The rapid growth of AI and machine learning is creating new possibilities for seismic processing and interpretation.

Upstream teams are under pressure to move faster, reduce costs and make better decisions with increasingly complex data. See how a new approach—combining AI with subsurface expertise is delivering measurable business impact.

Aspen Fidelis helps decision-makers evaluate capital investments, maintenance strategies and operational improvements by forecasting performance, cost and risk across complex industrial systems.

Why more sensors and more alerts aren't the answer — and what mining operators should focus on instead.

AspenTech CTO Claudio Fayad joins Hydrocarbon Processing's The Main Column podcast to discuss where Industrial AI is headed for refining and petrochemicals.

Electric utilities are under increasing pressure from regulators, customers and stakeholders to integrate renewable energy resources while maintaining reliability, power quality and operational flexibility.

Developing projects in emerging industries often requires making critical decisions with limited information. Engineering teams must evaluate multiple design alternatives early in the project lifecycle to identify the optimal configuration that maximizes return on investment while minimizing risk.

AspenTech Inmation™ OT Data Fabric unifies OT data into a stateful, persistent enterprise namespace and continuously contextualizes it into trusted, AI-ready intelligence. It connects plants, assets and applications across edge, cloud, and on-premises to establish a consistent, real-time, query-ready operational picture that scales from a single site to the global enterprise.

Explore real-world results from YPFB Andina and AspenTech, demonstrating how an integrated, asset-wide approach can uncover hidden production opportunities and improve economic performance—without relying solely on new capital investment.

Create feasible, up-to-date production schedules that bridge the gap between planning and operations. Enable faster decisions and more profitable operations by combining traditional scheduling with optional crude and blend optimization.