3rd IFAC Workshop on Automatic Control in 
Offshore Oil and Gas Production

(OOGP-2018)

May 30 – June 01, 2018 
Aalborg University Esbjerg, 
Niels Bohrs Vej 8, 6700 Esbjerg, Denmark 
http://ifac-oogp2018.org

                                

Background 
The low oil-prices, stringent regulations as well as harder and harder recovery conditions have been leading offshore oil & gas operators to seek more reliable, cost-effective and environmental friendly technologies for Exploration and Production (E&P), besides making new E&P in marginal reservoirs and reservoirs far from the coasts. At the same time, many new technologies on reservoirs, exploration, drilling, completion, production, measurement, processing and automation as well as drone technology, and subsea robotics, are being rapidly developed in recent decades, which open up new opportunities for making oil & gas E&P and its optimization more efficient, reliable and environmental friendly. 

The 1st OOGP took place in Trondheim, Norway during 31.05 – 01.06 2012, and the 2nd OOGP took place in Florianópolis, Brazil during 27-29.05 2015. Continuing with the previous workshops’ strategic journey, this workshop aims to provide a common high-tech forum for both academia and industries correlated with offshore oil & gas E&P, with special focus on the development and application of control, automation, measuring, robotic, and optimization technologies in offshore oil & gas E&P. The workshop will bring oil & gas operators, service and supplier companies, and academy together to share their ideas, open challenges and recent developments with the objective to enhance the close multi- and cross-disciplinary cooperation.

Conference venue
The conference will be held at Aalborg University, Esbjerg Campus, Niels Bohrs Vej 8, 6700 Esbjerg, Denmark, http://www.esbjerg.aau.dk/. Esbjerg is the fifth largest city and the offshore capital of Denmark, see: http://www.visit-esbjerg.com/ln-int/Esbjerg-Tourist-Information

Sponsors
OOGP-2018 is sponsored by the IFAC Technical Committee on Chemical Process Control (TC 6.1) and co-sponsored by the IFAC Technical Committee on Robotics (TC 4.3), also co-sponsored by Aalborg University, The Danish Society of Engineers (IDA), Offshoreenergy.dk, Inspiring Denmark, ABB, and The Danish Hydrocarbon Research and Technology Centre (DHRTC). 

     

         

All degree programmes and research activities at Aalborg University are problem and project-based and have an interdisciplinary focus. Through strong interplay between staff and students and intense collaboration with public and private sectors, we offer degree programmes with a real-world approach and provide world-class research. These results in new insights, new solutions to societal challenges, and knowledge change the world. http://www.aau.dk/
The Department of Energy Technology has a series of world class laboratory facilities at its disposal where researchers and students do much of their work. Companies and organisations have the opportunity to gain access to our laboratories, and with the expansion and renovation of the laboratories of the department, we can now offer students and cooperating partners some of the research world's most advanced and modern facilities in the energy sector. http://www.en.aau.dk/

 

ABB is a pioneering technology leader in electrification products, robotics and motion, industrial automation and power grids, serving customers in utilities, industry and transport & infrastructure globally. Continuing a history of innovation spanning more than 130 years, ABB today is writing the future of industrial digitalization with two clear value propositions: bringing electricity from any power plant to any plug and automating industries from natural resources to finished products. As title partner of Formula E, the fully electric international FIA motorsport class, ABB is pushing the boundaries of e-mobility to contribute to a sustainable future. ABB operates in more than 100 countries with about 135,000 employees.

More information about ABB can be found at http://new.abb.com/ 

In 2014, the partners in Danish Underground Consortium (DUC) entered into an agreement to finance the Danish Hydrocarbon Research and Technology Centre (DHRTC). The centre has been established to deliver innovative solutions based on excellent research. DHRTC’s talented employees and collaborating partners contribute to ensuring that we realise our vision, which is to demonstrate an increased oil and gas recovery in the Danish North Sea in a commercially viable way. 
Collaboration is fundamental in all aspects of the centre’s operation. DHRTC is the joint initiative of five leading Danish research institutions; Aalborg University, Aarhus University, University of Copenhagen, Geological Survey of Denmark and Greenland (GEUS) and Technical University of Denmark. Furthermore, the centre engages in interdisciplinary and international research and innovation in cooperation with the business community. 
DHRTC’s research is organised into three research programmes: Tight Reservoir Development, Advanced Water Flooding and Cost Transformation. Learn more about the centre at www.oilgas.dtu.dk.

The Danish Society of Engineers, IDA, is a professional organization with more than 110.000 members working and studying in the fields of technology, natural sciences and IT. Together we realise the potential of technology and knowledge. https://english.ida.dk/
IDA has sponsored the “Fiskeri- og Søfartsmuseet” activity for the OOGP-2018. https://fimus.dk/
Best Paper Awards 

•	OOGP-2018 Best Conference Paper Award: DA-AAU Best Conference Paper Award               

                            

IDA-AAU Best Conference Paper Award

The OOGP-2018 Best Conference Paper Award is sponsored by The Danish Society of Engineers (IDA) and Aalborg University. 

•	OOGP-2018 Best Student Paper Award: ABB Best Student Paper Award 

ABB Best Student Paper Award

The OOGP-2018 Best Student Paper Award is sponsored by ABB A/S.  

DAY 1						Wednesday, May 30, 2018

07:45 – 08:15 	
Main entrance hall at the university of Aalborg University Esbjerg
Registration and coffee.  	
08:15 – 08:30	
Room: C1-119 
Welcome ceremony by Zhenyu Yang and Jens Bo Holm-Nielsen, Department of Energy Technology in Esbjerg  
	
08:30 – 09:30	
Room: C1-119
Plenary Talk (1): Increased Production with Automatic Control in Offshore Oil and Gas Production in Statoil. Presented by Elvira Marie  
	
09:30 – 10:00 	
Room: C1-Foyer 
Coffee break 
	
10:00 – 12:00 	
Room: C1-119 
Regular Talk We_A: Production Optimization  
	
12:00 – 13:00	
Room: Canteen   
Lunch break  
	
13:00 – 15:00 	
Room: C1-119 
Regular Talk We_B: Drilling Control & Automation 
	
15:00 – 15:30	
Room: C1-Foyer 
Coffee break
	
15:30 – 17:30	
Room: C1-119
Regular Talk We_C: Reservoir Simulation, Optimization & Management	
17:30 – 21:30	
Welcome activities (Esbjerg city & harbor tour, Esbjerg Fiskeri- og Søfartsmuseum)
Bus leaves at 18:00 from the main entrance at Aalborg University Esbjerg. One-hour Esbjerg city and harbor tour before arriving at Fiskeri- og Søfartsmuseum at 19:00. There will be a light dinner and a guided tour at the Fiskeri- og Søfartsmuseum.

Note: If you want a to-go lunch Friday, please give the information to OOGP-2018 staff no later than the end of Wednesday.   

DAY 2					 	  Thursday, May 31, 2018

08:30 – 09:30	
Room: C1-119
Plenary Talk (2): Upstream Process Performance: Non-Intrusive Capture of Large but Hidden Opportunities. Presented by Olav Slupphaug
	
09:30 – 10:00 	
Room: C1-Foyer 
Coffee break 
	
10:00 – 12:00 	
Room: C1-119 
Regular Talk Th_A: Separation Control & Optimization
	
12:00 – 13:00	
Room: Canteen   
Lunch break
	
13:00 – 15:00 	
Room: C1-119 
Regular Talk Th_B: Plant-Wide Control & Monitoring 
	
15:00 – 15:30	
Room: C1-Foyer 
Coffee break

15:30 – 17:30	
Room: C1-119
Regular Talk Th_C: Big Data & Digital Field Technologies
	
19:00 – 21:30	

ECH Park Hotel – Stormgade 200, 6700 Esbjerg 

Conference Banquet held at ECH Park Hotel. After the main course, the best conference paper award and best student paper award will be announced and certificates will be delivered. 

