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LAURA BANDURA: Hello everyone.
My name is Laura Bandura, and I'm a research geophysicist
at Chevron.
Some of you may remember that I was on stage at Google Next
last July.
Back then, I talked about how to make sense out of way
too much data.
We were using Google Cloud's AutoML Vision
API to analyze the content of thousands
of geoscience documents and to make them searchable.
My goal then was to describe how we could quickly
access and utilize the work documented by thousands
of Chevron employees in the form of field
reports, seismic recordings, core samples, lab
analyses, environmental studies, and much more.
With Google Cloud, we got it in one place, digitized it,
and through the power of machine learning
gave this data new life.
Today, I want to tell you how far we've
come with that project and how we've
added tools to do something far more valuable--
creating a new way of consuming information
by a rich and diverse team of people
and acting faster to achieve our business goals.
The energy business literally powers the modern world.
For someone like me, part of the excitement
is understanding how we use geology and geophysics
to understand the subsurface of the Earth.
In my work, we use seismic waves to probe
the subsurface geology.
Those measurements are then used to create detailed pictures
of what the Earth looked like deep into the past
and also to help us determine where oil and gas are located.
Here we show an example of a modern river system containing
channel features that have similar dimensions and patterns
to features that we tried to find
in the subsurface for exploration.
And one of these examples is this image
of a submarine canyon system that we
found within seismic data.
But the excitement doesn't stop there.
The next step is to connect our interpretations of these images
to the value chain and to ultimately impact
how we produce oil and gas.
For an integrated energy company like Chevron
that means working with multiple teams globally
that include research scientists, engineers,
and analysts.
Some of us are working in offices interpreting data,
and others are out in the field conducting operations.
Communicating with our peers across geographic and language
boundaries and across subject matter domains
is nothing new to Chevron.
In fact, we've done this very well for over a century.
Over time however, information can become siloed.
What if we could create some common digital spaces
where all teams could look at all
of the available information to support
the work that they are doing?
What if all of Chevron's experts could
have the best data available at all times, regardless
of where they are located or what
their technical specialty is?
How would we organize something like that?
And the answer is to take things back to basics.
And for us, that is the earth and to build it up
in a whole new way.
On Google Cloud, we've created a system
that digitizes text, tables, and images, all sorts of notations
and data readings.
We've made everything searchable through metadata that
was automatically generated.
With AutoML, we utilize custom geologic labels to tag images
and use knowledge graphs to summarize field reports.
With natural language processing and translation,
we created an enormous index of our data and documents
that is now searchable in any language.
This means that data from years ago
can be combined with more recent findings
or matched against technology improvements
that we've made in field development planning and safety
or even in well completions, giving new life to work
that took place many years ago.
Where physical and geographical data are concerned,
Google Earth is the key technology for visualization.
We can take the surface view of the earth
and then expand it to create a view of its
below surface features, as well as we know them
from decades of our work in exploration and production,
populating it with information like seismic data
and well logs that describe transitions
between geologic layers.
We can add publicly available information
about surrounding geologies and industry activities,
developing still richer ways of seeing our data
with new understanding.
And this is really literally decades
of human work seen in the context of millions
of years of geology.
And this is really just the beginning for us.
We have new ways of seeing and using legacy and modern data
and linking it with real-time business processes
happening within Chevron around the globe each day
from earth science to facilities engineering,
to environment and safety, and beyond.
Through our collaboration with Google,
we have developed a framework that
enables us to do more together, connecting
our technical experts to our data and to each other.
And that's really made possible by what our hosts today
are calling One Google.
Thank you.
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