Data & Analytics
Major increases in hydrocarbon production require both incremental and revolutionary technologies, industry leaders said during the SPE Hydraulic Fracturing Technology Conference.
This paper presents an automated workflow deployed for scheduling and validating steady-state production-well tests across more than 2,300 wells in the Permian Basin.
This paper presents a multifaceted approach leveraging precise rig control, physics models, and machine-learning techniques to deliver consistently high performance in a scalable manner for sliding.
-
In this study, a deep-neural-network-based workflow with enhanced efficiency and scalability is developed for solving complex history-matching problems. -
Whether it’s reviving inactive gas-condensate wells or identifying overlooked reserves in brownfields, operators are making the most of older wells and fields.
-
The company said that adding Altair technology to its Xcelerator open digital business platform will create the world’s most complete AI-powered portfolio of industrial software.
-
This paper introduces a novel optimization framework to address CO2 injection strategies under geomechanical risks using a Fourier neural operator-based deep-learning model.
-
The energy-focused LLM project by Aramco Americas, SPE, and i2k Connect has entered the testing phase and is on track for licensing to operators later this year.
-
As part of a subnational climate coalition, the state is moving forward with a satellite data project to track methane emissions.
-
The Louisiana contractor is buying Kystdesign for an undisclosed sum, expanding its underwater vehicle business.
-
The agreement aims to bring the efforts of both companies together to advance digital-enabled carbon-free floating power generation.
-
Although 92% of energy companies say they plan on digital technology investments, only 27% currently retrain and reskill existing employees to meet the upcoming demand, according to a recent survey from Ernst & Young.
-
A roundtable discussion during CERAWeek pointed to the necessity of a mindset shift for the oil and gas industry to tap into AI’s true potential.