DAY 3						   Friday, Jun 1, 2018

08:30 – 09:30	
Room: C1-119
Plenary Talk (3): Optimal and Predictive Control in the Upstream Oil and Gas Industry. Presented by John Bagterp Jørgensen
	
09:30 – 10:00 	
Room: C1-Foyer 
Coffee break 
	
10:00 – 11:40 	
Room: C1-119 
Regular Talk Fr_A: Robotics & Nonlinear Control   
	
11:40 – 12:30	
Room: C1-119 
Close Note Talk by Sigurd Skogestad
	
12:30 – 13:30 	
Room: Canteen  
Lunch and OOGP-2018 Conference finishing 

Book of Abstracts of 3rd IFAC Workshop on Automatic Control in Offshore Oil and Gas Production
 
Technical Program for Wednesday May 30, 2018
 
We_Plenary_Talk_T1	C1-119	
Plenary Talk (1) (Plenary Session)	
Chair: Skogestad, Sigurd	Norwegian Univ. of Science & Tech	
08:30-09:30	We_Plenary_Talk_T1.1	
Increased Production with Automatic Control in Offshore Oil and Gas Production in Statoil*	
Bergheim, Elvira Marie	Statoil	
Kittilsen, Pål	Statoil ASA	
Aasheim, Robert	Statoil ASA	
Fredriksen, Morten	Statoil ASA	

In the light of the current global digitalization and automation focus, Statoil recognizes the great value of automatic control which also is reflected Statoil’s technology strategy.  To optimize production from existing and near field resources, safe and efficient operations are key success factors. Statoil’s technology strategy states an ambition to be technology leader within automatic production optimization. Traditionally, the automation level of oil and gas producing offshore platforms has been lower than for comparable onshore facilities like processing plants and
refineries. Particularly production and injection wells have been lacking automatic control. Both the equipment, the traditional way of operating wells and their inherent variable nature have led to a higher threshold for automation. However, the last 10 years, Statoil has significantly increased the level of automatic control for production and injection wells. The implementation of automatic control of production and injection wells ensures automatic compensation for natural variations in the wells in addition to automatic ramp-up of well. Automatic control of production wells typically gives an accelerated production in the range of 3-10% per well due to faster start-up and operating closer to the wells’ desired operation points.  Another type of application ses wells for actively compensation of disturbances topside, thus enabling operation closer to maximum capacity.  The first installation of using so-called swing producers to ensure maximum plant throughput was completed in 2008 and the yearly income by this implementation is about 80 MNOK/year.  Statoil has an ambition of go beyond just constraint chasing, and is also working on real-time production optimization. In this context, that means automatic prioritizing between wells, like distributing which wells to produce from and at what production rate for an overall optimal operation. Development of automatic production optimization solutions are in progress, both model based and model free methods. The main challenge is to make the optimization robust with contributions from measurement and model accuracy and use of feedback.	

We_A_Regular_Talk_T1	C1-119	
Production Optimization (Regular Session)	
Chair: Jorgensen, John Bagterp	Tech. Univ. of Denmark	
10:00-10:20	We_A_Regular_Talk_T1.1	
Oil Production Optimization of Several Wells Subject to Choke Degradation, pp. 1-6	
Verheyleweghen, Adriaen	Norwegian Univ. of Science and Tech	
Jäschke, Johannes	Norwegian Univ. of Science & Tech	
Unplanned maintenance interventions of subsea oil and gas production systems are prohibitively expensive, which leads to strict requirements to equipment reliability. Without a systematic way to ensure reliable operation however, a very conservative operational strategy is often chosen, which can lead to sub-optimal operation and the loss of large prot potentials. We propose to integrate condition monitoring and prognostics into the production planning problem to reduce conservativeness by actively steering plant degradation and preventing violation of health-critical constraints. We achieve this by combining equipment degradation models with regular process models and solving a shrinking horizon real-time optimization problem until the next planned maintenance horizon. A network of oil and gas producing wells with articial gas lift, subject to particle induced choke erosion is used as a case example.	
10:20-10:40	We_A_Regular_Talk_T1.2	
A Least Squares Method for Ensemble-Based Multi-Objective Oil Production Optimization, pp. 7-12	
Hjuler Christiansen, Lasse	Tech. Univ. of Denmark	
Hørsholt, Steen	Tech. Univ. of Denmark	
Jorgensen, John Bagterp	Tech. Univ. of Denmark	
Despite a significant potential to improve industrial standards, practical applications of production optimization are impeded by geological uncertainty. As a mean to handle the associated financial risks, the oil literature has devised a range of ensemble-based strategies that seek to optimize proper combinations of sample-estimated risk measures to balance the opposing objectives of risk and reward. Many of the associated optimization problems are naturally formulated in terms of multi-objective optimization (MOO). Ideally, MOO problems should be solved by generating an approximation to the efficient frontier of optimal trade- offs between risk and return. However, the large-scale nature of real-life oil reservoirs implies that formation of the frontier often becomes computationally intractable in practice. To meet this challenge, this paper introduces a generalized least squares (LS) approach that provides an efficient and unified solution strategy for ensemble-based multi-objective optimization problems. At its core, the LS method uses an a priori characterization of desirable trade-offs that allows the method to focus on a single Pareto optimal point. Consequently, the LS approach avoids the need to generate a representative of the efficient frontier. In turn, this significantly reduces the computational complexity compared to most MOO methods. As a result, the LS method poses a practical alternative to conventional strategies when the efficient frontier is unknown and computationally intractable to generate.	
10:40-11:00	We_A_Regular_Talk_T1.3	
Nonlinear Model Predictive Control of an Oil Well with Echo State Networks, pp. 13-18	
Jordanou, Jean Panaioti	Univ. Federal De Santa Catarina	
Camponogara, Eduardo	Federal Univ. of Santa Catarina	
Antonelo, Eric Aislan	Federal Univ. of Santa Catarina	
Aguiar, Marco Aurélio	Univ. Federal De Santa Catarina	
In oil production platforms, processes are nonlinear and prone to modeling errors, as the flow regime and components are not entirely known and can bring about structural uncertainties, making the design of predictive control algorithms a challenge. In this work, an efficient data-driven framework for Model Predictive Control (MPC) using Echo State Networks (ESN) as the prediction model is proposed. Unlike previous works, the ESN model for MPC is only linearized partially: while the free response of the system is kept fully nonlinear, only the forced response is linearized. This MPC framework is known in the literature as the Practical Nonlinear Model Predictive Controller (PNMPC). In this work, by using the analytically computed gradient from the ESN model, a finite difference method is not needed to compute derivatives as in PNMPC. The proposed method, called PNMPC-ESN, is applied to control a simplified model of a gas-lifted oil well, managing to successfully control the plant, obeying the established constraints while maintaining setpoint tracking.	
11:00-11:20	We_A_Regular_Talk_T1.4	
Gas-Lift Optimization by Controlling Marginal Gas-Oil Ratio Using Transient Measurements, pp. 19-24	
Krishnamoorthy, Dinesh	Norwegian Univ. of Science and Tech	
Jahanshahi, Esmaeil	Norwegian Univ. of Science & Tech	
Skogestad, Sigurd	Norwegian Univ. of Science & Tech	
This paper presents the application of a steady-state gradient control using transient measurements to a gas-lift optimization problem. Optimal operation of a gas-lifted field involves controlling the marginal gas-oil ratio (mGOR), which is the steady-state gradient of the oil rate with respect to the gas-lift rate. In this paper, we apply a novel method to estimate the marginal GOR online using a dynamic model and transient measurements, without the need for additional perturbation. The proposed method is based on linearizing the dynamic model around the current operating point to estimate the marginal GOR, which is then controlled using simple feedback controllers to achieve optimal operation. In case of disturbances, the proposed method is able to adjust fast to the new optimal point, without the need to solve computationally expensive optimization problems. By using transient measurements, it does not need to wait for the process to reach steady-state to update the model. The proposed method was tested in simulations and was shown to provide similar performance as an economic MPC.	
11:20-11:40	We_A_Regular_Talk_T1.5	
Fast Economic Model Predictive Control for a Gas Lifted Well Network, pp. 25-30	
Suwartadi, Eka	Norwegian Univ. of Science and Tech	
Krishnamoorthy, Dinesh	Norwegian Univ. of Science and Tech	
Jäschke, Johannes	Norwegian Univ. of Science & Tech	
This paper considers the optimal operation of an oil and gas production network by formulating it as an economic nonlinear model predictive control (NMPC) problem. Solving the associated nonlinear program (NLP) can be computationally expensive and time consuming. To avoid a long delay between obtaining updated measurement information and injecting the new inputs in the plant, we apply a sensitivity-based predictor-corrector path-following algorithm in an advanced-step NMPC framework. We demonstrate the proposed method on a gas-lift optimization case study, and compare the performance of the path-following economic NMPC to a standard economic NMPC formulation.	
11:40-12:00	We_A_Regular_Talk_T1.6	
Modifier Adaptation for Real-Time Optimization of a Gas Lifted Well Network, pp. 31-36	
A. Matias, José O.	Univ. of São Paulo	
Le Roux, Galo A. C.	Univ. of São Paulo	
Jäschke, Johannes	Norwegian Univ. of Science & Tech	
This work studies the steady-state optimization of a Gas Lift Oil Well Network. The optimization approach used is based on the methodology proposed by (Gao et al., 2016), which is a Modifier Adaptation (MA) with gradient estimation from fitted surfaces. The methodology uses plant data to locally approximate the cost and constraint functions of the plant by quadratic functions and then estimates the plant gradients based on the approximated functions. The proposed scheme is simulated using a phenomenological model of the oil well, which was introduced by (Krishnamoorthy et al., 2016). The optimization results showed that the MA scheme is able to increase production, reaching plant optimum, despite the presence of plant-model mismatch without any constraint violations. Furthermore, it was able to provide good quadratic approximations of both cost and constraint functions.	

