Article

Geologically Constrained Velocity Models Improve Field Development

Seismic processing, imaging, characterization and interpretation are preferably executed as a continuous workflow to maintain seismic data integrity and consistencies. Geophysicists must construct a workflow from hundreds of applications and algorithms, and thousands of parameters, to achieve desired project outcomes. Almost all these applications and algorithms are based on assumptions about the underlying geological model complexity and subsurface conditions.

Article

Comparing Bayesian and Neural Network Supported Lithotype Prediction from Seismic Data

The past few years have seen increased interest in the application of machine learning in the industry, specifically to seismic interpretation.

Article

Synthetic Seismic Data Generation for Automated AI-Based Procedures with an Example Application to High-Resolution Interpretation

There has been growing interest in the use of machine learning technologies for processing and interpreting seismic data. Many procedures that traditionally have been performed using deterministic methods and algorithms can be effectively replaced by neural networks and other artificial intelligence methodologies, improving simplicity, efficiency and automation.

Blog

The Year Ahead in DEI

The AspenTech DEI Team promotes an inclusive work environment that enables the success of all employees. Learn about the year ahead for DEI at AspenTech.

Case Study

Researchers Develop More Efficient Oleochemical Fractionation with AspenTech® Performance Engineering

This case study details the work done at the Universiti Malaysia Pahang to research oleochemical fractionation to how to make the process more sustainable, reducing process carbon footprint. The case study explores the AspenTech solutions implemented as well as the value created.

Video

Digital Agility Realized with APC

In today’s ever-evolving global economy, energy and chemical companies need to operate with newfound agility to meet market demand and maximize margins. Aspen DMC3 Adaptive Control now embeds powerful AI machine learning algorithms to build seed models by simply mining historical data. In addition, operators and engineers are now able to find answers 24x7 to common questions and get actionable guidance from Aspen Virtual Advisor's augmented intelligence. View this video and learn how you can coordinate multiple APCs in closed-loop and optimize broad envelopes in real-time to align planning, scheduling and operation, significantly reducing margin leakage and energy costs.

Blog

BASF Streamlines Operations by Connecting Disparate Data Sources with AspenTech Inmation

This solution provides real-time, bi-directional connections, data visualization and increased efficiency for BASF's processes and customer value.

Brochure

Aspen Connect™

Aspen Connect moves industrial data in real time.

Case Study

How ORYX GTL Improves Process and Production with Aspen InfoPlus.21®

Read this case study to learn how ORYX GTL deployed Aspen InfoPlus.21 (IP.21) and AspenONE Process Explorer™ (A1PE)—as the underpinning of their digitalization journey.

Blog

Software Solutions to Increase the Resiliency of the Pharma Supply Chain Network

Enhance real-time collaboration between internal and external stakeholders.

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