Reservoir simulation plays an important role in the petroleum industry. Today, there is a specific demand to run ensembles of megaand even giga-cell models. The iterative solution of the large systems of nonlinear governing equations, which describe the multiphase mass transfer in the subsurface, takes the most of the simulation time. The linearization part of the solution process occupies a significant fraction of that time, especially in compositional models. Moreover, the implementation of the linearization step usually embodies the most substantial, complex, and specific part of the computational loop in modern simulators, defining which physical mechanisms and assumptions are employed. This significantly complicates the implementation of simulation codes for heterogeneous computing hardware, which promises significant improvements in simulation time. In this work, we use the recently proposed Operator-Based Linearization (OBL) approach to develop a general purpose reservoir simulation code aiming to substantially decrease the simulation time. OBL offers a simplified linearization method, enhancing the computational performance of simulation and providing an opportunity of a painless porting to heterogeneous computing architectures. To distinct the contribution of both factors, we developed two versions of the compositional simulation prototype code: for traditional CPU and GPU-accelerated hardware architectures. While the former allowed us to speed the linearization stage up by an order of magnitude in comparison with the conventional approach, based on Automatic Differentiation (AD), the latter improved it further by another order of magnitude. The developed prototype realizes the potential of the OBL approach and GPU computing architecture, proving significant improvement in general purpose simulation performance.

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