Artificial Intelligence Proxy Models - Applications in Geosciences

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  • LanguageEnglish
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  • Last checkedJul. 08th '25
  • Date uploadedJul. 07th '25
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Artificial Intelligence Proxy Models: Applications in Geosciences



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English | 2025 | ISBN-10: 303190446X | 61 pages| Epub PDF (True) | 11 MB

This Springer Brief focuses on the use of artificial intelligence (AI) in geosciences and reservoir engineering. This concise yet comprehensive work explores how AI-driven proxy models can effectively tackle the computational challenges associated with reservoir simulations, history matching, production optimization, and uncertainty analysis.
In reservoir engineering, a key challenge is reproducing observed production and pressure data using forward simulation models, known as reservoir simulators. However, the inverse problem of history matching requires running hundreds of simulations, each demanding significant computational resources. Full-scale reservoir simulators are often too time-consuming, making proxy models—such as second-order polynomials, kriging, and artificial neural networks (ANN)—essential alternatives.

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