Reservoir Properties Modeling Driven By Seismic Data

At present, most of the oil/gas fields in China are in the middle-later development or mature phase after more than thirty years of exploitation. The distribution of remaining oil is characterized by "highly scattered in the whole field and relatively abundant in some areas". This makes the production more and more difficult to develop the remaining oil/gas. This also leads to focus lithologic reservoir instead of structural reservoir. Lithologic reservoirs normally are in small scale, and have irregular distribution, and rapid changes in reservoir lithology. These consist of the bottlenecks for the further development of oil/gas in various phases. Therefore, integration of geological, log, seismic, core and other information with principle of consistency to build a precise reservoir model is critical to develop the remaining oil/gas and to enhance oil recovery.In this thesis, based on previous studies, a new method for reservoir properties modeling driven by seismic data has been investigated. This method is different from the current commonly used methods, and is a deterministic modeling technique. Its main feature is to avoid the variogram, and to use the seismic data as the driven information. A spatial converting function is used to determine reservoir properties. This function is a representation of the spatial variation characteristics of seismic data. With the seismic data as spatial information and conditioning to the well data, this method is able to characterize petrophysical properties of reservoir parameters and its spatial variation.This method is validated using synthetic data. The influencing factors on the spatial converting function are analyzed using the synthetic data. Then, the method is applied to a field case to further verify the technigue.