We_B_Regular_Talk_T1	C1-119	
Drilling Control & Automation (Regular Session)	
Chair: Shor, Roman J.	Univ. of Calgary	
13:00-13:20	We_B_Regular_Talk_T1.1	
Limitations of Topside Actuation for Rejecting Heave-Induced Pressure Oscillations in Offshore Drilling, pp. 37-43	
Strecker, Timm	Norwegian Univ. of Science and Tech	
Aamo, Ole Morten	NTNU	
The heave motion of a floating rig induces pressure oscillations in the well when the heave compensators are disabled during connections. In this paper we discuss several factors affecting the achievable performance when rejecting such pressure oscillations by feedforward by controlling the opening of the topside choke. Here, the well is modeled as a semilinear hyperbolic system with a predictor-based control law that achieves exact pressure tracking at one location in the well in the nominal case. The focus is on wells with large friction (i.e.~deep wells with high-viscosity drilling muds), where large control inputs are required at the topside choke.	
13:20-13:40	We_B_Regular_Talk_T1.2	
Improved Kick and Loss Detection and Attenuation in Managed Pressure Drilling by Utilizing Wired Drill Pipe, pp. 44-49	
Holta, Haavard	NTNU	
Anfinsen, Henrik	NTNU	
Aamo, Ole Morten	NTNU	
A model based method for kick and loss detection and attenuation in Managed Pressure Drilling is presented. The drilling system is modeled as a distributed parameter system combined with a reservoir flow equation containing reservoir pressure and the so-called productivity index as uncertain parameters. A swapping-based design for state and parameter estimation utilizing bottom-hole pressure measurements available via wired drill pipe is combined with a closed loop controller for kick and loss attenuation. The performance of the proposed method is compared to earlier results on kick attenuation in a simulation, showing significant improvement.	
13:40-14:00	We_B_Regular_Talk_T1.3	
Model Order Reduction for Managed Pressure Drilling Systems Based on a Model with Local Nonlinearities, pp. 50-55	
Naderi Lordejani, Sajad	Eindhoven Univ. of Tech	
Besselink, Bart	Univ. of Groningen	
Abbasi, Mohammad Hossein	Eindhoven Univ. of Tech	
Kaasa, Glenn-Ole	Kelda Drilling Controls	
Schilders, Wilhelmus	TU Eindhoven	
van de Wouw, Nathan	Eindhoven Univ. of Tech	
Automated Managed Pressure Drilling (MPD) is a method for fast and accurate pressure control in drilling operations. The achievable performance of automated MPD is limited, firstly, by the control system and, secondly, by the hydraulics model based on which this control system is designed. Hence, an accurate hydraulics model is needed that, at the same time, is simple enough to allow for the use of high performance controller design methods. This paper presents an approach for nonlinear Model Order Reduction (MOR) for MPD systems. For a single-phase flow MPD system, a nonlinear model is derived that can be decomposed into a feedback interconnection of a high-order linear subsystem and low-order nonlinear subsystem. This structure, under certain conditions, allows for a nonlinear MOR procedure that preserves key system properties such as stability and provides a computable error bound. The effectiveness of this MOR method for MPD systems is illustrated through simulations.	
14:00-14:20	We_B_Regular_Talk_T1.4	
Real-Time Rate of Penetration Optimization of an Autonomous Lab-Scale Rig Using a Scheduled-Gain PID Controller and Mechanical Specific Energy, pp. 56-61	
Zarate-Losoya, Enrique	Texas A&M Univ	
Gildin, Eduardo	Texas A&M	
Noynaert, Sam	Texas A&M Univ	
Automation in the oil & gas industry has become a golden goal for major operators, increasing R&D expenditures, and automation related projects are increasingly more common. A miniaturized autonomous drilling machine was built with the objective of performing optimal operations regarding the rate of penetration and energy efficiency the lab-scale rig employs control algorithms, and innovative instrumentation solutions, leading to a large amount of data to be analyzed in real-time to accurately control important drilling parameters such as weight on the bit (WOB) and rotary speed. An scheduled-gain PID Controller was designed and implemented in a micro-controller to accurately adjust the amount of weight on the bit (WOB) and avoid disturbances. High-frequency data was acquired using LabVIEW and analyzed in real- time through the MATLAB programming environment. The data was then passed to MATLAB, where the automated algorithm analysis is performed. The results of the analysis are used in a closed-loop control algorithm to optimize the rate of penetration, energy eefficiency and mitigate drilling failures. The algorithm uses real-time instrumentation data to implement an automated step-test and optimize drilling parameters on the y. Increasing the average rate of penetration and reducing vibration-induced borehole irregularities	
14:20-14:40	We_B_Regular_Talk_T1.5	
Design Principles behind the Construction of an Autonomous Laboratory-Scale Drilling Rig, pp. 62-69	
Loeken, Erik	Univ. of Stavanger	
In recent years, hot topics such as digitalization, machine learning, digital twin and big data have evolved from being envisions on the paper to state of art solutions, expected to revolutionize drilling efficiency in the industry. Drilling automation tomorrow is all about exploiting the current state of technologies available to the entire operation of drilling a well. Not only can drilling automation limit costs and reduce the risk to rig personnel and the environment, but they also give access to locations of considerable potential that previously have been regarded unsafe or uneconomical to operate in. There are however some challenges in keeping up with the ever-increasing pace of the development. For one, testing of novel and innovative solutions is often very expensive because of non-productive rig time during implementation, trial runs and data evaluation. Also, the modern technologies require extensive R&D before on-site testing can even commence. While on land-rigs, some of these costs and risks can be greatly minimized, many offshore solutions lack that luxury. This paper presents an overview of the design principles that go into the construction of a fully autonomous laboratory-scale drilling rig at the University of Stavanger. It aims at describing 1) the engineering principles involved to resemble full-scale drilling operations on the laboratory scale, 2) design considerations and components, 3) component requirements for the rig, 4) control system algorithms for real-time optimization of drilling parameters and detection and handling of drilling anomalies, 5) development of drilling models (drill string dynamics, bit-vibration, etc.) and 6) benefits and future work with the laboratory-scale system. Some of the concepts that are presented in this paper have yet to be implemented during 2018.	
14:40-15:00	We_B_Regular_Talk_T1.6	
Design of Semi-Physics Simulation Training System for Offshore Drilling Electrical Engineers, pp. 70-75	
QIN, YANG	China Univ. of Petroleum	
ZUO, XIN	China Univ. of Petroleum	
Gao, Xiaoyong	China Univ. of Petroleum	
Aiguo, JIANG	China Oilfield Services Ltd	
yan, bo	China Oilfield Services Ltd	
Lei, Fei	China Oilfield Services Ltd	
As the automatic drilling control system is more widely adopted in the field of offshore oil drilling, the integration of the control system has brought the electrical engineers more challenges to the system troubleshooting. There is an urgent need to propose a low-cost training solution for electrical engineers. Therefore, a semi-physics simulation training system of offshore drilling specifically designed for electrical engineers is addressed in this paper. To maintain high simulation fidelity, driller chairs and PLC controllers are copied and realized from field. Mathematical models are built to simulate both normal and fault state of the drilling control system. Different faults are realized by changing the setting parameters of model or switching between faulty models. Finally, with the help of virtual reality technology, the 3-D environment of drilling operation is realized to improve the vision performance. Moreover, an instructor station subsystem is designed to evaluate trainer's performance. Through this simulation training system, the electrical engineers can not only master drilling control system, but also improve the troubleshooting skill.	

