A controller providing a link between reservoir and network simulators has been developed to facilitate reservoir and production management. An optimizer included in the network simulator ensures that optimal management of the coupled system is achieved. The utility of the tool is first tested using a very simple reservoir model with one injector and a single smart producer, and subsequently demonstrated for water-alternating-gas (WAG) injection in two North Sea field cases. For the synthetic test case, various optimization scenarios are explored with the coupled system and compared to standalone flow simulation results. In the North Sea Field 1, optimum oil production is achieved by adjusting the settings of the surface valves as well as the downhole intelligent completion valves (ICVs); in Field 2, gas lift is optimized over time. The coupled system has given more accurate and realistic results in all cases. For the synthetic test case, the coupling gives a significantly higher production than the standalone reservoir simulator run whatever the optimization scenario. For the Field 1 smart well case, the coupled results match historic performance more closely because the pressure drop across the flow lines and surface facilities, the interaction among the wells in the production network, and the boundary conditions are all accounted for. For the gas lift optimization case, the coupled system gives more realistic results with respect to the potential for increased oil production and recovery than the standalone reservoir and network models. Introduction Achieve Reservoir and Production Management Goals Reservoir management is normally achieved using numerical simulation to model the performance of the reservoir under different scenarios of well placement, number of wells, and production and/or injection profiles. However, reservoir simulators do not generally model the production downstream of the wellhead, and so the production network effects on the behavior of the overall system are not fully acknowledged. Flow simulation of the reservoir system also does not account for all the boundary conditions set at the surface, such as the suction pressure of the separator. This may have a direct impact on the evaluation of the production targets that will actually be achieved. On the other hand, production management typically uses surface network nodal analysis tools that fully account for those effects but can only model the reservoir as a homogeneous ‘tank’ of uniform properties. Moreover, reservoir management aims at optimizing the reservoir performance over the field life by maximizing the recovery factor at the minimum cost, while production management is concerned with optimizing the production system capabilities on a day-to-day basis. Thus, reservoir and production management have complementary goals in field development, but on different time scales, and by using separate tools there is no guarantee that one will achieve a solution that satisfies both aims. Therefore, the integration of the capabilities of both reservoir and production system simulators appears to be a critical technology for field development and optimization.

Real Time production workflows introduce significant changes to the production management practices. The introduction of new technologies such as affordable satellite communication, local field area networks, global connectivity to the internet, collaborative workspace (both virtual and actual war room concepts) and data mining agents have all contributed a number of enhancements in the production arena. Although the early gains obtained during the implementation of real time workflows can be as large as increase of 50% of production in some assets, the long term gains are typically in the order of 3 to 8 %. The paper provides a number of approaches to quantify the value of enabling traditional production processes with real time information and activities. This paper also presents some inroads and lessons learnt in terms of the deployment of a new breed of real time services offered to support daily production management activities. These Activities include: Electrical Submersible Pump (ESP) monitoring and surveillance, real time productivity monitoring based on interpretation of downhole sensors and multiphase flowmeters. The analysis of over 600 installations worldwide provide insights of solutions and opportunities in varying environments covering a wide range of challenges such as North American cost sensitive context to Colombian security conscious field operations and harsh environment deployments. Among the main challenges of the real time infrastructure for the production world, is the infamous management of legacy systems (old and aging SCADA systems, archaic instrumentation, challenging production sharing agreement financial terms). The paper offers a number of recommendations, and establishes a methodology to the deployment of workflows power by real time information. A short discussion of the relative benefits of hosted services versus fully integrated solutions housed within the asset IT infrastructure provides key elements to operators to decide what would be the long term cost effective solution to be selected for a given asset. Introduction The need for real-time or relevant data feed to support production workflows is not new. Permanent monitoring devices have been in use in the oil field industry since the beginning of the century for surface applications (earlier in the form of pressure and temperature strip charts). The field of downhole instrumentation has been tackled in various ways since the early 60s. Engel (1963) introduced an electromechanical gauge and showed data from 1959–1961. Since the mid 70s permanent electronic gauges have been deployed in wells on dry completions, and subsea in the early 80s (Bezerra et al, 1992). The value of such measurements was well recognized at that time, and it is not surprising that they are becoming more and more popular in the upstream oil and gas arena. The recent evolution of various information technologies brings new possibilities for deploying monitoring services to facilitate production workflow. The Digital Oil Field of the Future (DOFF) study, Cambridge Energy Research Associates, Inc., (CERA, 2003) identifies monitoring and control as one of five key technologies that will impact the oil and gas industry in the future. With a number of such implementations already in place, it is now possible to provide examples and recommendations for a successful realization of these technologies in the production environment. However, the full realization of the value of any real time workflows lies beyond the availability of an organized and contextualized form of the production data sets. In other words, this is not just a data management issue. Automation of data acquisition, including data validation and data preparation, are key aspects of a real-time workflow. Likewise, the systematic computation of key performance indicators and the ability to generate events based on these computations, such that alarm status of well and network performance can be updated automatically, are the gems that benefit production management.

