Neural networks may be used to determine and predict formation dip angles and perform quality assurance assessments from data collected with a multi-component induction tool used for well logging. The neural networks make use of corrected, rotated and normalized data to provide the predictions and assessments. Synthetic data using various models is used to train the neural networks. The teachings herein provide for real-time determinations with a substantial degree of accuracy in the results.