عنوان مقاله [English]
نویسنده [English]چکیده [English]
One of the most important operations for reservoir characterization and simulation is well logging. Sonic, density and gamma ray logs are run in most of oil/gas wells to determine reservoir properties such as porosity, permeability and lithology. Also these logs can be used for estimation and modeling of pore pressure which is the main subject of this paper. Direct measurement of pore pressure by conventional tools is expensive and produces local data but well logs are less expensive and have continuous data. In this paper, first pore pressure models are reviewed and then pore pressure model of hydrocarbon reservoir located in Southwest of Iran is constructed. This reservoir is old and some of wells had no sonic log, thus this log predicted using artificial neural network method. T-student test showed that predicted sonic logs have acceptable accuracy. In next stage, first for all of wells pore pressure estimated using Eaton’s model and then in one well, the estimated pore pressure log was compared to measured pore pressure data. This comparison showed that the estimated pore pressure log is very close to measured pore pressure. Therefore the pore pressure model for field was constructed using Geostatistics method.