Real Time Production is not just a buzzword today. A number of assets is experimenting implementations of real time production systems and some have made the leap of faith and rely extensively on it to optimze part of their production processes. A number of trial and errors have enabled to construct a number of rules of thumbs in the design, implementation and operation of such system. Because of the easy (or easier) case for value generation, the surveillance and optimization of artificial lift systems have been preferential targets for such implementations (in this paper we will focus on ESP operations). One of the main operational issues related to the realisation of the value expect from this type of project is to ensure that all of the required information is correct. This is not a little feat! This paper describes the challenge of the federation of the information required to perform automated surveillance of ESP in remote wells. The end-to-end delivery of reliable workflows requires the following elements:–Validated streaming real time information (pump measurements, intake and discharge pressures etc...)–Validated episodic information (well test flowrates, choke and back pressure information)–Static information (tubing size, formation parameters etc...) The reliability of a real time production workflow in an automated system requires the insurance that all of these three types of information be correct. The evaluation of the dependency of reliable information of information to the quality and reliability of the final surveillance information is demonstrated through the use of graph analysis. This methodology enables to focus the field data capture in the right areas, which are not always intuitive. Field examples from South America demonstrate the value of such real time production workflows. Case histories also demonstrate instances of raising wrong alarms and the analysis of such event confirms the theoretical sensitivity analysis. The paper concludes with a number of recommendations towards the field practices related to the real time enabling of the production operations some that can be extended to the futuristic full field automation. Introduction The need for real-time or relevant data feed to support production workflows is not new. Permanent monitoring devices have been in use in the oil field industry since the beginning of the century for surface applications (earlier in the form of pressure and temperature strip charts). The field of downhole instrumentation has been tackled in various ways since the early 60s. Engel (1963) introduced an electromechanical gauge and showed data from 1959–1961. Since the mid 70s permanent electronic gauges have been deployed in wells on dry completions, and subsea in the early 80s (Bezerra et al, 1992). The value of such measurements was well recognized at that time, and it is not surprising that they are becoming more and more popular in the upstream oil and gas arena. The recent evolution of various information technologies brings new possibilities for deploying monitoring services to facilitate production workflow. The Digital Oil Field of the Future (DOFF) study, Cambridge Energy Research Associates, Inc., (CERA, 2003) identifies monitoring and control as one of five key technologies that will impact the oil and gas industry in the future. With a number of such implementations already in place, it is now possible to provide examples and recommendations for a successful realization of these technologies in the production environment.

