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Aspen Mtell® combines the power of data and technology to enable reliability and maintenance engineers to monitor the performance of assets, providing real-time visibility into asset health and actionable insights for faster decision-making. Discover why companies like LG Chem, Evolution Mining, OCP Ecuador and others have opted for AspenTech´s prescriptive maintenance solution to improve their operational efficiency and achieve carbon mitigation and sustainability goals.

Aspen SeisEarth Applies Neural Network Inversion Features to Impact Upstream Energy Industry

AspenTech has been recognized in the global index of companies—spanning a broad range of industries—which are primed for long-term growth.

AspenTech's Ron Beck uncovers key areas within supply chain to understand technology’s role in energy transition.

Discover how Aspen RMS 3D modeling software, an industry-leading geoscience and reservoir engineering collaboration platform, enables faster, more robust and reliable production models, improved decision making, more justifiable investments and enhanced field performance, leading to higher recovery rates in even the most complex reservoirs.

For more than 20 years, Aspen SKUA has led the industry in providing advanced capabilities for geological and reservoir modeling. With a simple-to-use, workflow-based interface, users can obtain results quickly. And when the modeling gets tough, Aspen SKUA handles complexities that other solutions cannot.

One of the key challenges in accelerating decision-making and reducing the development cycle of any operational E&P prospect is to seamlessly share the same updated data with all parties involved in the project. An Aspen Geolog-OSDU Connector was built by the AspenTech SSE team in close collaboration with TotalEnergies.

Aspen Geolog has long been considered the industry standard for advanced petrophysical analysis and formation evaluation.

For chemical and petrochemical producers, reducing emissions and minimizing disruptions to process requires analyzing and monitoring vast amounts of disparate process data. Learn how Petrocuyo, Braskem Idesa and other leading companies are gaining insight into variability issues and improving overall process efficiency.

Leading asset-intensive companies are using prescriptive maintenance—powered by AI and machine learning—to unlock the value and productivity lying uncaptured in assets. Using a scalable, easy to implement prescriptive maintenance solution, companies can improve the accuracy of failure detection, increase the advance notification period of asset downtime events and reduce maintenance spend.