This paper reviews the trends in applying machine learning to subsurface geothermal
resource development. The review is focused on the machine learning applications over the …

The accurate and frequent measurement of the drilling fluid's rheological properties is
essential for proper hydraulic management. It is also important for intelligent drilling …

Measuring-while-drilling has been considered as an effective method to determine the
mechanical properties of rock. In this paper, drilling models are improved for predicting the …

Rate of penetration (ROP) management is a matter of importance in drilling operations and it
has been considered in different studies. Different machine learning methods such as …

One of the most important problems that the drilling industry faces is drilling cost. Many
factors affect the cost of drilling. Increasing drilling time has a significant role in increasing …

Drilling operations for oil or gas wells are very expensive. Optimizing the drilling efficiency
and increasing the rate of penetration (ROP) will reduce the overall cost of the drilling …

The margin between pore pressure and fracture gradient in new offshore discoveries
continues to get narrower. This poses greater risks and higher cost of ensuring safety of …

The accurate prediction of the rate of penetration (ROP) is crucial for optimizing drilling
parameters and enhancing drilling efficiency in ultra-deep wells. However, this task is …

The objective of this study was to summarize the progress in the application of machine
learning (ML) to enhanced geothermal systems (EGSs), including the entire process of EGS …

Our previous study (Zhou et al., 2023) proposed a fuzzy inference model to inverse the
predominant flow area in fractured reservoirs. Yet, geothermal reservoir parameters in the …