Title of article :
Pore throat size characterization of carbonate reservoirs by integrating core data, well logs and seismic attributes
Author/Authors :
Hosseinzadeh ، Sirous Oil and Energy Petropars Company , Kadkhodaie ، Ali - University of Tabriz , Mosaddegh ، Hossein - Kharazmi University , Kadkhodaie Ilkhchi ، Rahim - University of Tabriz
Abstract :
The current study proposes a three-step approach for pore throat size characterization of these reservoirs, by integrating core data, well logs and 3D seismic volume. In this respect, first the pore throats size was calculated using Pittman and Winland models based on routine core analysis data and calibration the results with the laboratory-derived capillary pressure curves. In the second step, the pore throat size as a continuous log was calculated using petrophysical data for each studied well. Finally, the calculated pore throat size log was tied to 3D seismic data at well locations. The results show that seismic attributes including acoustic impedance, amplitude envelope, filter 15/20-25/30 and derivative instantaneous amplitude are the best predictor set for converting the 3D seismic volume into a pore size cube by a probabilistic neural network mode. The methodology illustrated in this study, was employed on Ilam carbonate reservoir in one of the southwestern oilfields of Iran. The findings demonstrate that seismic data in combination with core and well log data could be considered as an effective tool for spatial modeling and characterization of pore throat size in carbonate reservoirs.
Keywords :
Pore throat size , artificial neural network , seismic attributes , seismic inversion , carbonate reservoirs
Journal title :
Geopersia
Journal title :
Geopersia