Unconventional/complex reservoirs

Hybrid Approach Proves Effective in Multiwell Forecasting in Unconventionals

The authors of this paper propose a hybrid approach that combines physics with data-driven approaches for efficient and accurate forecasting of the performance of unconventional wells under codevelopment.

Simulation grid for a two-well RGNet model.
Simulation grid for a two-well RGNet model.

The aim of the complete paper is to propose a hybrid approach that combines physics with data-driven approaches for efficient and accurate forecasting of the performance of unconventional wells under codevelopment. The method the authors propose is the reservoir graph network (RGNet) model. By reducing system complexity while maintaining fundamental physics, the model provides an efficient and accurate way to model, history-match, and predict unconventional wells. Compared with a full-physics model that takes from hours to days to run, the described model only takes from seconds to minutes.

Performance Analysis of Unconventional Reservoirs

Developing unconventional reservoirs is a complex process involving well targeting, timing, spacing, and completion design for horizontal wells with hydraulic fractures.

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