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This paper presents a step-by-step work flow to facilitate history matching numerical simulation models of hydraulically fractured shale wells.

In the 2020 Completions Technology Focus, I stated that digitization will forever change how the most complex problems in our industry are solved. And, despite another severe downturn in the upstream industry, data science continues to provide solutions for complex unconventional well problems.

This paper outlines an approach to history matching that uses artificial intelligence with an artificial neural network and data-driven analytics. The approach has been used to mitigate history-matching challenges in a mature, highly geologically complex field offshore Malaysia.

The world's largest oil company has taken its lumps from 2020 and is ready to look forward to higher oil demand and the coming of a hydrogen market.

As we see in these papers, new tools and techniques are being developed to match the ability of engineers to meet the challenges posed by assets such as shale reservoirs and maturing fields.

The water-shutoff technique is used in some wells of the U reservoir in the Iro field of the Oriente Basin in Ecuador to restore production after an early water breakthrough. This paper compares the production historical data, workovers, and sand-body correlation of wells to understand reservoir behavior, shale-baffle-sealing continuity, the existence of different san…

The duo also plan to develop and mature new technologies across the carbon-capture value chain.

The authors use machine-learning methods combined with geomechanical, wellbore-trajectory, and completion data sets to develop models that predict which stages will experience difficulties during completion.

Scientists at the Sandia National Laboratories are using machine learning to find methane hydrates on the seafloor, using an approach similar to weather forecasting.

A pilot project validates the use of an advanced polymerflooding technology on the Alaska North Slope.