The Cornea Field was discovered in January 1997. The Cornea structure represents a relatively simple trap configuration comprising a large, elongated, four-way dip closure, formed by the drape of Albian age sediments over a northeast to southwest trending positive basement feature. It is located on an active hydrocarbon migration fairway with proven charge and is capped by a regionally extensive Albian seal. An associated Direct Hydrocarbon Indicator extends over an area of 50 km2 and this feature coincides with gas-fluid contacts throughout the field.Subsequent to the initial Cornea discovery wells in permit WA–241-P, further exploration drilling took place within WA–241-P, and also within two, newly-acquired, adjacent permits, WA–265-P and WA–266-P, during 1998 and 1999. Detailed field assessment during and subsequent to these wells, involving geological, geophysical and reservoir engineering disciplines, indicated that the field consisted of an extensive gas cap over a thin, laterally discontinuous oil rim. The poor quality of the Lower Cretaceous marine reservoir succession and the extremely low expected oil recovery indicated that recoverable volumes would be low.This paper contains a review of the data and studies that led to a full understanding of the field. Key learning points from the case study are introduced here and may help future exploration campaigns in other areas.

Shell's new Modular Reservoir Simulator (MoReS) has been equipped with a comprehensive and versatile user interface called FrontEnd. Apart from providing a user-friendly environment for interactive reservoir simulation, FrontEnd serves as a software platform for other dynamic simulation and reservoir-engineering applications. It offers to all supported applications a common user interface, enables the re-use of code and reduces overall maintenance and support costs associated with the embedded applications. Because of its features, FrontEnd facilitates the transfer of research results in the form of operational software to end users. When coupled with MoReS, FrontEnd can be used for pre- and post-processing and interactive simulation. The pre-processing options allow data to be inputted by means of various OSF/Motif widgets containing a spreadsheet, text editors, dialogues and graphical input. The display of the input data as well as the post-processing of all simulation results is made possible by a variety of user-defined plots of tabular (e.g. timestep summary) and array (simulation grid) data. During a simulation user-defined plots can be displayed and edited, allowing a close inspection of the results as they are being calculated. FrontEnd has been equipped with a powerful input command language, which gives the batch user as much flexibility and control over the input as the interactive user. Introduction The introduction of powerful workstations offers opportunities to change the way reservoir simulations are carried out. Most current reservoir-simulation software require the engineer to assemble a data deck with a text editor or dedicated pre-processors, submit the run in batch mode, wait for its execution and then investigate the results using post-processing software. Yet current hardware is powerful enough to run interactive simulations whose results can be monitored as they are being calculated. Such interactive simulation can increase the efficiency of the engineer significantly. Since the data can be immediately displayed and validated, obvious errors can be detected early and alternative scenarios can be quickly evaluated. To make Shell's new Modular Reservoir Simulation package MoReS fully interactive, it has been equipped with a versatile and powerful user interface called FrontEnd. BRIEF DESCRIPTION OF MORES The MoReS reservoir simulator offers a large choice of fluid descriptions, ranging from standard black or volatile oil to user-specified multicomponent mixtures. In addition, tracers, polymers and chemical reactions are handled for various specialist applications (e.g. reservoir souring, environmental applications etc.). The simulator can be operated in either a non-fractured or fractured mode. In the latter case dual porosity, dual permeability and block-to-block flow (oil re-infiltration) can be taken into account. P. 545

During the last several years Shell and its affiliates have initiated a significant number of Enhanced Oil Recovery projects covering chemical, thermal and miscible flooding applications in a variety of geological and hydrocarbon settings.Key in de-risking and sanctioning these projects is a far more detailed understanding of the fundamentals in rock and fluids physics and chemistry that have an overriding impact on the ultimate recovery and project economics. This required a significant upgrade of the experimental capability to measure relevant rock and fluid properties as well as the ability to visualize and model the EOR processes at various geological and time scales. State of the art experimental facilities have been built to enhance visualisation and understanding of flow processes in cores as well as to measure accurate physical and chemical properties.The proprietary reservoir simulator and modelling toolkit has been upgraded to include the relevant EOR processes and rock / fluid interactions in sufficient detail, covering for example In-Situ Combustion, Polymer floods, Designer Water™ flooding, Alkaline Surfactant Polymer flooding, Thermally Assisted-Gas-Oil-Gravity-Drainage, In-Situ Upgrading, a variety of Solvents and Hybrid applications at various scales, ranging from core scale to full field simulations.The Smart Fields concept pursues continuous optimisation of hydrocarbon assets, 24 hours a day, and 7 days a week. This optimisation covers locating and recovering hydrocarbons, improving performance of production (well) facilities throughout the field life cycle on timescales ranging from seconds to field life. An important part of the Smart Fields concept is Closed Loop Reservoir Management (CLRM), which ensures that data gathered in the operations phase is used to improve quality of reservoir models and allow a faster field management cycle. Novel robust mathematical optimisation algorithms and control methods are rapidly maturing to assist automatic history matching, high-grading geological reservoir model ensembles and reducing the uncertainties. The desired outcome is better well offtake or injection policies that are also robust against remaining key uncertainties.Extending the Smart Field concepts to EOR requires the definition of the appropriate levels of smartness for EOR projects for each element of the Smart Field Life Cycle, which consists of: data acquisition, modelling, integrated decision making and operational field management, each with a high level of integration and automation.

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