2006SPE Russian Oil and Gas Technical Conference and ExhibitionRequires access

A Model for Gas Coning and Rate-Dependent Gas/Oil Ratio in an Oil-Rim Reservoir

Are Mjaavatten, Robert Aasheim, Steinar Sælid, Oddvar Gronning

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Abstract

Abstract In oil rim fields a thin oil layer lies between an aquifer and a gas cap. Oil may be produced from such fields using horizontal wells. Production will lower the local gas/oil contact near the well in a process called gas coning (or more accurately, cresting). After gas breakthrough, the gas/oil ratio (GOR) from the well may vary strongly with the production rate. The ability to predict this dependency is essential for production optimisation for such fields. We have developed a mathematical model that can predict gas coning behaviour and the resulting rate dependent GOR with a surprisingly high degree of accuracy over periods of several months or more. We combine a dynamic model that describes the essential reservoir behaviour with a highly simplified description of the interaction between the well and the surrounding reservoir. The full model has three adjustable parameters that allow us to fit the behaviour to individual wells, using historical oil and gas production rates. The model forms the basis of the GORM (Gas/Oil Ratio Model) computer program that since early 2003 is in regular use for production planning and optimisation at the Troll field. We have also tested the model on wells in other fields, with encouraging results.

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Abstract In oil rim fields a thin oil layer lies between an aquifer and a gas cap. Oil may be produced from such fields using horizontal wells. Production will lower the local gas/oil contact near the well in a process called gas coning (or more accurately, cresting). After gas breakthrough, the gas/oil ratio (GOR) from the well may vary strongly with the production rate. The ability to predict this dependency is essential for production optimisation for such fields. We have developed a mathematical model that can predict gas coning behaviour and the resulting rate dependent GOR with a surprisingly high degree of accuracy over periods of several months or more. We combine a dynamic model that describes the essential reservoir behaviour with a highly simplified description of the interaction between the well and the surrounding reservoir. The full model has three adjustable parameters that allow us to fit the behaviour to individual wells, using historical oil and gas production rates. The model forms the basis of the GORM (Gas/Oil Ratio Model) computer program that since early 2003 is in regular use for production planning and optimisation at the Troll field. We have also tested the model on wells in other fields, with encouraging results.

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Available abstract

Abstract In oil rim fields a thin oil layer lies between an aquifer and a gas cap. Oil may be produced from such fields using horizontal wells. Production will lower the local gas/oil contact near the well in a process called gas coning (or more accurately, cresting). After gas breakthrough, the gas/oil ratio (GOR) from the well may vary strongly with the production rate. The ability to predict this dependency is essential for production optimisation for such fields. We have developed a mathematical model that can predict gas coning behaviour and the resulting rate dependent GOR with a surprisingly high degree of accuracy over periods of several months or more. We combine a dynamic model that describes the essential reservoir behaviour with a highly simplified description of the interaction between the well and the surrounding reservoir. The full model has three adjustable parameters that allow us to fit the behaviour to individual wells, using historical oil and gas production rates. The model forms the basis of the GORM (Gas/Oil Ratio Model) computer program that since early 2003 is in regular use for production planning and optimisation at the Troll field. We have also tested the model on wells in other fields, with encouraging results.

Key concepts: Petroleum engineering, Gas oil ratio, Fossil fuel, Natural gas field, Aquifer, Oil production, Production rate, Environmental science

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