, which is a key factor in volcano gravimetry. Since the density contrast of a source is not determined by the inversion, but preset by the user to run the inversion process, it cannot be used to specify the nature of the source process. The interpretation must be assisted by external constraints such as structural or tectonic controls, or volcanological context. Synthetic modeling and Growth inversions, such as those presented here, can serve also for optimizing the volcano monitoring gravimetric network design. We conclude that the Growth inversion methodology may, in principle, prove useful even for the detection of thin elongated sources of high density contrast by providing useful information on their position, shape (except for thickness) and mass, despite the strong ambiguity in determining their differential density and volume. However, this yielded information may be severely compromised in reality by the sparsity and noise of the interpreted gravity data.

火山重力研究中经常遇到的细长源，如堤坝、岩坎、烟囱、斜板等，对基于模型勘探和生长源体的重力反演方法提出了巨大的挑战。这里测试的生长反演方法基于将地下划分为直角矩形单元，并在迭代加权混合调整过程中用不同的密度填充单元，其中通过强制增长的地下密度分布来平衡数据失配的最小化。紧凑的源体。生长反演如何应对细长源是我们研究的主题。我们使用由放置在三个真实火山环境中的模拟源引起的合成时空重力变化。我们的案例研究证明了生长反演应用于由细长源生成的稀疏且嘈杂的重力变化数据的优点和局限性。 Growth 无法准确复制此类来源。它们以较小的密度对比度成像，更厚，体积夸张。尽管存在这一缺点，生长反演可以提供有关多个源参数的有用信息，甚至对于细长源来说也是如此，例如位置（包括深度）、方向、长度和质量，这是火山重力测量的关键因素。由于源的密度对比度不是由反演确定的，而是由用户预先设置以运行反演过程，因此它不能用于指定源过程的性质。解释必须得到外部约束的帮助，例如结构或构造控制，或火山背景。综合建模和生长反演（例如此处介绍的那些）也可以用于优化火山监测重力网络设计。我们的结论是，生长反演方法原则上甚至可以证明对于高密度对比度的细长源的检测是有用的，通过提供有关其位置、形状（厚度除外）和质量的有用信息，尽管在确定它们的过程中存在很大的模糊性。不同的密度和体积。然而，所产生的信息实际上可能会因解释的重力数据的稀疏性和噪声而受到严重损害。