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Geosciences is a field of great societal relevance that requires solutions to several urgent problems facing our humanity and the planet. As geosciences enters the era of big data, machine learning (ML)—that has been widely successful in commercial domains—offers immense potential to contribute to problems in geosciences. However, geoscience applications introduce novel challenges for ML due to combinations of geoscience properties encountered in every problem, requiring novel research in machine learning. This article introduces researchers in the machine learning (ML) community to these challenges offered by geoscience problems and the opportunities that exist for advancing both machine learning and geosciences. We first highlight typical sources of geoscience data and describe their common properties. We then describe some of the common categories of geoscience problems where machine learning can play a role, discussing the challenges faced by existing ML methods and opportunities for novel ML research. We conclude by discussing some of the cross-cutting research themes in machine learning that are applicable across several geoscience problems, and the importance of a deep collaboration between machine learning and geosciences for synergistic advancements in both disciplines. [ABSTRACT FROM AUTHOR]

The plutonic crustal sequence exposed northeast of Sabzevar is part of the ophiolitic belt of Sabzevar that occurs along the northern margin of the Central Iran micro-continent. The sequence includes olivine and pyroxene gabbro with cumulate characteristics, isotropic gabbro, foliated gabbro and a diabase sheeted dyke complex cut by wehrlite and olivine websterite intrusions, and pegmatite gabbro and plagiogranite as small intrusions and dykes. The sequence is comparable to gabbros in known ophiolite complexes. Microscopic studies show an abundance of the mesocumulate and heteradcumulate textures that represent open system magma chambers, which are common in supra-subduction zones. The olivine → plagioclase → clinopyroxene → ± orthopyroxene → amphibole trend of mineralization in the gabbros, similar to mid-ocean ridge basalt (MORB), and olivine → clinopyroxene → ± orthopyroxene → plagioclase → amphibole, similar to arc rocks, indicate the diversity in the formation of these rocks, and represent petrographic evidence of their formation in a supra-subduction zone. The rocks have calc-alkaline to tholeiitic affinities, and niobium depletion in the spider diagrams of diabase that matches the patterns of island arc magma. These patterns, and the light rare earth element enrichment of the diabase and plagiogranite, suggest the effect and introduction of the fluids, originating from the subducting slab, beneath the mantle wedge. The low titanium compositions, matching those of arc diabase and plagiogranite, plot in the island arc to MORB tectonomagmatic fields, and suggest formation of the Sabzevar ophiolitic plutonic crustal sequence in a supra-subduction zone during Late Cretaceous time. [ABSTRACT FROM AUTHOR]