feature a data-driven energy future

The energy sector is undergoing a significant transformation, driven by the integration of data collection and machine learning. As we innovate toward tomorrow, technology helps us deliver the energy the world needs today.

At Chevron Canada, we’re using data and machine learning to optimize current operations while building our capacity in new energies.

Scott McKean of Chevron Canada discussing subsurface data

collecting data

The journey begins far beneath our feet.

Monitoring the subsurface is critical for developing unconventional reservoirs like the Duvernay and producing the energy that Canada needs. Technology is accelerating our ability to safely collect data from deep underground where our oil and natural gas resources are located. We can now use sophisticated sensors, including acoustic and fiber-optic sensors, across our wells.

“We can measure how we are breaking the rock three kilometers under the ground, using things like microseismic and fiber-optic measurement,” explains Scott McKean, a subsurface data scientist at Chevron Canada. "We can actually listen to what the ground is doing."

Imagine a sensor recording data every 30 centimeters over a three-kilometer well—a network of eyes and ears delving deep into the Earth's crust. This network isn't just extensive; it's dense, detailed and designed to capture a comprehensive picture of what's happening underground.

When we integrate data from numerous sources, including simulation modeling, advanced logging, mechanical earth models, and microseismic and fiber-optic measurement, it gives us the power to better predict and understand our well performance.

 

the power of data

Collecting data is just the first step. The true magic lies in what we do with this data.

By employing advanced machine learning algorithms, we transform this raw information into actionable insights. These insights enable us to optimize operations, enhance safety measures, and gain a deeper understanding of the reservoirs we tap into.

"Machine learning is just science and statistics, really,” McKean notes. “We use physics to interpret data and judge how our wells are performing.”

This approach allows for informed decisions, significantly improving the efficiency and sustainability of operations.

 

beyond immediate applications

This expertise in subsurface analysis extends beyond oil and gas extraction.

Chevron’s global expertise in subsurface analysis and modeling positions us uniquely to build lower carbon energy systems of the future, like carbon capture.

In carbon capture, understanding the subsurface is vital for safely and effectively storing captured carbon dioxide. Chevron’s ability to analyze and model subsurface structures enables us to identify the suitable sites and monitor them effectively. This expertise also transfers into the assessment of geothermal energy projects.

As we continue to seek out emerging technologies at the cutting edge of technology, our skills and knowledge in subsurface analysis can help us evaluate and scale new solutions.

 

pioneering the subsurface

Integrating extensive data collection and machine learning in subsurface surveillance is a stride towards a more sustainable and secure energy future.

As McKean puts it, "We've gotten so good at subsurface surveillance and geophysics that we can detect the equivalent energy of breaking a stick three kilometers underground, then interpret what that means for our reservoirs."

By harnessing the power of data and science, we are optimizing current operations and paving the way for innovative energy solutions. And that matters as we strive to advance a reliable, affordable energy system and a lower carbon future.