6 Ways Big Data Hadoop Is Helping America Become Energy Independent

In the last several years, oil drilling efforts in the US have greatly increased. The International Energy Agency has predicted that by 2016, the US will surpass Saudi Arabia and Russia in oil production.

In the last several years, oil drilling efforts in the US have greatly increased. The International Energy Agency has predicted that by 2016, the US will surpass Saudi Arabia and Russia in oil production. This is good news for the US as far as self-sustainability, but because the oil production throughout the rest of the world has ceased to expand, it also means that the US must become more efficient to help meet international demands for oil.

Hadoop is a significant aid in streamlining the oil and gas production industry, from testing and verifying potential drilling sites and oil extraction to ensuring equipment safety and minimizing environmental damage. Below are some specific Hadoop use cases in the oil and gas industry.

1. Oil Exploration & Discovery

Seismic monitors play a big role in searching for, identifying, and evaluating potential drilling sites during oil and gas explorations. The data they produce is analyzed to predict oil availability and success of operations, which has a direct link to revenue and costs. Other factors that go into choosing a drilling site are weather, soil, and equipment capability- all of this data can be stored and processed in Hadoop. With the MapR Distribution including Hadoop, oil explorations can determine optimal location and method for production, profitability, and safety.

2. Oil and Gas Production

Like any well, oil wells change as they are drained and as the oil reserve changes. All of the seismic, drilling, and production data are collected and analyzed in an enterprise data hub (EDH) to forecast the success of wells. Patterns can be established and changes can be made to oil lifting methods, if necessary, and production is maintained at an optimum level.

3. Equipment Maintenance

Drilling equipment technology has come a long way with the development of sensors (such as drill heads and down hole sensors) that contribute data to Hadoop. The data is used to detect any equipment errors, mechanical failures, or potential dangers, as well as geological so that oil companies can quickly resolve the issues, if any, and understand the geological conditions as they may change.

4. Reservoir Engineering

Mechanical earth models help oil companies understand the geological conditions of the earth. When combined with the processing power of The MapR Distribution including Hadoop, companies can analyze the data and determine the amount of oil in the reservoir to forecast drilling methods and success. This not only helps optimize the oil extraction, but it leads to more sustainable oil pulling techniques.

5. Safety and Environment

The dangers of injury, fire, rig explosion, collapse, and other catastrophes are high on drilling sites. With Hadoop’s anomaly detection abilities, system errors, equipment failure, and potential dangers can not only be fixed, but avoided altogether. By analyzing data and understanding the patterns of the drills, rigs, and other machinery, the oil reserve, and the earth, Hadoop can predict changes and make drilling practices safer for the environment and the workers.

6. Security Against Threats

While many accidental incidents can be avoided with the help of Hadoop, so can malicious ones. With so much global tension surrounding fuel and fuel sourcing both in the US and throughout the world, it’s especially important to take precautions against both cyber and physical threats. Data theft or alteration, computer hacking and virus planting, security breaches, and other ill-intended actions can be detected, resolved, and even prevented Hadoop. Advanced anomaly detection observes changes and glitches in real time, helping oil companies maintain a safe work environment.

Conclusion 

With the technological advances in recent years, oil drilling efficiency and safety have helped the US surge in oil and gas production. Big data can contribute to the streamlining of the industry, providing accessible data, machine learning, and anomaly detection to oil companies so they can prevent disaster, produce more, and improve the process as they go.

The adoption of Hadoop in the oil and gas industry can greatly help the United States in their production of oil. Increasing oil production in the US has not only helped lower the cost of oil and gas, but has lowered our dependence on other nations for fuel. With the help of Hadoop, the US may surpass the leading producers of oil throughout the rest of the world and become a leading supplier, which is good for the local, national, and global economy.

To learn more about how Hadoop can help your business, download The Executive’s Guide to Big Data and Apache Hadoop.