Permeability prediction is a key and difficult task in hydrocarbon reservoir characterization.
Machine learning has long been studied for permeability prediction using porosity and …

Porosity, as a key parameter to describe the properties of rock reservoirs, is essential for
evaluating the permeability and fluid migration performance of underground rocks. In order …

Geological interface depth modeling from the gravity field data is crucial for the exploration
of oil and gas, map** of sediment-basement interfaces and many other geological …

Tight sandstone has strong pore heterogeneity and complex pore structure, and the pore
structure of tight sandstone varies with different permeability. To study the differences in the …

The knowledge of fracture properties and its geometrical patterns is often required for the
analysis of mechanical and flow properties in fractured reservoirs, as fracture …

Accurate classification and characterization of pore–crack structures are substantial to
carbonate reservoirs in terms of reservoir exploration and development. Although …

This paper explores the innovative application of machine learning and neural network
algorithms to predict pore types in carbonate rocks using experimental acoustic properties …

Single-well acoustic imaging in logging-while-drilling (LWD) has important application
potential in evaluating cluster-well drilling safety as it can be applied to the real-time …

Real-time monitoring of wellbore status information can effectively ensure the structural
safety of the wellbore and improve the drilling efficiency. It is especially important to …

The utilization of hydraulic fracturing technology is indispensable for unlocking the potential
of tight oil and gas reservoirs. Understanding and accurately evaluating the impact of …