基于机器学习的岩浆液体温度计

IF 3.5 2区 地球科学 Q1 GEOCHEMISTRY & GEOPHYSICS Journal of Petrology Pub Date : 2024-03-02 DOI:10.1093/petrology/egae020
Gregor Weber, Jon Blundy
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引用次数: 0

摘要

火成岩岩石学中广泛使用经过实验校准的模型来恢复岩浆的压力和温度。然而,较大的误差(尤其是气压测量误差)限制了这些模型解析地壳火成岩系统结构的能力。在此,我们将机器学习应用于大型实验数据库,校准新的回归模型,该模型可根据熔体成分和相关相组合恢复岩浆的 P-T。该方法适用于从玄武岩到流纹岩的成分、0.2 到 15 千巴的压力以及 675-1400°C 的温度。使用滤波器对模型进行了测试和优化,滤除了标准偏差超过第50百分位数的估计值,结果表明压力的均方根误差(RMSE)为1.1-1.3千巴,温度估计值的误差为21°C。我们的研究结果表明,在对共存矿物组合熔体化学成分的限制条件下,熔融指数是岩浆变量的可靠记录器。这是因为尽管天然岩浆的氧化物成分相对较多,但其热力学差异相对较小。我们将模型应用于两个地球物理信息约束良好的对比案例:圣海伦火山(美国)和冰岛的 Askja 火山口。1980-1986年喷发的圣海伦火山的英安岩整块岩石被推断为从cpx-hbl-opx-plag-mt-ilm泥浆中提取的液体,其熔体提取源压力为5.1-6.7千巴,与地球物理约束条件非常吻合。熔融包裹体和基质玻璃的压力较低(0.7-3.8 千巴),与成像地球物理异常点上游和上升过程中的岩浆结晶相一致。对阿斯佳历史喷发岩浆储层深度的估计与地震波速度异常点的位置相吻合。5-10 千米深处的 Vp/Vs 异常点与热流纹岩(约 990°C)源区相对应,而玄武岩浆(约 1120°C)则储存在火山口下 7-17 千米深处。这些例子说明了我们的模型如何能够将岩石学和地球物理学联系起来,从而更好地约束火山给料系统的结构。我们的模型(MagMaTaB)可通过用户友好型网络应用程序(https://igdrasil.shinyapps.io/MagmaTaBv4/)访问。
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A machine learning-based thermobarometer for magmatic liquids
Experimentally calibrated models to recover pressures and temperatures of magmas, are widely used in igneous petrology. However, large errors, especially in barometry, limit the capacity of these models to resolve the architecture of crustal igneous systems. Here we apply machine learning to a large experimental database to calibrate new regression models that recover P-T of magmas based on melt composition plus associated phase assemblage. The method is applicable to compositions from basalt to rhyolite, pressures from 0.2 to 15 kbar, and temperatures of 675-1400°C. Testing and optimisation of the model with a filter that removes estimates with standard deviation above the 50th percentile show that pressures can be recovered with root-mean-square-error (RMSE) of 1.1-1.3 kbar and errors on temperature estimates of 21°C. Our findings demonstrate that, given constraints on the coexisting mineral assemblage melt chemistry, is a reliable recorder of magmatic variables. This is a consequence of the relatively low thermodynamic variance of natural magma compositions despite their relatively large number of constituent oxide components. We apply our model to two contrasting cases with well-constrained geophysical information: Mount St. Helens volcano (USA), and Askja caldera in Iceland. Dacite whole-rocks from Mount St Helens erupted 1980-1986, inferred to represent liquids extracted from cpx-hbl-opx-plag-mt-ilm mush, yield melt extraction source pressures of 5.1-6.7 kbar in excellent agreement with geophysical constraints. Melt inclusions and matrix glasses record lower pressures (0.7-3.8 kbar), consistent with magma crystallisation within the upper reaches of the imaged geophysical anomaly and during ascent. Magma reservoir depth estimates for historical eruptions from Askja match the location of seismic wave speed anomalies. Vp/Vs anomalies at 5-10 km depth correspond to hot (~990°C) rhyolite source regions, while basaltic magmas (~1120°C) were stored at 7-17 km depth under the caldera. These examples illustrate how our model can link petrology and geophysics to better constrain the architecture of volcanic feeding systems. Our model (MagMaTaB) is accessible through a user-friendly web application (https://igdrasil.shinyapps.io/MagmaTaBv4/).
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来源期刊
Journal of Petrology
Journal of Petrology 地学-地球化学与地球物理
CiteScore
6.90
自引率
12.80%
发文量
117
审稿时长
12 months
期刊介绍: The Journal of Petrology provides an international forum for the publication of high quality research in the broad field of igneous and metamorphic petrology and petrogenesis. Papers published cover a vast range of topics in areas such as major element, trace element and isotope geochemistry and geochronology applied to petrogenesis; experimental petrology; processes of magma generation, differentiation and emplacement; quantitative studies of rock-forming minerals and their paragenesis; regional studies of igneous and meta morphic rocks which contribute to the solution of fundamental petrological problems; theoretical modelling of petrogenetic processes.
期刊最新文献
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