Alex F. Teixeira

Gas-lift Optimization and Control with Nonlinear MPC

Abstract Abstract More than 70% of the oil production in Brazil employs gas-lift as the artificial lift method. An effort is being done by some operators to complete new gas-lift wells with down hole pressure gages. This paper proposes a Non-Linear MPC algorithm to control a group of wells receiving gas from a common Gas-Lift Manifold. The objective is to maximize an economic function while minimizing the oscillations of the pressures at the manifold and at the bottom of the wells.

Sucker-rod pumping system: Simulator and dynamic level control using bottom hole pressure

In this work a new perspective of the control of a sucker-rod pumping system is presented. In despite of the widely application of control strategies based on dynamometer cards recognition they present several limitations in the control and maintenance aspects. Nowadays, with the development of a new class of low cost downhole sensors, new control strategies could bee applied. In this work, a control framework using the bottom hole pressure combined with a variable speed drive (VSD) structure is proposed. A hardware in the loop simulation platform was developed to evaluate the measure of the bottom hole pressure contribution in a sucker-rod pumping control system.

A mixed-integer linear programming model for automatic routing decisions in oil production optimization

Production optimization of gas-lifted oil wells with routing and pressure constraints is a complex problem, which has attracted the interest of engineers and scientists alike. To this end, a mixed-integer nonlinear model is developed to automatically decide upon flowing well production to a single or multiple manifolds (in the paper referred to as automatic routing). To bypass the complexity of the problem due to its nonlinear and discrete characteristics, a mixed-integer linear reformulation is proposed using piecewise-linear approximations. The resulting formulation splits flows in the pipelines based on the pressure differences which is also observed in commercial multiphase flow simulators. Finally, a computational analysis shows that significant gains can be obtained in oil production by considering automatic routing in the optimization model.

Integrated Methodology for Production Optimization from Multiple Offshore Reservoirs in the Santos Basin

A methodology is proposed for production optimization of oilfields consisting of multiple offshore reservoirs. In such complex systems, several production units are interconnected by a subsea pipeline network that transfers fluids to onshore terminals. A graph-based model of production units, pipelines, and nonlinear phenomena leads to a mixed-integer nonlinear problem for production optimization. Owing to its sheer size, the proposed approach relies on piecewise-linear proxy modeling of the production units and fluid flow. The end result is a mixed-integer linear problem to which robust algorithms can be applied. By means of simulation, the methodology is tested for an offshore oilfield in the Santos Basin, encompassing multiple reservoirs and production platforms.

UKF-Based Data-Driven Soft Sensing: A Case Study of a Gas-Lifted Oil Well

Abstract We address the problem of designing a data-driven soft sensor to estimate the downhole pressure in gas-lifted oil wells. Such application is based on a two-step procedure. In the first step, black-box models are identified offline using experimental data. In the second step, recursive predictions of these models are combined with current measured data (of variables other than the downhole pressure) by means of an interacting bank of unscented Kalman filters. In doing so, a closed-loop model prediction is performed. Results indicate that such closed-loop scheme improves estimation accuracy compared to the free-run model prediction.

Hybrid Monitoring of Offshore Compression Systems

Abstract In this work a hybrid methodology based on statistical approach and phenomenological modeling was developed aiming the monitoring of the performance of compression equipment in an offshore oil platform. A rigorous model was employed in order to estimate thermodynamic based values of the performance of the compression system, given by the polytropic efficiency and head. Residuals were generated by comparing the model values with the ones which were calculated from manufacturers curves using process data (suction and discharge pressures and temperatures, turbine rotation and suction flow). Even though the monitoring technique developed is essentially multivariable and dynamic, the results are displayed using typical univariate process control charts, providing a friendly interface for the operator and allowing the clear detection of process faults.