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Lost oil and Gas Wells - AI helps researchers dig through old maps

Lost oil and Gas Wells – AI helps researchers dig through old maps

Scattered across the United States are remnants from almost 170 years of commercial drilling. There are hundreds of thousands of lost oil and gas wells. These wells (UOWs) are not listed in formal records, and they have no known (or financially solvent) operators. They are often out of sight and out of mind – a hazardous combination.

If the wells aren’t properly plugged, they can potentially leak oil and chemicals into nearby water sources. Moreover, it could send toxic substances like benzene and hydrogen sulfide into the air. They can also contribute to climate change by emitting the greenhouse gas methane, which is about 28 times as potent as carbon dioxide at trapping heat in our atmosphere on a hundred-year timescale (with even higher global warming potential over shorter periods).

To find UOWs and measure methane emissions in the field, researchers are using modern tools, including drones, laser imaging, and suites of sensors. But the contiguous United States covers more than 3 million square miles. To better predict where the undocumented wells might be, researchers first pair the new with the old: modern artificial intelligence (AI) and historical topographic maps.

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Source: BERKELEY LAB

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U.S Natural Gas Power Is Booming Thanks to AI

U.S Natural Gas Power Is Booming Thanks to AI

U.S. power-generating companies are announcing plans for the highest volume of new natural gas-fired capacity. This is after years as the AI boom is driving electricity demand.

During the first half of 2024, electricity-generating firms unveiled plans for the new gas-powered capacity. According to data from the Sierra Club cited by Bloomberg, this is equal to all capacity announced in 2020.

The increase in gas-fired generation jeopardizes the current U.S. emissions and ‘clean grid’ goals.

Natural gas-fired electricity generation in the United States has jumped year-to-date compared to last year. This is as total power demand rose with warmer temperatures and demand from data centers.

Natural gas could be a big winner in the AI-driven power demand surge in the U.S. Many tech companies prefer to power their AI development centers with solar and wind. The need to get these data centers built and powered fast would boost demand for natural gas.

After more than a decade of flatlining power consumption in America, the AI boom, chip, and other tech manufacturing are leading to higher U.S. electricity demand.

For years, natural gas has accounted for the largest share of U.S. power generation, at around 40% of all electricity-generating sources.

This year, natural gas is expected to provide around 42% of America’s electricity, similar to last year, as total consumption is set to grow by 3% in 2024 and another 2% in 2025, per data from the U.S. Energy Information Administration (EIA).

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Source: Oil Price

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How AI will transform planning

How AI will transform planning, scheduling, and risk management in the oil and gas industry

The oil and gas industry has long been a cornerstone of global energy production. The future holds even greater possibilities as AI begins to redefine how this sector operates. With the complexities of planning, schedule development, and risk management becoming more pronounced. AI is poised to revolutionize these areas, enabling the industry to adapt to an increasingly unpredictable environment. So, how AI will transform planning?

In an industry marked by volatility, high capital expenditures, and intricate project lifecycles, traditional methods of planning and risk management are increasingly becoming insufficient. These approaches, often based on historical data, human mistakes, and obsolete models, can lead to inefficiencies, delays, and unanticipated risks that significantly impact both financial and operational outcomes. However, the integration of AI will transform these challenges into opportunities for greater efficiency.

AI’s ability to analyze vast datasets, identify patterns, and generate predictive insights will become an indispensable asset in planning and scheduling. Companies will be able to enhance accuracy, reduce uncertainty, and make more informed decisions by incorporating AI into these processes. AI-driven risk management tools will proactively identify potential safety issues, allowing for preemptive action and reducing the likelihood of project disruptions, ultimately leading to safer and more efficient operations.

Project management, particularly the development of detailed and accurate schedules, will also see significant advancements. AI-powered tools, leveraging machine learning algorithms and vast historical project data, will predict schedule deviations with unprecedented accuracy. This predictive capability will enable project managers to anticipate bottlenecks and adjust schedules proactively, ensuring smoother execution and reducing the reactive firefighting that often plagues large-scale projects.

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Source: Tech Talks

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