petroleum

How Data Visualization & Analytics is Transforming the Petroleum Industry

Introduction

In the modern world, one of the primary assets of successful, thriving societies is a low-cost energy source. Finding and producing petroleum hydrocarbons is technically challenging and economically risky. The process generates a large amount of data, and the industry needs new technologies and approaches to integrate and interpret this data to drive faster and more accurate decisions. Doing so will lead to safely finding new resources, increasing recovery rates and reducing environmental impacts.

Petroleum Industry & Data Visualization – How they are related?

The science of Data Visualization & Analytics has historically been regarded by the oil and gas industry as a term used by ‘softer’ industries to track people’s behaviors, buying tendencies, sentiments, etc. However, the concept of Data Visualization & Analytics – defined as analysis of increasing volume, variety and velocity of data – is quite familiar to the petroleum industry.

The processes and decisions related to oil and natural gas exploration, development and production generate large amounts of data. The data volume grows daily. With new data acquisition, processing and storage solutions – and the development of new devices to track a wider array of reservoir, machinery and personnel performance – today’s total data is predicted to double in the next two years.

Many types of captured data are used to create models and images of the Earth’s structure and layers 5,000-35,000 feet below the surface and to describe activities around the wells themselves, such as machinery performance, oil flow rates and pressures. Millions of wells are currently producing oil and/or gas across the world everyday, and many more gauges are monitoring performance, therefore this dataset is growing daily.

Furthermore

The petroleum industry recognizes that great power and imminent breakthroughs can be found in this data by using it in smarter, faster ways. However, resistance regarding workflows and analysis approaches remains in place, as it has for the last 30 years. How does the industry bridge the vocabulary and cultural gap between data scientists and technical petroleum professionals? Ideas, applications and solutions generated outside the petroleum industry rarely find their way inside. Other industries seem to have bridged this gap, but in talking to experts in the broader technology industry, the oil industry is seen as a ‘no man’s land’ for new-age entrepreneurs, while major technology providers spend billions trying to enter it.

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