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Digital Transformation: Quest for Operational Efficiency

In recent times, we have been inundated with articles concerning the oil and gas industry’s race toward digitalization and automation. The pillars of such a transformation are the rapidly evolving Industrial Internet of Things (IIoT), secure cloud computing, data analytics, artificial intelligence (AI), and machine learning.

In addition, advances in sensor technology have enabled important breakthroughs in near-continuous real-time measurements, potentially transfiguring our ability to derive pertinent information from real-time measurements of processes that change over time. Sensors that are able to continuously report current downhole conditions in producing wells and surface facilities have become powerful tools for managing oilfields.

The skillful combination of these rapidly emerging digital and permanent sensor technologies is moving the industry toward advances in automation to optimize asset performance across the full life cycle of a reservoir with minimum human intervention.

Seeing the Unseen

We strive to see what is beneath the surface. Our ability to construct a digital twin image of the subsurface is solely dependent upon the data we measure. Oilfield data are classified into two categories: data at rest (archived) and data in motion (live streaming data). The huge amounts of data gathered over time pose a formidable challenge to automation. Secrets to E&P problems may lie hidden within the massive amount of accumulated data.

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Digital Transformation: Quest for Operational Efficiency

Michael Thambynayagam, CEO, MaxEUR

01 July 2019

Volume: 71 | Issue: 7

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