Short-Term Production Optimization Under Water-Cut Uncertainty

Abstract

Summary Short-term production optimization is an essential activity in the oil/gasfield-development process because it allows for the maximization of field production by finding the optimal operational point. In the fields that use gas lift as an artificial-lift method, the gas-lift optimization is a short-term problem. This paper presents a stochastic approach to include uncertainties from production parameters in gas-lift optimization, called the uncertain-gas-lift-optimization problem (UGLOP). Uncertainties from production variables are originated from the measurement process and the intrinsic stochastic phenomena of the production activity. The production variables usually obtained from production tests play an important role in the optimization process because they are used to update reservoir and well models. To include the uncertainties, the strategy involves representing the well-test data using nonlinear regression [support-vector regression (SVR)] and using the Latin-hypercube-sampling (LHS) method. The optimization gives a stochastic solution for the operational point. In the solved problem, this operational point is composed of the individual wells’ gas-lift-injection rate, choke opening, and well/separator routing. The value of the stochastic solution is computed to evaluate the benefit of solving the stochastic problem over the deterministic. The developed methodology is applied to wells of a Brazilian field considering uncertainty in water-cut (WC) values. As a result, an up-to-4.5% gain in oil production is observed using this approach.