We_C_Regular_Talk_T1	C1-119	
Reservoir Simulation, Optimization & Management (Regular Session)	
Chair: Schovsbo, Niels Hemmingsen	Geological Survey of Denmark and Greenland (GEUS)	
15:30-15:50	We_C_Regular_Talk_T1.1	
Production Optimization of a Rigorous Thermal and Compositional Reservoir Flow Model, pp. 76-81	
Ritschel, Tobias Kasper Skovborg	Tech. Univ. of Denmark	
Jorgensen, John Bagterp	Tech. Univ. of Denmark	
We model thermal and compositional reservoir production as mass and energy balances combined with a phase equilibrium constraint. The phase equilibrium constraint is modeled as a thermodynamically rigorous UV flash process. The UV flash problem is a mathematical statement of the second law of thermodynamics, and it replaces the condition of equality of fugacities that is often used. We demonstrate that such a thermal and compositional reservoir model is in a semi-explicit index-1 differential-algebraic form, and we briefly describe a gradient-based single-shooting algorithm for the solution of production optimization problems. We implement the algorithm in C/C++ using the software DUNE, the thermodynamic software ThermoLib, and the optimization software KNITRO. We present an example of optimal water flooding where the injected water has a higher temperature than the reservoir fluid.	
15:50-16:10	We_C_Regular_Talk_T1.2	
Improved Surface-Subsurface Coupled Reservoir Simulation Using Automatic PID Control, pp. 82-87	
Gildin, Eduardo	Texas A&M	
Redick, Brian	Texas A&M Univ	
A PID control scheme has been developed to reduce both non-physical oscillations and computational effort in coupled surface-subsurface simulation. It is shown that the employed control scheme selects superior time steps as compared to a commercial off-the-shelf coupling software (with respect to computational efficiency). Our methods include a novel implementation of a time stepping algorithm in a PID framework. The PID controlled simulation was 297% faster than the default simulation, and incurred less than 0.5% error in production profiles. The control scheme developed can be applied to any commercial simulator where the user can select the time step, without alterations to underlying code.	
16:10-16:30	We_C_Regular_Talk_T1.3	
Oil Production Optimization of Black-Oil Models by Integration of Matlab and Eclipse E300, pp. 88-93	
Hørsholt, Steen	Tech. Univ. of Denmark	
Nick, Hamidreza M.	Tech. Univ. of Denmark	
Jorgensen, John Bagterp	Tech. Univ. of Denmark	
In this paper, we present a software tool for oil production optimization. The software combines the simulation power of a commercial black-oil reservoir simulator with adjoint-gradient capability (Eclipse E300) and state-of-the-art software for constrained optimization (Matlab). The software enables deterministic and ensemble-based optimization strategies for black-oil reservoir flow models and compositional reservoir flow models. The software implements a number of ensemble-based optimization strategies such as the robust optimization, the mean-variance optimization, and the conditional value at risk optimization. Consequently, the software constitutes a powerful tool to assist and guide decision making in the real-life reservoir management process. In this paper, we present the workflow and numerical results for mean-variance optimization of a synthetic 2-dimensional black-oil reservoir using water flooding.	
16:30-16:50	We_C_Regular_Talk_T1.4	
Computation of Phase Equilibrium in Reservoir Simulation and Optimization, pp. 94-101	
Ritschel, Tobias Kasper Skovborg	Tech. Univ. of Denmark	
Jorgensen, John Bagterp	Tech. Univ. of Denmark	
In this paper, we discuss mathematical models and computational methods for computation of vapor-liquid equilibrium in systems relevant to reservoir simulation and optimization. We formulate the phase equilibrium problem as an optimization problem and discuss the UV-flash, the TV-flash, and the PT-flash. The UV-flash occurs for thermal and compositional dynamical simulation problems, the TV-flash occurs for compositional dynamical simulation problems, and the PT-flash occurs for steady-state problems.	
16:50-17:10	We_C_Regular_Talk_T1.5	
Scenario-Based Robust Optimization of Water Flooding in Oil Reservoirs Enjoys Probabilistic Guarantees, pp. 102-107	
Siraj, Muhammad Mohsin	Eindhoven Univ. of Tech	
Saltik, Bahadir	Department of Electrical Engineering, Eindhoven Univ. of Te	
Van den Hof, Paul M.J.	Eindhoven Univ. of Tech	
Grammatico, Sergio	Delft Univ. of Tech	
Model-based optimization of the water-flooding process in oil reservoirs suffers from high levels of uncertainty arising from strongly varying economic conditions and limited knowledge of the reservoir model parameters. To handle uncertainty, diverse robust optimization approaches that use an ensemble of uncertain parameter realizations (i.e., scenarios), have been adopted. In these scenario-based approaches, the effect of considering a finite set of scenarios on the constraint violation and/or the performance degradation with respect to the unseen scenarios have not been studied. In this paper, we provide probabilistic guarantees on the worst-case performance degradation of a scenario-based solution. By using statistical learning, we analyse the impact of the number of scenarios on the probabilistic guarantees for the worst-case solution subject to both economic and geological uncertainties. For the economic uncertainty, we derive an explicit a-priori relationship between the probabilistic guarantee and the number of considered scenarios, while for the geological uncertainty, a-posteriori probabilistic upper bounds on the worst-case solution are given.	
17:10-17:30	We_C_Regular_Talk_T1.6	
Software for Evaluating IPR Composite in Grouped Subsaturated Reservoirs, pp. 108-112	
Mascarenhas, Eduardo	Santa Catarina State Univ	
Alves Pessoa, Oseias	Santa Catarina State Univ	
The Inflow Performance Relationship (IPR) is widely used by the industry to predict well performance and, therefore, optimise production. This work aims to present a simple and objective approach for the initial IPR composite modeling of grouped subsaturated reservoirs within a production well. Unlike other computational implementations for the composite IPR calculation that do not consider the phase change of liquid hydrocarbons in the calculation of the IPR (Guo, 2007), the presented model will take into account the reservoir phase changes below the Bubble point (PB), capturing the existing non-linearities and, therefore, providing more realistic results. The model presented could be used as a starting point for more comprehensive models, allowing the addition of complexities that better depict reservoirs, existing fluids and different subsurface equipment.	

