Improvement of petrophysical evaluation in a gas bearing carbonate reservoir–A case in Persian Gulf

• Application of shear wave velocity and effective porosity in evaluation of a gas bearing carbonate reservoir was studied.
• Effective porosity has a higher impact on improvement of porosity evaluation compared to shear wave velocity.
• Simultaneous application of shear wave velocity and effective porosity improves porosity evaluation in gas bearing sections.

Significant digenetic processes such as dolomitization, chemical dissolution, reprecipitation, fracturing, etc. create complex pore size distribution in carbonate reservoirs. Contrary to sandstones, the pore size distribution in carbonates is bimodal or trimodal. The existence of organic material increases the complexity, too. The dominant carbonate minerals are dolomite and calcite, commonly associated with a variable content of anhydrite. Anhydrite content negatively impacts the well log interpretation and complicates carbonates behavior compared to sandstones. In addition, the existence of gas affects the whole interpretation by underestimating porosity, due to low hydrogen index. Therefore, to have an accurate hydrocarbon in place estimation, we have to reduce the abovementioned problems in the interpretation.This paper presents existing methods in evaluation of a gas bearing carbonate reservoir in Persian Gulf and tries to improve the evaluation using new logs. The initial evaluation is based on traditional logging tools such as Gamma Ray (GR), Resistivity Logs, Density, Neutron and Sonic. Since there exists only core porosity, we will validate the model by them. Porosity of the cores do not correspond to the calculated properties by the initial model.To improve the characterization, dipole sonic imager and nuclear magnetic resonance (NMR) logs included in the model. Effective porosity (total porosity corrected by shale volume) obtained from NMR has a better impact on the initial model compared to shear wave velocity. If both of the parameters are added to the dataset simultaneously, the obtained porosity approaches to the laboratory measurements, especially in gas bearing intervals. The equations of porosity versus core porosity were calculated using the method of least square regression and higher values of R2 were obtained. The average calculated porosity approaches to the average porosity of laboratory measurements.