The ISAPP research program aims to increase hydrocarbon recovery, well productivity and field life time through the application of innovative reservoir development and management methods on smart wells and smart fields. Over the last years, more and more high-tech hardware, such as advanced sensors, smart wells, and data centers, have been installed for hydrocarbon producing fields. At the same time computer power has increased significantly. Therefore, possibilities have opened to develop and implement integrated closed-loop, model-driven, optimization technologies.
Scope and History
ISAPP started with the vision that in the near future, hydrocarbon production is going to be managed from a central control room, runs mostly automatically and involve optimization of both daily production rates and the ultimate recovery. Two main complications for achieving this future scenario concern:
- - Insufficient "intelligent" or "smart", automated, integrated concepts and algorithms to improve hydrocarbon production using measurement and control.
- - A lack of qualified staff to actually implement and use such new technologies.
To overcome these complications TNO, Delft University of Technology (TU Delft) and Shell initiated in 2004 the 1st ISAPP program. From a technology perspective, the program was inspired by both measurement and control theory as used in the process industry and data assimilation workflow from meteorology. In the 1st program (over 40 PhD students, support staff and demonstration field studies) algorithms were developed for continuous updating of reservoir models (history matching) based on data from various sources, such as production sensors, remote sensing and time-lapse seismic data. These methods were combined with model based optimization workflows in a closed-loop. In this way, objectives such as improving recovery from oil and gas fields, developing optimally controlled, automated operations, reducing pollution and unwanted emissions and training new, high quality staff were pursued.
At completion of the 1st ISAPP program in 2009, it was clear that a continuation of research on smart wells and smart wells was in the interest of the ISAPP partners. TU Delft and Shell continued cooperating in the so-called Recovery Factory, whereas TNO and TU Delft started in 2011 a 2nd ISAPP program together with industrial partners ENI, Statoil and Petrobras.
The program consists of pre-competitive research, tool development and application of methods and software to field cases. The research is conducted mainly via PhD projects at the TU Delft. Tool development and application of methods and software to real field cases is done by TNO in close collaboration with the industrial partners. Two research themes are central in the ISAPP-2 program:
- - Production Systems (i.e. short-term production optimization), and
- - Subsurface Characterization and Flow (i.e. long-term reservoir management).
Theme: Production Systems
Via concepts from systems and control theory applied in integrated modeling, monitoring and control activities the Production Systems theme aims at stabilizing and optimizing production in order to let operators achieve production targets that result from the long term production contracts.
The main goals for the Production Systems theme are:
- - Flow Assurance: Assure stable production for the complete production system during the lifetime of an asset
- - Production Monitoring: Interpret data to represent the condition of the asset in an informative way
- - Production Optimization: Optimize short term production taking the long term consequences in mind.
Theme: Subsurface Characterization and Flow
Central to the Subsurface Characterization and Flow theme is the closed-loop reservoir management concept. It is the value creating cycle that consolidates technological advancements in data acquisition and processing as well as increased computational capabilities (software and hardware) into higher reservoir recovery or net present value, lower costs or greater flexibility.
In closed loop reservoir management, model-based algorithms to optimize long term objectives under uncertainty (optimized field development planning) are combined with methods to update reservoir models based on monitoring information (optimized history matching).
The main goals for this ISAPP-2 theme are:
- - Bringing improved methods and algorithms of the closed-loop model-based components (initial modeling, data assimilation, model based optimization) to several intelligent practical tools to be used off-line. For example, data assimilation (history matching) is still often done manually, whereas with today's complex reservoirs and increasing amounts of data from various sources this need to be done in a more efficient, automated way, using all available information.
- - Integrate one or more closed-loop model-based tools with asset components of industrial partners to come to an industrial applications and demonstrations on several field case.
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