The identification of sweet spots, areas within a reservoir with the highest production
potential, has been revolutionized by the integration of machine learning (ML) algorithms …

Calibration of reservoir models for unconventional hydrocarbon reservoirs requires
permeability data as input. Accurate permeability prediction from velocity data is desirable …

We are in an era where digital technologies are developing at exponential rates and
transforming industries wholesale. The confluence of machine learning advances …

Identification of petrophysical and geomechanical" sweet spots" along multi-fractured
horizontal wells (MFHWs) is an important step in the optimization of hydraulic fracture …

Prediction of mineralogical compositions along multi-fractured horizontal wells (MFHWs)
using indirect methods, for the purpose of characterizing lithological and rock brittleness …

A prediction method for the EUR (Estimated Ultimate Recovery) of tight sandstone gas
reservoirs based on a composite machine learning approach was proposed and applied in …

This project measured the physical, mechanical, and elastic properties of a range of
chondrite lithologies, a domain that was inadequately explored. The properties measured …