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How AI Transforms the Oil and Gas Exploration Process

Written by Charan Sai Dasagrandhi | Sep 2, 2021 8:32:01 PM

The oil and gas industry of late is picking up the pace of digitalization and has been actively adopting artificial intelligence to improve its various operations- exploration, drilling, predictive maintenance, defect detection, safety management, and so on. While there are many areas where AI is transforming the oil and gas industry, here we discuss specifically the role of AI in enhancing the efficiency of oil and gas exploration.

Understanding AI Role in Improving Oil & Gas Exploration

The U.S. Energy Information Administration states US domestic crude oil production has surpassed 11 million barrels per day. This undoubtedly asserts the need to grow exploration endeavours. However, the legacy processes of oil and gas exploration are costly and human-intensive.

The conventional procedures of exploration geophysics aren't accurate and are extremely expensive. Here is where AI capabilities come in. Moreover, the manual analysis process takes time and can be prone to human error. Carrying out drilling based on this less than perfect analysis results in lost resources, time, and money.

It is for this purpose, technology leaders like Microsoft partner with industry leaders like Shell and Baker Hughes to build AI solutions for oil and energy operations. Similarly, BP Ventures invested $5 million in AI technology to explore how to improve its upstream operations. The same behaviour is reflected in market stats too. Businesswire reports “the AI in Oil and Gas market was valued at $2 billion in 2019 and is expected to reach $3.81 billion by 2025.”

Current AI Oil and Gas Exploration Use Cases

Many pioneers in the oil and gas industry are deploying drones to collect seismic images and reservoir info to be fed into AI-powered image processing applications. These applications use this data along with the historical data and analyses to generate exploration data.

Advanced knowledge graphs automatically relate data altogether, discovering relationships and workflows. Based on thorough analysis, explorations are carried out. This AI-driven approach reduces risk and guarantees precise data. With the power of data analytics and machine learning, even the huge amounts of data in data silos can be used to extract meaningful information and drive efficiency.

AI technology empowers engineers with real-time data, provides superior data analysis in the oil and gas exploration process. Exploration teams can evaluate exploration and reservoir information, estimate complete reserve capacity, get insights into production models and predict production quantities.

AI is transforming how exploration teams operate, investigate data, distinguish conditions, and make upstream decisions. Emphasizing an AI approach for exploration, BP states that by optimizing the exploration process life cycle, they reduce 90 percent of time taken to compile and, analyze data and simulate the exploration process.

Conclusion

In contrast to conventional oil and gas discovery, AI can be an efficient solution delivering accurate data in the exploration process. AI applications can inspect the area, evaluate data, and meticulously map areas to conduct the drilling process and deliver data.