New method predicts underground fluid levels using seismic data accurately.
Scientists developed a method to link NMR log-derived free fluid porosity with seismic attributes using regression and neural networks. They connected well logs to seismic data, converted seismic data to acoustic impedance, and used regression to find the best attributes for predicting porosity. A neural network was then used to make predictions, with the method applied to the South Pars Gas Field in the Persian Gulf Basin.