Comprehensive framework for gradient-based optimization in closed-loop reservoir management

摘要: An efficient, robust, and flexible adjoint-based computational framework for performing closed-loop reservoir management is developed applied. The methodology includes gradient-based production optimization data assimilation (history matching). Flexibility achieved through the use of automatic differentiation (AD) within simulation, optimization, history matching modules. AD will also facilitate application to physical models higher complexity. A fast sequential convex programming (SCP) solver based on method moving asymptotes (MMA) applied component closed-loop. This technique shown outperform quadratic (SQP) method, which commonly used computations. workflow integrates both proxy seismic measurements into a unified framework. effect noisy data, different types, accuracy assessed. overall tested using well-documented Brugge model. Results demonstrate efficient performance individual components improvement in net present value that these procedures.