Norne Field manual history matching & analysis
Master thesis
Permanent lenke
http://hdl.handle.net/11250/239425Utgivelsesdato
2010Metadata
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Sammendrag
A reservoir engineer’s most important job function is to predict the production future of a reservoir from given production rates. To be able to do this job the first requirement is updating a petroleum reservoir model using production data. This process is called history matching. It is an essential requirement before a reservoir model becomes acceptable for production forecasting.
To accomplish this task engineers have developed several methods over a period of many years. These range from simple decline curve analysis techniques to sophisticated multidimensional, multiflow reservoir simulators. Whether a simple or complex method is used, the general approach taken to predict production rates is first to calculate producing rates for a period for which the engineer already has production information. If the calculated rates match the actual rates, the calculation is assumed to be correct and can then be used to make future predictions. If the calculated rates do not match the existing production data, some of the process parameters are modified and the calculation repeated. The process of modifying these parameters to match the calculated rates with the actual observed rates is referred to as history matching.
Mainly two types of history matching techniques are employed, Manual History Matching (MHM) and the Automatic History Matching (AHM). In manual history matching the engineer selects the input data to be adjusted according to the available knowledge of the field, engineering judgment and experience. Automatic history matching uses computer assisted logic to adjust the reservoir data. While this may remove some human error based on bad judgement or incomplete knowledge even then the engineer is required to review the match and analyze the results critically.
This thesis employs the Manual History Match method and all its related techniques will be employed to match the observed and calculated data to the best possible values.