Predicting initial formation temperature for deep well engineering with a new method

Abstract

With the progress of science and technology, human beings explore the energy underground with thousands of meters. As a thermophysical parameter, initial formation temperature (IFT) plays an essential role in deep well engineering. However, it is not easy to predict the IFT accurately before drilling. This work uses a new method to analyze the effect factors of the underground temperature field, and assumes an artificial surface to eliminate the disturbance of the human errors and equipment errors on the surface temperature and thermal conductivity. Considering different distributions of the formation thermal conductivity and the rock radiogenic heat production, an optimized model was established. With this model, the paper predicted the bottom temperature of the main hole of the Chinese Continental Scientific Drilling (CCSD) as 132.80 °C at 4 725 m depth with 0.5% error. When the thermal conduction is dominant in the formation, this simple method can predict the IFT distribution effectively for deep well in the exploration stage. However, it is almost impossible to avoid aquifers in the formation of drilling deep well, an existing drillhole including groundwater is needed to predict for testing the model’s accuracy.