Photoelectric Factor

The photoelectric factor (PEF) quantifies the absorption of gamma rays in materials, offering valuable insights into rock composition in geological applications and material properties in manufacturing. Current research focuses on accurately predicting PEF values using machine learning techniques, such as artificial neural networks, Gaussian process regression, and ensemble methods like random forests, to address missing or incomplete data in well logs or to optimize material properties during additive manufacturing. These predictive models improve the efficiency and accuracy of reservoir characterization in the oil and gas industry and enhance the control and optimization of material properties in advanced manufacturing processes.