What is it about?
This paper proposes an artificial intelligence-based methodology to identify hydraulic fracturing parameters. This methodology integrates artificial intelligence techniques to match borehole pressure curves. In this context, the genetic algorithm minimizes the error between the observed and the predicted data. Furthermore, the multilayer perceptron (a feedforward neural network) is adopted to build a proxy model
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Why is it important?
Predicting the behavior of petroleum reservoirs is challenging and includes, as a crucial step, determining its geomechanical parameters
Perspectives
We aim to contribute to the estimation of geomechanical parameters for problems related to the petroleum industry based on an efficient approach
Rafael Abreu
Pontificia Universidade Catolica do Rio de Janeiro
Read the Original
This page is a summary of: Inverse analysis of hydraulic fracturing tests based on artificial intelligence techniques, International Journal for Numerical and Analytical Methods in Geomechanics, July 2022, Wiley,
DOI: 10.1002/nag.3419.
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