DSDE: In Practice

GHGSat announced a new service for visualizing greenhouse-gas emissions. The interactive online resource will be freely available and will be formally launched during COP26 in November.

This paper updates a previous case study and presents the results of actual implementation of an optimized steam-injection plan based on the model framework.

This paper describes the development and field trials of a cloud-connected, wireless intelligent completion system that enables long-term monitoring and interval control to enhance production management by connecting the user wirelessly from the desktop to downhole inflow-control valves.

This paper details how artificial intelligence was used to capture analog field-gauge data with a dramatic reduction of cost and an increase in reliability.

Many forms of remote sensing imagery can be used, along with data sets and the resultant products, to improve the efficiency and safety of upstream oil and gas operations on the North Slope of Alaska.

This paper investigates the most important independent variables, including petrophysics and completion parameters, to estimate ultimate recovery with a machine-learning algorithm. A novel machine-learning model based on random forest regression is introduced to predict estimated ultimate recovery.

The December issue of the peer-reviewed SPE Journal includes a spotlight section on data analytics, presenting paper SPE 195698, “Prediction of Shale-Gas Production at Duvernay Formation Using Deep-Learning Algorithm.”

Rovco’s stereo camera technology system sends images and 3D models of assets from the seabed to computer browsers in any location, offering users instantaneous access to information during inspection or construction.

Using deep-learning and computer-vision techniques, the software recognizes all instances of specific instruments, valves, lines, and other features in a P&I diagram in seconds.

The company is relying on DevOps and agile to hit a bold growth goal by 2025: doubling profits without changing prices.