| dc.description.abstract | History matching is one of the most important activities during the development and management of petroleum reservoirs. Matched models are fundamental to ensure reliable future forecasts, and give an idea of the level of understanding of the geological and reservoir models. Petroleum reservoirs are very complex and there are great difficulties involved in building correct reservoir models. Depending on this level of knowledge, available production data, and complexity of a reservoir, this activity may be very time consuming. In order to achieve matched models, sometimes little changes can be made on the geological and reservoir models, mainly in those attributes with higher uncertainty, for example, relative permeability curves, its distribution through the reservoir, and other parameters with few samples.
One of the objectives of this work is to perform history matching on the Norne Field E-segment using Schlumberger‟s seismic to simulation software Petrel. The history match will be done based on trial and error by modifying some reservoir properties, end point scaling and by modeling and including the aquifer support into the system. The best history match was achieved by modifying the SWCR in the system, modeling an aquifer support using Carter Tracy model and by modifying the horizontal and vertical Permeabilities of the model. After the history match is achieved two prediction strategies are developed and compared, where we did forward modeling to build some confidence level in the reservoir model.
An Uncertainty and sensitivity assessment was done on the reservoir model to analyze the impact certain reservoir properties have on the volume calculations and simulation results in the Norne E-segment reservoir model. The impact of uncertainty in our Sw and contact positions on volume calculations in this model can be seen.
The impact of the grid resolution in placing horizontal wells was also studied, a synthetic model of the Norne E-segment was built selecting the varying grid resolutions both laterally and vertically, then properties were upscaled to the models and a well placed below an impermeable shale zone in each model to determine the optimum location. Using a model with a fine grid resolution enables you to place the well in the best position in the reservoir model. | nb_NO |
