Immiscible fluid–fluid displacement dynamics is a crucial element to understanding and
engineering many subsurface flow applications, including enhanced oil recovery and …

Decline curve analysis (DCA) is one of the most widely used forms of data analysis that
evaluates well behavior and forecasts future well and field production and reserves. Usually …

Conventional foam modelling techniques require tuning of too many parameters and long
computational time in order to provide accurate predictions. Therefore, there is a need for …

Data-driven decisions powered by machine-learning methods are increasing in popularity
when it comes to optimizing field development in unconventional reservoirs. However, since …

Today, raw data on any industry is widely available. With the help of artificial intelligence (AI)
and machine learning (ML), this data can be used to gain meaningful insights. In addition, as …

In all development phases of brownfields, identifying sweet spots and the potential
remaining oil in place to be recovered is a cornerstone of reservoir management studies and …

Many important business decisions and planning in unconventional reservoirs rely on a
reliable forecast on well performance. Common practices like statistical type curves …

An Augmented AI approach has been developed to optimize completion design parameters
and access the full potential of unconventional assets by leveraging big data sculpting …

Electric Submersible Pumps (ESP) are common artificial lift equipment for boosting well
productions. One of the challenges faced with ESP applications is the ESP system reliability …

Waterfloods are amongst the most widely implemented methods for oil field development.
Despite their vast implementation, operational bottlenecks such as lack of surveillance and …