data analytics

A discussion at the inaugural executive breakfast convened by the SPE Data Science and Engineering Analytics Technical Section, held alongside CERAWeek by S&P Global and powered by Black & Veatch, tackled the challenge of value creation from artificial intelligence in the energy industry.

This case study from Italian technology developer Sentris highlights the effectiveness of using sensors during pigging operations to optimize cleaning efficiency.

The companies also agreed to collaborate on new AI models to unlock further insights from S&P Global Energy’s upstream data.

The cloud platform provider said the initiative is designed to help energy companies manage and analyze large-scale operational data.

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.

This paper proposes a novel approach toward drilling maximum-reservoir-contact wells by integrating automated drilling and geosteering software to control the downhole bottomhole assembly, thereby minimizing the need for human intervention.

This paper explores the evolving role of the digital petroleum engineer, examines the core technologies they use, assesses the challenges they face, and projects future industry trends.

This paper details a data-driven methodology applied in Indonesia to enhance flare-emission visibility and enable targeted reduction strategies by integrating real-time process data with engineering models.

This article is the first in a Q&A series from the SPE Methane Emissions Management Technical Section (MEMTS) on methane intelligence and how oil and gas teams translate emissions data into credible decisions and measurable reductions.

This paper presents an approach to management and interpretation of pipeline-integrity data, ensuring integrity, safety, and reliability of the operator’s critical pipelines.