Article

Improved Seismic Images through Full-Azimuth Depth Migration

A seismic survey was conducted in a production oil field in Serbia. It was assumed that significant reserves still exist in the field, as well as additional undiscovered reservoirs. An advanced seismic imaging technology was required to further characterize the existing reservoirs and identify and characterize new ones.

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.

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.

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.

Case Study

Efficient Data Integration, Visualization and Mapping in a Mature Basin Lead to Interpretation of New Prospects

In a mature onshore North American basin with a wealth of information, an operator needed to streamline data integration and interpretation in order to enable efficient prospecting. Read how Aspen SKUA™ software was used to develop multiple custom-made macros to automate repetitive and time-consuming tasks, and to create a new mapping workflow that enabled the customer to efficiently create prospecting maps to assist in the strategic acquisition of oil and gas leases.

On-Demand Webinar

Webinar with Chemical Processing: How ORYX Increases Yield, Reduces CO2 Emissions by 2% with Advanced Process Analytics

As a leading synthetic fuel plant based in Qatar, ORYX GTL’s mission is to “add value to Qatar’s natural resources by applying innovative technology.” Reducing CO2 emissions and flaring at the world’s first-ever, commercial-scale Gas-to-Liquid (GTL) plant is key to supporting this mission. More specifically, the company is using advanced process analytics to achieve its ambitious operational goals.

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