Technical Topics

This article focuses on the introduction of one of the flow-network-based models called GPSNet that has growing popularity in the literature and shows promising results during our proof-of-concept applications.

In Part 2 of this three-part series, we dive into a practical example using the production data of Equinor’s Volve field data set.

In Part 1 of this three-part series, we use long short-term memory (LSTM), a machine learning technique, to predict oil, gas, and water production using real field data.

This article takes a deep dive into the challenges of leak detection and repair strategies, as well as delving into some of the solutions that can help companies increase efficiencies, minimize waste, and ensure environmentally friendly operations.

Explore the impact managing natural damage phenomena, avoiding induced damage, and enhancing efficiency has on getting the most out of oil and gas assets.

Process design is adaptable and can be applied in many situations involving the flow of measurable components. Applying process design and documentation to the drilling and construction of wells facilitates understanding across various disciplines.

Explore the challenges associated with fiber-optics data analysis and how recent advances in technology can be leveraged to maximize the value of the data.

These seven open-source simulators are available for free use and are among the best available in the industry.

Join Serkan Dursun, Saudi Aramco, and Salem Algharbi, SDAIA, as they explore the capabilities and limitations of large language models GPT-3 and GPT-4 and ChatGPT and discuss their potential applications in the oil and gas industry.

Join us for the final installment in our four-part series focused on addressing the implementation of AI in the petroleum industry using a real case study.