Energy

New sources of energy and increased productivity

Big Data in Energy

The power industry is filled with data. Large volumes of information are generated in all stages of production, from exploration and production to the distribution of energy.

With a country of continental size, efficiently distributing energy becomes a major challenge.

With a well-structured Big Data environment, you can:

  • Discover new sources of energy;
  • Reduce spending on drilling and exploration;
  • Increase efficiency and productivity;
  • Preventing accidents before they happen;
  • Avoid power failure;
  • Evaluate patterns of consumption;
  • Match supply to demand;
  • Plan for better maintenance and repairs.

Practical examples


EXPLORATION

First, you have to determine where to look for new oil or gas fields. It is possible to observe potentially productive areas through data collected from the seismic tracking in their current fields of exploration.

Once you've made the breakthrough, you need to assess the likelihood that this new field will be profitable. Big Data analysis tools are now used to process the series of data variables that can affect the feasibility of drilling operations. Examples of such data include:

  • Soil quality;
  • Geological anomalies;
  • Production costs;
  • Climatic factors;
  • Transportation and logistics;
  • Among others...

This analysis can help estimate the amount of oil or gas to be extracted. It all comes down to data: historical production along with local drilling, climate and environmental data (eg ocean currents for offshore platforms). The result is a much clearer picture of what you have to work with.

In addition, in an exploration platform, there are thousands of sensors that must be monitored in real time. This is easily done in a well-structured Big Data environment.


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