Oil and gas production from a cluster of wells is conventionally relatively difficult to manage, at least partly due to field conditions, subsurface uncertainty and the multiphase nature of the well effluents. This can lead to late diagnosis of production problems, slow and conservative handling of production constraints and restricted understanding of subsurface potential. FieldWare Production Universe (FW PU) is a software application developed by Shell International Exploration & Production and Shell Global Solutions International that allows data driven well models to be constructed and updated from real time production data, and thereafter applied to track well-by-well production in real time. This paper updates on extensions of FW PU data driven techniques and also on the experience so far on the wide scale field implementation, roll out and support of the technology.

The successful embedding of a real time technology that such as FieldWare PU, which allows a step changes in the level of surveillance of well-by-well production, and the realization of maximum value from its use is a non-trivial exercise. In an ideal implementation, the software application needs to match the dynamic physical production elements (reservoir inflow, well performance, production processing and testing facilities) and the capabilities of the production staff as well as their production management processes. Key elements of the FW PU roll out in field operations include evaluation of actual production surveillance challenges vis-à-vis the value of the tool to be introduced, hardware and software readiness checks, clear setting of goals and expectations, post implementation evaluations, training of users and super-users, adjustment of workflows, and embedding the use of the application into the relevant operational processes.

This paper further discusses extensions of the data driven approach to a wide spectrum of applications, including real time operational optimization, the tracking of well productions in subsea and smart wells, and for specific types of production operations such as for beam pumped wells as well as wells which are intermittently operated. In particular the application of data driven techniques to beam pump pump-off controls, circumventing the need for load cells, is highlighted.

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