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This project will develop practical workflows, algorithms and programming codes for inferring unknown reservoir properties from distributed temperature and acoustic sensing data. In-situ pressure and flow conditions can be interpreted from downhole fiber signals gathered in real time, which are used to estimate unknown heterogeneous reservoir parameters continuously. Machine learning methods will be incorporated to […]
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