Technical Program for Thursday May 31, 2018
 
Th_Plenary_Talk_T1	C1-119	
Plenary Talk (2) (Plenary Session)	
Chair: Jorgensen, John Bagterp	Tech. Univ. of Denmark	
08:30-09:30	Th_Plenary_Talk_T1.1	
Upstream Process Performance: Non-Intrusive Capture of Large but Hidden Opportunities*	
Slupphaug, Olav	ABB	
Storkaas, Espen	ABB	
The authors are part of an ABB unit that have developed services and solutions for improved upstream process performance over the last 20+ years. The kernel competency underpinning this development and the associated large end-customer value creation is the cross-disciplinary competency of dynamic behavior and operability of real-world physical systems, like oil- and gas production systems. Based on the affiliation of the authors, it might be surprising to learn that – at its core – this competency is completely independent of technology and systems. We will share a decomposition and characterization of the dynamic process behavior – which is key to plant regularity and integrity – and use it as a basis for explaining why we believe the associated competency is hidden, the associated value is large, and that it can be captured non-intrusively at virtually no risk. We will also provide a profile for the hidden competency and discuss how we think it relates to university education as well as the classical upstream disciplines like process, operations, production, reservoir, electrical, mechanical, and automation. Next, we move on to discuss how we believe that operators and owners efficiently and sustainably can identify and capture such large but hidden opportunities. We do this by proposing ways to “embed” the hidden competency throughout the lifecycle of their assets - including our experienced value creation by doing so. In the discussion on value capture, we will address topics ranging from contractual structures via digital technology enablers and project execution to acceleration of continuous improvement of operations.	

Th_A_Regular_Talk_T1	C1-119	
Separation Control & Optimization (Regular Session)	
Chair: Skogestad, Sigurd	Norwegian Univ. of Science & Tech	
10:00-10:20	Th_A_Regular_Talk_T1.1	
Model-Based and Model-Free Optimal Control of a Gas Liquid Cylindrical Cyclone, pp. 113-119	
Ohrem, Sveinung Johan	Norwegian Univ. of Science and Tech	
Kristoffersen, Torstein Thode	Norwegian Univ. of Science and Tech. (NTNU)	
Holden, Christian	Norwegian Univ. of Science and Tech	
Optimal control is important in the oil and gas industry, where small changes of process variables may have significant economical, environmental and safety impacts. Finding the optimal setpoint for a controlled variable may not be straight-forward for an operator, motivating the use of automatic optimization methods. A widely used optimal control method is the model predictive control (MPC) method which requires a dynamic model to predict the future behaviour of the system. The MPC satisfies constraints and finds the optimal input to a plant. However, the requirement of a model can make the method difficult to implement and computation time might be too high for real-time implementation. An alternative to MPC is the Extremum Seeking (ES) method. This method aims to find the input that optimizes the output by slowly perturbing the controlled variable. It does not require a model and is less computationally expensive. In this paper we apply an MPC and an ES optimization scheme to a gas liquid cylindrical cyclone in order to optimize the purity of the gas outlet. Simulations show that both methods are able to find a liquid level setpoint that ensures high quality of the gas outlet stream under varying inlet conditions.	
10:20-10:40	Th_A_Regular_Talk_T1.2	
Slug Handling with a Virtual Harp Based on Nonlinear Predictive Control for a Gravity Separator, pp. 120-125	
Backi, Christoph Josef	Norwegian Univ. of Science and Tech	
Krishnamoorthy, Dinesh	Norwegian Univ. of Science and Tech	
Skogestad, Sigurd	Norwegian Univ. of Science & Tech	
This paper presents a nonlinear model predictive control approach for a three-phase gravity separator model. The aim of the controller is to dampen slug-induced, oscillatory disturbances in the inflow to the gravity separator. This means that, despite the disturbance, the levels of water and oil as well as the pressure should be held at constant operational setpoints. Additionally, a second objective is to dampen the outflows of water, oil and gas and hence keep too large oscillations in flows from downstream equipment. Several constraints are added such as the height of the weir, maximal and minimal allowable levels and pressures as well as constraints on the outflows.	
10:40-11:00	Th_A_Regular_Talk_T1.3	
Control Parings of a De-Oiling Membrane Process, pp. 126-131	
Jepsen, Kasper	Aalborg Univ	
Hansen, Leif	Aalborg Univ	
Yang, Zhenyu	Aalborg Univ	
In offshore oil and gas productions increased attention is directed at the oil-water separation process, as environmental laws demand lower hydrocarbon concentrations in the discharged produced water. Membrane filtration is one possible candidate for significantly improving separation efficiency. However, fouling is one major challenge, where contaminants accumulate within the membrane and thereby adds additional flow resistance. This paper investigates the possibility of improving reference tracking and reducing fouling by improving control pairings and actuator placement. This is achieved by investigating the interaction between commonly deployed decentralized control loops on a membrane process model. The relative input-output interactions are evaluated across varying feed flow rates and membrane flow conductances to ensure that decoupling is maintained beyond the defined operating point. This work concludes that the location of the actuators affects the degree of decoupling significantly and to achieve the maximum degree of decoupling, different actuators must be selected across a variety of operating condition.	
11:00-11:20	Th_A_Regular_Talk_T1.4	
Hydrocyclone Separation Efficiency Modeled by Flow Resistances and Droplet Trajectories, pp. 132-137	
Bram, Mads Valentin	Aalborg Univ. Esbjerg	
Hansen, Leif	Aalborg Univ	
Hansen, Dennis	Aalborg Univ. Esbjerg	
Yang, Zhenyu	Aalborg Univ	
The growing demand to optimize the deoiling performance for offshore oil & gas gives the incentive to improve existing control solutions by means of model-based control solutions. This paper proposes a separation efficiency grey-box model of a deoiling hydrocyclone. Grey-box modeling of deoiling hydrocyclones aims to combine knowledge from fluid dynamics with the data-driven parameter estimation to yield better accuracy than black-box derived models while keeping the computational load much lower than CFD-simulations. The model has to be reasonably accurate in all likely operating conditions and be computed in real-time, in order to be beneficial for advanced model-based control. The developed grey-box model is based on flow resistance and oil droplet trajectory analysis. The model functionally describes how the valve openings, inflow rates, and PDR set-points affect separation efficiency of the considered generic deoiling hydrocyclone. The results are reasonable and provide a fundamental overview of how the operational conditions affect separation efficiency. The model can be extended to account for changes in the axial velocity distribution, coalescence and breakup of droplets.	
11:20-11:40	Th_A_Regular_Talk_T1.5	
Modeling and Control of an Inline Deoiling Hydrocyclone, pp. 138-143	
Das, Tamal	Norwegian Univ. of Science and Tech	
Jäschke, Johannes	Norwegian Univ. of Science & Tech	
In subsea oil and gas production and processing, automatic control of operation is of signicant importance. Typically, processing in subsea elds involves separation of hydrocarbons from water and rejection of water in an environmentally friendly way. Separators such as deoiling hydrocyclones help achieve these objectives. However, control strategy for hydrocyclones is not yet well established in the literature due to a lack of control oriented models for hydrocyclone. In this work we present a model for hydrocyclone based on mass balance equations. Subsequently, we propose a PI controller for controlling the water quality.	
11:40-12:00	Th_A_Regular_Talk_T1.6	
Plant-Wide Optimal Control of an Offshore De-Oiling Process Using MPC Technique, pp. 144-150	
Hansen, Leif	Aalborg Univ	
Durdevic, Petar	Aalborg Univ. Esbjerg	
Jepsen, Kasper	Aalborg Univ	
Yang, Zhenyu	Aalborg Univ	
This paper investigates the optimal control solution using MPC for a typical offshore topside de-oiling process. By regarding the combination of the upstream three-phase gravity separator and the downstream de-oiling hydrocyclone set-up as one integrated plant, the plant-wide control problem is formulated and handled using MPC technology. The de-oiling dynamics of the hydrocyclone are estimated via system identification while the key dynamics of the considered gravity separator are modeled based on mass balance and experimental parameter estimation. The developed MPC solution is simulated and experimentally validated via a lab-scaled pilot plant. The comparison of performances of the MPC controlled system with those of a PID controlled system, which emulates the commonly deployed control solution in most current installations, shows the promising results in optimally balancing the gravity separator's (level) control and hydrocyclone's (PDR) control.	

