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Article by Control Engineering: How to Connect Data with Data Fabric Software

Industrial organizations are under increasing pressure to connect data from legacy systems, modern applications and distributed assets to support optimization, resilience and AI-driven operations.

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From Data Silos to Unified Insight: The New Reliability Ecosystem for Modern Manufacturing

As process manufacturers navigate tighter margins, workforce challenges and increasingly complex assets, integrated reliability strategies are becoming essential for maintaining performance and operational resilience.

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Article by Hydrocarbon Processing: Harness the Power of Asset Performance Management to Transform Reliability

Unplanned shutdowns, rising OPEX and safety risks continue to challenge refiners and petrochemical producers. Asset Performance Management (APM) solutions help companies predict and prevent equipment failures, reduce costs and improve reliability.

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Mind the Data Gap with Industrial AI

More than half of all companies say they lack the skills they need to get the most out of their AI applications. Industrial AI offers a solution for this “expertise gap” by automating data cleaning, monitoring and analytics to enable the efficient scaling of custom-fit solutions.

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Article by Automation World: How Data Can Future-Proof Manufacturing Modernization

In this article from Automation World, discover how manufacturers can improve their operations now and in the future by building a strong industrial data foundation.

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Broadband Processing of Conventional 3D Seismic Survey for Better Reservoir Characterization of Gas Hydrate Deposits in KG Basin, India

In this article, legacy 3D seismic data from the KG deep water basin underwent broadband reprocessing using state-of-the-art-software.

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Accelerating Results in Carbon Storage Studies Using an Integrated and Automated Approach

Carbon capture, utilization and storage projects are growing at record speed, resulting in an increasing need for subsurface technologies that can unlock fast time-to-results throughout all the steps of the project.

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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.

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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.

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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.

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