Reservoir and production management practices can benefit from the use of information obtained in real-time. This paper focusses specifically on the gains obtained from the continuous monitoring of naturally flowing and artificially lifted wells.The deployment of real-time production workflows is an important enabler to improve the value of oil and gas assets. The impact is seen in areas such as:the improvement of production (well productivity), through the reduction of deferred production and increased productivity;reduction of operating costs (OPEX);reduction of repair time;reduction of capital expenses (CAPEX);capture of best (and worst) practices;increased operational flexibility; andimproved efficiency of workforce.Field examples over a range of applications covering both artificially lifted wells to naturally flowing wells demonstrate the value of real-time monitoring and relevant-time surveillance and diagnostic applications. Examples of permanent monitoring systems installed at subsurface and/or at surface illustrate how operators can optimise the value of new and existing assets. Although much of the technology has been available for years, deployment in actual field operation is still a challenge. Several best practices are suggested to improve implementation success. The human component in this oil field revolution is important and cannot be under-estimated. The success of real-time enabled workflows can only occur if the workforce fully cooperates and buys-in to the solution. The inertia of legacy practices can derail the change management process if not considered early in the implementation.This paper discusses several industry approaches to product and service delivery of real-time enabled production workflows, and the various possible implementations. The commercial and physical implementations of these production workflows can range from remotely hosted solutions with no footprint on the operator premises, to fully integrated solution using and integrating legacy system of the oil and gas company. A segmentation of these approaches facilitates the selection process depending on parameters such as the size of the asset, legal constraints, availability of expertise. The value of the benefits of each of these approaches also provides a better understanding of the probable gains that may be achieved in the short to long-term time frame.

A new total-concept approach to achieving reliability for intelligent completion systems has produced successful installations in the BP Wytch Farm field and in the Norsk Hydro Troll and Oseberg fields. Intelligent monitoring and inflow-control systems optimize field production and ultimate recovery. Total reliability is critical to realizing these benefits. Reliability in all aspects of the completion, from equipment design to installation, is built into the engineering process. Reliability modeling and lifetime forecasts are based on system architecture; survival analysis is based on track records and accelerated testing of components. Modeling and forecasts are refined throughout the project to guide and accelerate design and development. Introduction Reliability of flow-control devices is a critical concern because, like permanent gauges, they are meant to last for the life of the well, yet they are not usually recovered for repair, maintenance or post-mortem failure analysis. However, whereas permanent monitoring systems have at least two decades of engineering evolution and field experience, downhole flow-control devices and the equipment associated with "intelligent wells" are relatively new since the first of such installations were made three years ago. These considerations make long-life field trials for new equipment impractical before commercial installation; therefore, identification of risks and reliability assessment through other techniques is essential. Industry initiatives by BP, Norsk Hydro, and others have stressed the importance of a structured approach to reliability and testing as part of the development process.1,2, 3 This paper addresses how the development of reliable intelligent wells can be accelerated to achieve the benefits they offer. The benefits of a total-concept approach to reliability have been demonstrated during the last three years in the development and field deployment of seventeen downhole flow control devices in twelve different wells, including the world's first all-electric system. The approach uses a mosaic of reliability and testing techniques. These combine analytical and experimental methods as part of the engineering development process from equipment design to field deployment and operation. These are described along with the benefits and limitations of each method. Background Recent studies have shown permanent gauge installations have achieved a 90%-5 year reliability for temperatures lower than 100°C, but this drops to about 50% in wells up to 150°C based on field track records for the past 6 years (Fig. 1).2,3 Detailed analysis of field track records shows that the cable and its connections cause the majority of failures. Therefore design improvements and reliability qualification testing (RQT) have focused on this area, especially since an electric cable and its connections provide the backbone for new-generation, electrically operated downhole intelligent completion valves and sensors. Field experience with thousands of hydraulically operated subsurface safety valves has demonstrated their high reliability and long life. In addition they are cost effective and straightforward to install. However, an operational drawback of hydraulic valves is their limited flow control resolution, whereas an electric valve is infinitely adjustable over its openclosed range. Also an all-hydraulic system alone does not offer the possibility to provide downhole measurements of pressure, temperature and fluid flow rate.