Th_B_Regular_Talk_T1	C1-119	
Plant-Wide Control & Monitoring (Regular Session)	
Chair: Ruben, Schulkes	Statoil	
13:00-13:20	Th_B_Regular_Talk_T1.1	
Applied Nonlinear Compressor Control with Gain Scheduling and State Estimation, pp. 151-157	
Tengesdal, Njål	Norwegian Univ. of Science and Tech. (NTNU)	
Kristoffersen, Torstein Thode	Norwegian Univ. of Science and Tech. (NTNU)	
Holden, Christian	Norwegian Univ. of Science and Tech	
Subsea gas compressors are key components for both increased and accelerated hydrocarbon production. Compressors enable the development of fields that are remote, in deep waters, or have low and/or reduced reservoir pressure. In this paper, we present a gain scheduling controller for a nonlinear centrifugal compressor model, coupled with an extended Kalman filter estimating an unmeasured system state. The controller is designed for the normal operating region of a GT2252 turbocharger compressor section, planned for future small-scale experiments. The controller is developed with pole placement design on the equivalent linearized dynamics of the nonlinear model in a set of operating points. The linearized closed-loop system in each operating point is then provably locally asymptotically stable. The controller and estimator are analyzed in simulations, and show to achieve tracking of the desired plenum pressure using the estimate of the compressor mass flow.	
13:20-13:40	Th_B_Regular_Talk_T1.2	
Assessment of Flexible Operation in an LNG Plant, pp. 158-163	
Ying Xuan, Ying	Imperial Coll. London	
Pretlove, John	ABB	
Thornhill, Nina	Imperial Coll. London	
Process industries are becoming increasingly reliant on electrical power for reasons of efficiency and sustainability. A large industrial site typically has its own power management system to distribute electricity to the process and to manage electrical contingencies such as partial loss of supply. Recent work has illustrated more flexible alternatives to load shedding whereby an industrial process plant can continue to operate at a lower level making use of available electrical power. This paper presents a way for achieving such flexibility in a Liquefied Natural Gas (LNG) plant. It analyzes the consequences for production of varying the consumed power, and assesses the maximum flexibility within the feasible operating envelope of the process. The study has been conducted by modeling and simulation of an LNG plant using the Linde process with three refrigeration cycles. The results also show the relationships between electrical power consumption and production in terms of production rate and product characteristics. They also show that the vapour-liquid equilibrium plays a crucial role in establishing the operating points and setting the boundaries in which the process has to work. Thus, through the assessment and simulation of an LNG plant, this work demonstrates that flexible operation has benefits over alternatives. It achieves more operating points and therefore adds more flexibility.	
13:40-14:00	Th_B_Regular_Talk_T1.3	
The Extended Kalman Filter for State Estimation of Dynamic UV Flash Processes, pp. 164-169	
Ritschel, Tobias Kasper Skovborg	Tech. Univ. of Denmark	
Jorgensen, John Bagterp	Tech. Univ. of Denmark	
We present an extended Kalman filter for state estimation of semi-explicit index-1 differential-algebraic equations. It is natural to model dynamic UV flash processes with such differential-algebraic equations. The UV flash is a mathematical statement of the second law of thermodynamics. It is therefore important to thermodynamically rigorous models of many phase equilibrium processes. State estimation of UV flash processes has applications in control, prediction, monitoring, and fault detection of chemical processes in the oil and gas industry, e.g. separation, distillation, drilling of oil wells, multiphase flow in oil pipes, and oil production. We present a numerical example of a UV flash separation process. It involves soft sensing of vapor-liquid compositions based on temperature and pressure measurements.	
14:00-14:20	Th_B_Regular_Talk_T1.4	
Potential for Real-Time Monitoring and Control of Dissolved Oxygen in the Injection Water Treatment Process, pp. 170-177	
Durdevic, Petar	Aalborg Univ. Esbjerg	
Raju, Chitra Sangaraju	Billund Vand A/S	
Yang, Zhenyu	Aalborg Univ	
Injection of water into wells is a common practice in offshore oil and gas installations, and here as in many other industries the water has to be deaerated before it is sent through miles of pipelines to reduce the risk of corrosion in those pipelines and other downstream equipment. It requires extremely low concentrations of dissolved oxygen for the corrosion of metals to begin, and removing the dissolved oxygen is currently done in large vacuum deaeration towers, a highly energy demanding process, along with additional injection of chemical oxygen scavengers. In many instances these processes are controlled in a feed-forward manner, where the operators rely on infrequent sampling and corresponding measurements to control the process. The possibilities for optimisation in this field are thus numerous. The main challenges are online measurements of dissolved oxygen and their use in feedback control. This article gives a brief review of the state-of-the-art and investigates the potential of using dissolved oxygen as a reliable feedback parameter, taking inspiration from onshore waste water industries which have been dealing with dissolved oxygen feedback control since the 1970's.	
14:20-14:40	Th_B_Regular_Talk_T1.5	
Plant Wide Oil and Gas Separation Plant Optimisation Using Response Surface Methodology, pp. 178-184	
Andreasen, Anders	Ramboll Energy	
Rasmussen, Kasper Rønn	Aalborg Univ	
Mandø, Matthias	Aalborg Univ	
In this paper we will demonstrate Response Surface Methodology (RSM) applied to process simulation of an offshore oil and gas separation plant. By performing surrogate experiments according to Design of Experiment (DoE) and subsequent construction of multiple linear regression models for the chosen responses the overall separation process is optimised in terms of power consumption under the constraints of quality specification for the gas and oil export, respectively. The fluid treated in the separation plant is rich in NGL (Natural Gas Liquids) which causes challenges in meeting the export specifications. Further, the NGL causes increased condensate recycle in the compression system, thereby increasing power consumption for the compressors as well as increased cooling for heat exchangers. Offshore the NGL is difficult to dispose, which makes fractionation unattractive and the NGL must be exported via the oil (partly stabilised) or via the gas (rich gas) or a combination of the two. Effectively, this violates the export specifications and the NGL must be extracted in on-shore facilities either at the oil or gas receiving facilities. By exploring different options, applying RSM, it is found that in terms of overall power consumption export of NGL with the gaseous products is more effective that exporting the NGL with the partly stabilised oil. The methodology used in the present paper can also be applied to existing production facilities as a generic optimisation tool. Due to the simplicity of the   regression models mimicking the separation plant they can be coupled with the overall process control for potential on-line plant optimisation.	
14:40-15:00	Th_B_Regular_Talk_T1.6	
Derivative-Free Optimization of Offshore Production Platforms Sharing a Subsea Gas Network, pp. 185-190	
Camponogara, Eduardo	Federal Univ. of Santa Catarina	
Machado, Amanda	Federal Univ. of Santa Catarina	
Silva, Thiago L.	Federal Univ. of Santa Catarina	
Merlini Giuliani, Caio	Univ. Federal De Santa Catarina	
Vieira, Bruno	Petrobras	
Teixeira, Alex	Petroleo Brasileiro S.A. (Petrobras)	
Several systems in the real-world arise from the integration of subsystems, bringing about the need for coordination to share limited resources and drive economic gains. Large offshore oilfields fall in this category, such as the Santos Basin, which consists of multiple reservoirs that are operated by platforms interconnected by a subsea gas network. The high content of CO2 imposes constraints on the produced gas delivered to an onshore terminal. To cope with complexity, previous works proposed modeling the production platforms in terms of boundary conditions, thereby decoupling the platform local problems from the optimization of integrated operations. This work follows the same strategy, however proposes the use of derivative-free optimization to find boundary conditions that optimize the overall production. Such an approach adds flexibility from the direct use of simulators for the gas network, while allowing the platform problems to be solved with the method of choice, possibly using mixed-integer nonlinear or linear optimization. The derivative-free approach was shown to be effective in the optimization of the integrated production of the Santos Basin.	

