Well Models for Production Optimization

Abstract

In coupled reservoir simulations a model of a reservoir and the production system are joined together to obtain realistic responses. One way of performing production optimization is to make use of a gas oil ratio (GOR) estimate when calculating the optimal flow rates. Today this estimate is either not accurate enough or calculating it is a time consuming process. The thesis tries on an alternative online approach for estimating the GOR. It makes use of basis functions in the form of polynomials and normalized radial basis functions together with a recursive least squares (RLS) algorithm. This yields a simple and effective optimization strategy. When using a second order polynomial together with the fast convergent recursive least squares algorithm one achieves a suitable fit to the estimated production data. The algorithm has not yet been tested together with a production optimization tool and it has not been compared to the existing methods for estimating the GOR. Still it seems to have a lot of potential and the RLS is fast, convergent and proper for the objective of this thesis.