On-Demand Webinar

Rapidly Develop, Scale-up and Optimize Hydrogen Processes

Hydrogen is playing a key role in meeting the dual challenge of achieving both growth and sustainability initiatives. For over 40 years, AspenTech® has been partnering with industrial leaders to help them meet this dual challenge, by leveraging domain expertise to help organizations run more safely, efficiently and sustainably. With the need to rapidly expand the deployment of hydrogen production globally, companies must address the challenges of high energy and capex cost of innovation, scaleup and storage to expedite speed to market.

On-Demand Webinar

Make Hydrogen a Viable, Practical Energy Solution with Digitalization

As the hydrogen economy continues to gain momentum, organizations are looking for faster, more efficient ways to design and deploy hydrogen projects. Growing pressure to meet sustainability targets is only increasing the demand to make these initiatives both viable and profitable.

On-Demand Webinar

Scaling Up the Green Hydrogen Economy with Microsoft and AspenTech

As companies look to advance their sustainability projects to meet net-zero goals, hydrogen has quickly emerged as a viable clean energy solution. But what is the best approach to quickly, reliably and cost effectively deploy green hydrogen production?

Technical Paper

Improving Underlying Image by Resolving High Velocity Anomaly Using Sonic Log in Velocity Model Building

In the presence of complex geology and lateral velocity variations, unresolved velocity anomalies in the overburden degrade deeper imaging.

Article

Seismic AVO Attributes and Machine Learning Techniques Characterize a Distributed Carbonate Build-Up Deposit System

Discover how seismic volume-based unsupervised facies classification associated with advanced visualization and detection helps delineate the prospect’s potential, increase drilling success and reduce cost and risk.

Article

Model-based Ground-roll Attenuation with Updating Quality Factors

Surface waves can generate coherent noise, known as ground roll, in seismic surveys. Ground roll can significantly degrade data quality.

Article

Using a Self-growing Neural Network Approach to CCS Monitoring

This article shows how a machine-learning workflow based on a Self-Growing Neural Network (SGNN) was used by Aspen SeisEarth™ as an efficient and unbiased scanning tool for carbon capture and storage (CCS) monitoring, enabling faster identification of the confinement system.

Brochure

AspenTech Inmation™ Real World Use Cases

Learn how AspenTech Inmation works to unlock value from your industrial data.

Blog

New Research Reveals the State of Industrial Data Today

Recently, the AspenTech DataWorks team commissioned Vanson Bourne to perform an independent study of 200 North American and European decision makers to learn more about their industrial data usage

Case Study

BASF Connects Disparate Industrial Data Sources to Improve Operations

Learn how BASF, a large global chemical producer, uses AspenTech Inmation™ to unlock value from industrial data.

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