data analytics

The Taiwanese company is upgrading its ships in an effort to improve its ability to work with companies pursuing offshore renewable energy.

This paper presents a case study on injectivity tests to prove the concept of carbon capture, use, and sequestration capability, describing the design of surface and downhole testing systems, lessons learned, and recommendations.

The authors of this paper describe a project aimed at automating the task of cuttings descriptions with machine-learning and artificial-intelligence techniques, in terms of both lithology identification and quantitative estimation of lithology abundances.

The combined firm aims to create a stronger and more diversified geophysical company and energy data provider.

This paper presents the concept of a supervisory and advisory system dedicated to support the detection of abnormal events and to provide guidelines for fluid treatment.

Sustainability data management is a relatively new discipline that requires a unique set of tools, processes, and procedures to meet corporate demands.

Machine learning has been shown to have a promising role in oil and gas explorations in recent years. Among the applications, determining a proper location for injection and production wells along with their optimal operating conditions is a complex problem.

The partnership plans to develop an overlying software suite, Data Mesh, to consolidate data from various sources and increase data-access efficiency.

This article explains what deep learning is and how it works and presents an example use case from the energy industry.

This paper summarizes techniques for production allocation using geochemical methods and describes a best practice for a specialized approach.