Browsing NTNU Open by Author "Camponogara, Eduardo"
Now showing items 1-16 of 16
-
An Augmented Lagrangian Method for Optimal Control of Continuous Time DAE Systems
Aguiar, Marco Aurelio Schmitz de; Camponogara, Eduardo; Foss, Bjarne Anton (Journal article, 2016)This works presents an algorithm for solving optimal control problems (OCP) of differential algebraic equations (DAE) based on the augmented Lagrangian method. The algorithm relaxes the algebraic equations and solves a ... -
An Augmented Lagrangian for Optimal Control of DAE Systems: Algorithm and Properties
Aguiar, Marco Aurelio; Camponogara, Eduardo; Foss, Bjarne Anton (Peer reviewed; Journal article, 2021)This article proposes a relax-and-discretize approach for optimal control of continuous-time differential algebraic systems. It works by relaxing the algebraic equations and penalizing the violation into the objective ... -
Black-oil minimal fluid state parametrization for constrained reservoir control optimization
Codas, Andres; Foss, Bjarne Anton; Camponogara, Eduardo; Krogstad, Stein (Journal article; Peer reviewed, 2016)We propose to solve a black-oil reservoir optimal control problem with the Direct Multiple Shooting Method (MS). MS allows for parallelization of the simulation time and the handling of output constraints. However, it ... -
Contributions to production optimization of oil reservoirs
Codas Duarte, Andrés (Doctoral thesis at NTNU;, Doctoral thesis, 2016)This thesis covers methods for optimization of oil production in three time-scales. In the long-term perspective, years, it is desired to maximize the economic return of the field operation, or alternatively, it is desired ... -
Derivative-free trust region optimization for robust well control under geological uncertainty
Silva, Thiago Lima; Bellout, Mathias; Giuliani, Caio M.; Camponogara, Eduardo; Pavlov, Alexey (Peer reviewed; Journal article, 2022)A Derivative-Free Trust-Region (DFTR) algorithm is proposed to solve the robust well control optimization problem under geological uncertainty. Derivative-Free (DF) methods are often a practical alternative when gradients ... -
Echo State Network Based Inverse Models for Feedforward Assisted Optimal Control of Electric Submersible Pumps
Grønningsæter, Ola Solli (Master thesis, 2023)Håndtering av forstyrrelser er antakelig en av de viktigste, men også mest utfordrende, områdene innen reguleringsteknikk. Til tross for at det finnes uttalelige metoder, samt store mengder teori på hvordan forstyrrelser ... -
Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells
Antonelo, Eric; Camponogara, Eduardo; Foss, Bjarne Anton (Journal article; Peer reviewed, 2017)Process measurements are of vital importance for monitoring and control of industrial plants. When we consider offshore oil production platforms, wells that require gas-lift technology to yield oil production from low ... -
Introducing Approximate Well Dynamics into Production Optimization for Operations Scheduling
Hulse, Eduardo O.; Silva, Thiago Lima; Camponogara, Eduardo; Rosa, Vinicius R.; Vieira, Bruno F.; Furtado, Alex Teixeira (Journal article; Peer reviewed, 2020)Most of the literature on short-term production optimization concerns the computation of optimal system settings for steady-state operations. Such methodologies are applicable when the scales of time are faster than reservoir ... -
A modified derivative-free SQP-filter trust-region method for uncertainty handling: application in gas-lift optimization
Hannanu, Muhammad Iffan; Camponogara, Eduardo; Lima Silva, Thiago; Hovd, Morten (Journal article; Peer reviewed, 2024)We propose an effective algorithm for black-box optimization problems without derivatives in the presence of output constraints. The proposed algorithm is illustrated using a realistic short-term oil production case with ... -
Network-Constrained Production Optimization by Means of Multiple Shooting
Silva, Thiago Lima; Codas, Andrés; Stanko, Milan; Camponogara, Eduardo; Foss, Bjarne Anton (Journal article; Peer reviewed, 2019)A methodology is proposed for the production optimization of oil reservoirs constrained by gathering systems. Because of differences in scale and simulation tools, production optimization involving oil reservoirs and ... -
Nonlinear Model Predictive Control of Electrical Submersible Pumps based on Echo State Networks
Jordanou, Jean P.; Osnes, Iver; Hernes, Sondre B.; Camponogara, Eduardo; Antonelo, Eric Aislan; Imsland, Lars Struen (Peer reviewed; Journal article, 2022)Employed for artificial lifting in oil well production, Electrical Submersible Pumps (ESP) can be operated with Model Predictive Control (MPC) to drive an optimal production, while ensuring a safe operation and respecting ... -
Optimal preventive policies for parallel systems using Markov decision process: application to an offshore power plant
Machado, Mario; Lima Silva, Thiago; Camponogara, Eduardo; de Arruda, Edilson; Ferreira Filho, Virgílio (Journal article; Peer reviewed, 2023)This work proposes a Markov Decision Process (MDP) model for identifying windows of opportunities to perform preventive maintenance for multi-unit parallel systems subject to a varying demand. The main contribution lies ... -
Physics-Informed Neural Networks for Modeling and Control of Gas-Lifted Oil Wells
Kittelsen, Jonas Ekeland (Master thesis, 2022)Physics-Informed Neural Networks (PINNs) er en metode for å trene et nevral nettverk til å gjenskape oppførselen til et dynamisk system uten å ha tilgang til simulerte eller målte data, kun ved å bruke den kjente underliggende ... -
Physics-Informed Neural Networks for Modeling of Electric Submersible Pumps in Oil Wells
Bjørlo, Aurora Sletnes (Master thesis, 2023)Physics-Informed Neural Networks (PINN) er nevrale nettverk som inkluderer kjente fysiske sammenhenger inn i treningsprosessen sin, slik at de kan modellere fysiske systemer effektivt, selv med begrenset tilgang til ... -
Practical NMPC of Electrical Submersible Pumps based on Echo State Networks
Hernes, Sondre Bø (Master thesis, 2020)Dette prosjektet går ut på å kontrollere en ESP (electric submersible pump) ved bruk av ESN-PNMPC (Echo state network- practical nonlinear model predictive control) . Å kontrollere en ikke lineær dynamisk prosess kan ... -
Recurrent Neural Networks and Nonlinear Model-based Predictive Control of an Oil Well with ESP
Osnes, Iver (Master thesis, 2020)Modellering og simulering er et avgjørende verktøy for å forstå komplekse ulineære systemer. Nøyaktige modeller er ofte nyttige i reguleringssammenhenger, men kan være vanskelige å anskaffe. Innenfor oljeindustrien har ...