Th_C_Regular_Talk_T1	C1-119	
Big Data & Digital Field Technologies (Regular Session)	
Chair: Slupphaug, Olav	ABB	
15:30-15:50	Th_C_Regular_Talk_T1.1	
A Machine Learning Approach for Virtual Flow Metering and Forecasting, pp. 191-196	
Andrianov, Nikolai	Tech. Univ. of Denmark	
We are concerned with robust and accurate forecasting of multiphase flow rates in wells and pipelines during oil and gas production. In practice, the possibility to physically measure the rates is often limited; besides, it is desirable to estimate future values of multiphase rates based on the previous behavior of the system. In this work, we demonstrate that a Long Short-Term Memory (LSTM) recurrent artificial network is able not only to accurately estimate the multiphase rates at current time (i.e., act as a virtual flow meter), but also to forecast the rates for a sequence of future time instants. For a synthetic severe slugging case, LSTM forecasts compare favorably with the results of hydrodynamical modeling. LSTM results for a synthetic noisy dataset of a variable rate well test show that the model can also successfully forecast multiphase rates for a system with changing flow patterns.	
15:50-16:10	Th_C_Regular_Talk_T1.2	
Physical-Stochastic (greybox) Modeling of Slugging, pp. 197-202	
Kloppenborg Møller, Jan	Tech. Univ. of Denmark	
Goranovic, Goran	Tech. Univ. of Denmark (DTU)	
Poulsen, Niels Kjølstad	Tech. Univ. of Denmark	
Madsen, Henrik	Tech. Univ. of Denmark	
We use state-based stochastic greybox modeling - combining physics and statistics - to model the slugging phenomenon. We extend the model of DiMeglio et al. (2010) to include random components and variable flow coefficients, providing 30 seconds prediction intervals. Altogether six models, each comprising no more than ten equations, are fitted to off-shore riser training data and then cross-validated on new data sets. We use advanced statistical methods to 1) obtain optimal parameters of a given model fitted to measurements, 2) give model predictions with uncertainty intervals, and 3) quantitatively measure the relative goodness of the extended models. These features of our reductive method are general and can be applied to any data sets. For the slugging data, simpler models are preferable over the more complex ones (although the differences are minute for practical purposes in oil and gas industry) and a high statistical significance obtained on the training data does not imply improved long term prediction on independent data. Better physical (mechanistic) models to capture slugging oscillations are needed, ultimately to develop effective control strategies.	
16:10-16:30	Th_C_Regular_Talk_T1.3	
Oil Production Monitoring and Optimization from Produced Water Analytics; a Case Study from the Halfdan Chalk Oil Field, Danish North Sea, pp. 203-210	
Schovsbo, Niels Hemmingsen	Geological Survey of Denmark and Greenland (GEUS)	
Gottfredsen, Sofie N.	DHRTC, Tech. Univ. of Denmark (DTU)	
Schmidt, Karen G.	DHRTC, Tech. Univ. of Denmark (DTU)	
Jørgensen, Thomas M.	DTU Compute, Tech. Univ. of Denmark (DTU)	
Produced water analysis is a direct source of information to the subsurface processes active in an oil field. The information is, however, complex and requires a multidisciplinary approach and access to multiple data types and sources to successfully unlock and decode the processes. We apply data analytics on a combined data set of water chemistry and oil and gas production data measured in the production stream from five wells in the Halfdan field. The field is produced applying extensive water injection to ensure the most efficient water sweep of the reservoir. Relationships between daily production data and water chemistry are examined with Principal Component Analysis (PCA), and systematics with respect to predictability of daily changes in the oil production from water chemistry are examined with partial least square (PLS) regression models. For each well, the water chemistry provides a high degree of predictability with respect to daily oil cut in the production stream. The results have potential for application within prediction of sweep efficiency, by-passed oil and for prediction of water break-through. Full potential, however, depend on successful implementation of water chemistry-oil production analytics into other data domains such as seismic (4D) data and well work-over data.	
16:30-16:50	Th_C_Regular_Talk_T1.4	
Management of System Complexity in HAZOP for the Oil & Gas Industry, pp. 211-216	
Wu, JING	Tech. Univ. of Denmark	
Lind, Morten	Tech. Univ. of Denmark	
The paper gives an insight in how to deal with system complexity from a HAZOP study perspective. The research enlightens the importance of understanding system complexity in oil and gas industry and thereby gradually to change old-fashioned HAZOP industrial practice and improve safety performance in oil and gas industry. Methods and computer aided tools mentioned in the paper can improve HAZOP quality and efficiency with low manpower cost and support brainstorm section in HAZOP studies. The oil and gas industry can implement the method for HAZOP study on real plants to test its usefulness.	
16:50-17:10	Th_C_Regular_Talk_T1.5	
Reliability Improvement of Compressors Based on Asset Fleet Reliability Data, pp. 217-224	
Schulze Spüntrup, Frederik	Norwegian Univ. of Science and Tech	
Londoño, Juan Guillermo	ABB AS, Imperial Coll. London	
Skourup, Charlotte	ABB	
Thornhill, Nina	Imperial Coll. London	
Imsland, Lars	Norwegian Univ. of Science and Tech	
Physical assets of the process industries include compressors, pumps, heat exchangers, batch reactors and many more. A large company that operates over many sites typically manages such assets in a coordinated way as an asset fleet. Strategic planning of maintenance and scheduling requires information about reliability, availability and maintainability of the assets in an asset fleet. The work presented in this paper assesses the reliability of centrifugal compressors based on the data collected in OREDA (Offshore and onshore REliability DAta project). The fault tree (a top-down approach to illustrate all subsystems in a system) has been modeled by focusing on the six main subsystems of the compressor (power transmission, compressor, control and monitoring, lubrication system, shaft seal system, and miscellaneous). All the maintainable items described in ISO 14224 are considered. Based on the failure rates collected in OREDA, the most prevalent failures have been identified via a Pareto analysis. The article gives recommendations which subsystems should be prioritized for maintenance and which types of faults are likely to occur. The main contribution of this paper is an industry-based statistical analysis of the failure mechanisms in centrifugal compressor systems. It is expected to improve the reliability of centrifugal compressor systems and can be implemented in industrial settings with a similar documentation system like OREDA.	
17:10-17:30	Th_C_Regular_Talk_T1.6	
On-Line Fault Diagnosis of Produced WaterTreatment with Multilevel Flow Modeling, pp. 225-232	
Nielsen, Emil Krabbe	Tech. Univ. of Denmark	
Jespersen, Stefan	Aalborg Univ	
Zhang, Xinxin	Tech. Univ. of Denmark	
Ravn, Ole	Tech. Univ. of Denmark	
Lind, Morten	Tech. Univ. of Denmark	
Making sense of alarms can be difficult on oil and gas platforms. Multilevel Flow Modeling provides a structure for modelling plant functionality and inferring causes for alarms and predicting consequences. Currently, Multilevel Flow Modeling has limited application for on-line fault diagnosis. Based on a fault emulated on a pilot plant for offshore produced water treatment, Multilevel Flow Modeling is used for reasoning about causes for triggered alarms. The inferred causes are analysed to investigate the current maturity of Multilevel Flow Modeling for on-line diagnosis.	

