Virtual Reality (VR) Implementation of Reservoir Models and Integration with Artificial Intelligence (AI)
Die Hu
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Abstract
In order to support visualizations of non-3D information and multiple reservoir models, multi-dimensional and multi-representation features are developed. The multi-dimensional feature supports the view of 3D reservoir models and the corresponding 2D information. Multiple 2D panels can be displayed together and show information on different wells. Non-3D data is represented in 3D mode using color, height, size factors.
Two prototypes are proposed as preliminary explorations of integrating VR and AI. The first one is to integrate time series forecasting algorithms with the graph user interface in the VR visualization system. LSTM and Transformer show similarly acceptable prediction results. Because of the computational cost and current data limitation, LSTM is used as a default algorithm to predict monthly oil production in the VR visualization system. The second integration attempt applies the fuzzy set theory to select refracturing candidate wells. If good data is put into calculations, the fuzzy set theory provides solutions based on engineers’ experience. In the study, field history data and physics from a reservoir simulation model are studied using the fuzzy set theory. Though the two examples are not fully or automatically integrated into the VR visualization system, they are good starts for the research.