Seminar Numerical Analysis: Drosos Kourounis (Università della Svizzera italiana)

Adjoint methods for gradient-based optimization of oil recovery

Adjoint-based gradients form an important ingredient of fast optimization algorithms for computer-assisted history matching and life-cycle production optimization. Large-scale applications of adjoint-based reservoir optimization reported so far concern relatively simple physics, in particular two-phase (oil-water) or three-phase (oil-gas-water) applications. In contrast, compositional simulation has the added complexity of frequent flash calculations and high compressibilities which potentially complicate both the adjoint computation and gradient-based optimization, especially in the presence of complex constraints. These aspects are investigated using a new adjoint implementation in a research reservoir simulator designed on top of an automatic differentiation framework coupled to a standard large-scale nonlinear optimization package.  Based on several examples of increasing complexity we conclude that the AD-based adjoint implementation is capable of accurately and efficiently computing gradients for multi-component reservoir flow. However, optimization of strongly compressible flow with constraints on well rates or pressures leads to potentially poor performance in conjunction with an external optimization package. We present a pragmatic but effective strategy to overcome this issue.

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