Technical Program for Friday June 1, 2018
 
Fr_Plenary_Talk_T1	C1-119	
Plenary Talk (3) (Plenary Session)	
Chair: Yang, Zhenyu	Aalborg Univ	
08:30-09:30	Fr_Plenary_Talk_T1.1	
Optimal and Predictive Control in the Upstream Oil and Gas Industry*	
Jorgensen, John Bagterp	Tech. Univ. of Denmark	
Ritschel, Tobias Kasper Skovborg	Tech. Univ. of Denmark	
Hørsholt, Steen	Tech. Univ. of Denmark	
Hjuler Christiansen, Lasse	Tech. Univ. of Denmark	
Capolei, Andrea	Tech. Univ. of Denmark (DTU)	
We review the applications of optimal control and model predictive control for the upstream oil and gas industry. The applications range from closed-loop reservoir management aimed at maximizing the recovered net present value of an oil reservoir over its lifetime to continuous planning, scheduling and control of process equipment such as pipelines, compressors, risers and separators. We compare model predictive control and optimization in the upstream oil and gas industry to the more mature industrial practice of model predictive control in combination with real-time optimization and even economic model predictive control in downstream chemical, petrochemical, oil refining and energy producing industries. Economic model predictive control is identified as a key enabling technology for increasing profitable production, reducing cost, and automatizing offshore oil and gas production.	

Fr_A_Regular_Talk_T1	C1-119	
Robotics & Nonlinear Control (Regular Session)	
Chair: Durdevic, Petar	Aalborg Univ. Esbjerg	
10:00-10:20	Fr_A_Regular_Talk_T1.1	
Benchmarking of Industrial Stick-Slip Mitigation Controllers, pp. 233-238	
Aarsnes, Ulf Jakob Flø	International Res. Inst. of Stavanger	
Di Meglio, Florent	MINES ParisTech	
Shor, Roman J.	Univ. of Calgary	
The present paper evaluates how three different top-drive feedback controllers influence the occurrence of a stick-slip limit cycle in a rotating drill string. The considered controllers are: 1) The industry standard stiff, high-gain controller, 2) SoftTorque, and, 3) ZTorque. The evaluation is performed as a simulation study on a distributed model of a drill string with a collar section and Coulomb friction as a distributed source term. This model is capable of replicating stick-slip oscillations as caused by the reduction in friction from static to dynamic, and have been shown to yield a good match with field data. The simulation study is summarized as a map for each controller indicating the existence and amplitude of oscillations, parametrized in the key friction parameters.	
10:20-10:40	Fr_A_Regular_Talk_T1.2	
Flexible Architecture for Transparency of a Bilateral Tele-Operation System Implemented in Mobile Anthropomorphic Robots for the Oil and Gas Industry, pp. 239-244	
Garcia, Marcelo Vladimir	Basque Country Univ	
Naranjo, Jose Ezequiel	UTA	
Lozada, Erika Cristina	UTA	
García, Carlos Andrés	Univ. De Las Fuerzas Armadas ESPE	
Espin, Hugo Israel	UTA	
Carmen de las Mercedes, Beltrán Mesías	Univ. TÉCNICA DE AMBATO	
The main problem of the exploration and production sector in the oil and gas industry worldwide, and especially in Ecuador, lies in the extreme environmental conditions inherent to each oilfield, which makes it difficult to perform daily tasks of maintenance or equipment verification. Due to these harsh environments, this industry has seen the need to implement bilateral tele-operation systems with a high degree of scalability that allows the interaction between equipment and trained personnel that could safely perform maintenance activities. In order to achieve this objective, it is necessary to select a standardized messaging protocol that meets the current needs of the Industrial Internet of Things (IIoT) and allows the efficient use of communication channels bandwidth. This paper presents the design of a bilateral tele-operation system that allows the operator to carry out maintenance or remote inspection activities in the Well-Pads located in Petroamazonas EP, Ecuador. For the development of this system, the MQTT protocol is selected over other IIoT protocols because of its high speed of response in real time as well as its low consumption of resources. In the local site a virtual reality environment developed in a 3D graphic engine is implemented. Through input devices an infinite transparency is obtained, besides transmitting the experience and skills of the operator to the slave through the senses of sight, hearing, and kinesthesis 	
10:40-11:00	Fr_A_Regular_Talk_T1.3	
Hovering Control for Automatic Landing Operation of an Inspection Drone to a Mobile Platform, pp. 245-250	
Li, Shaobao	Aalborg Univ	
Durdevic, Petar	Aalborg Univ. Esbjerg	
Yang, Zhenyu	Aalborg Univ	
This paper investigates the hovering control problem of a drone on a 6-DOF mobile platform. An inner-outer loop strategy based on high-gain observer is presented. In the outer loop, the high-gain observer is designed to estimate the states of the drone such that its velocity and acceleration measurements are not necessary, and then a nested saturation controller is designed. In the inner loop, a hybrid controller which can be effectively used for avoiding unwinding phenomenon is applied to regulate the attitude of the drone. Finally, a simulation example is used to demonstrate the effectiveness of the proposed control method.	
11:00-11:20	Fr_A_Regular_Talk_T1.4	
Smart-Spider: Autonomous Self-Driven In-Line Robot for Versatile Pipeline Inspection, pp. 251-256	
Qu, Ying	Aalborg Univ	
Durdevic, Petar	Aalborg Univ. Esbjerg	
Yang, Zhenyu	Aalborg Univ	
This paper presents the design and development of a conceptual prototype of an autonomous self-driven inline inspection robot, called Smart-Spider. The primary objective is to use this type of robot for offshore oil and gas pipeline inspection, especially for those pipelines where the conventional intelligent pigging systems could not or be difficult to be deployed. The Smart-Spider, which is real-time controlled by its own on-board MCU core and power supplied by a hugged-up battery, is expected to execute pipeline inspection in an autonomous manner. A flexible mechanism structure is applied to realize the spider's flexibility to adapt to different diameters of pipelines as well as to handle some irregular situations, such as to pass through an obstacled areas or to maneuver at a corner or junction. This adaption is automatically controlled by the MCU controller based on pressure sensors' feedback. The equipped devices, such as the selected motors and battery package, as well as the human-and-machine interface are also discussed in detail. Some preliminary laboratory testing results illustrated the feasibility and cost-effective of this design and development in a very promising manner.	
11:20-11:40	Fr_A_Regular_Talk_T1.5	
Simplified Modelling and Identification of an Inspection ROV, pp. 257-262	
Enevoldsen, Thomas	Aalborg Univ. Esbjerg	
Einarsson, Emil Mar	Aalborg Univ	
Pedersen, Simon	Aalborg Univ	
Yang, Zhenyu	Aalborg Univ	
The expansion of subsea applications demands extended use of autonomous capabilities within Remotely Operated Vehicles (ROVs), which can reduce the overall operation time and cost. Obtaining a simple but also reasonably precise model is important for an autonomized control strategy. This study outlines a low-dimensional model structure for a commercial underwater inspection ROV, based on simplifying physical assumptions. The respective model parameters are obtained from experimental data. Tuning parameters are then introduced in order to further improve the accuracy of the identified model. Based on a model validation it is concluded that the obtained model contains the main properties of the ROV.	

Fr_Close_Note_Talk_T1	C1-119	
Close Note Talk (1) (Plenary Session)	
Chair: Yang, Zhenyu	Aalborg Univ	
11:40-12:30		Fr_Close_Note_Talk_T1	
Skogestad, Sigurd	Norwegian Univ. of Science & Tech