| 摘要 |
A method of estimating formation porosity using a neural network for neutron porosity tools. In the training stage, the near-to-far ratio, environmental variables, such as mineralogy, borehole size, standoff etc., are fed to the inputs and the neural network is trained for obtaining the related true porosity (the output). The trained neural network is implanted into tool's firmware for the real time porosity measurement, accounting for the environmental effects considered during training. |
