What is unconventional?

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Subsurface science in the oil industry has gradually shifted in emphasis over the last five, maybe ten, years. In 2000, much of the work being done in our field was focused on conventional oil and gas plays. Today, it seems like most of what we do has something to do with unconventional resources. And this is set to continue. According to the American Petroleum Institute, unconventional gas production accounts for almost 50% of today's US Lower 48 production total of about 65 billion cubic feet per day, and is expected to reach 64% by 2020. In Canada, where unconventional gas is also very important, unconventional oil is at least as significant to geoscientists, especially bitumen. According to the Alberta govermnent, production from the Athabasca oil sands in 2011 will be about 2 million barrels per day.

But what does 'unconventional' mean? The short answer is "not conventional", which is more helpful than it sounds, and the long answer is "it depends who you ask". This is because where you draw the line between conventional and unconventional depends on what you care most about. To illustrate the point, here are some points of view...

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Innovations of the decade to come

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On Monday I posted about what I think were the major advances in exploration and reservoir geoscience in the last decade. I wanted to follow up with a look at what might happen next.

As oil and gas become harder to find and develop safely, responsibly, and economically, our tools and data will of course only continue to improve. In particular, acceptable oil sands and shale gas recovery efficiency demand new ideas and new methods. I hope the next decade will see us making progress in some of these areas, some of them long-lived problems. Here's one, more after the break:

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Innovations of the decade

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Exploration geophysics and subsurface geoscience have come a long way since 2001. I thought I could just sneak under the wire before the end of January with a look back at the ideas and technologies that have changed how we find oil and gas today. The list isn't definitive, or even objective: I have my natural bias towards the realm of integrated subsurface interpretation. Anyone with another perspective would, I’m certain, pick different highlights of the previous decade. But these are mine.

It’s fun to think back to the year 2000. It’s the year I emigrated to Canada from Norway, so I remember it clearly. I was at university for most of the 1990’s, but my recollection is that exploration geoscience was all about the emergence of computer-based interpretation, the commoditization of 3D seismic data, huge integrated databases, and the acceptance of amplitude-versus-offset methods (or AVO) as a valid approach.

Here’s what I think were the greatest advances of the noughties, the decade 2001 to 2010...

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Rock physics and steam

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Over the last few weeks, I have been revisiting and reminiscing over some past work, and found this poster I made for the 2007 SEG Development & Production Forum on the geophysics of heavy oil. A few months ago, the organizers of the workshop made a book out of many great articles that followed. Posters, however, often get printed only once, but that doesn't mean they need only be viewed once.

The poster illustrates the majority of my MSc thesis on the rock physics of steam injection in Canadian oil sands. You might be interested in this if you are interested in small scale seismic monitoring experiments, volume visualization, and novel seismic attributes for SAGD projects. For all you geocomputing enthusiasts, you'll recognize that all the figures were made with MathWorks MATLAB (something I hope to blog about later). It was a fun project, because it merged disparate data types, rock physics, finite-difference modeling, time-lapse seismic, and production engineering. There are a ton of subsurface problems that still need to be solved in oil sands, many opportunities to work across disciplines, and challenge the limits of our geoscience creativity. 

Here's the full reference: Bianco, E & D Schmitt (2007). High resolution modeling and monitoring of the SAGD process at the Athabasca tar sands: Underground Test Facility (UTF), 2007 SEG D&P Forum, Edmonton, Canada. If you prefer, you can grab these slides which I gave as an oral presentation on the same material, or flip to chapter 6 in the book.

The integration gap

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Agile teams have lots of ways to be integrated. They need to be socially integrated: they need to talk to each other, know what team-mates are working on, and have lots of connections to other agile teams and individuals. They need to be actively integrated: their workflows must complement one another's. If the geologist is working on new bulk density curves, the geophysicist uses those curves for the synthetic seismograms; if the geophysicist tweaks the seismic inversion result, the geomodeller uses that volume for the porosity distribution.

But the agile team also needs to be empirically† integrated: the various datasets need to overlap somehow so they can be mutually calibrated and correlated. But if we think about the resolution of subsurface data, both spatially, in the (x,y) plane, and vertically, on the z axis, we reveal a problem—the integration gap.

Scales_of_measurement.png

This picks up again on scale (see previous post). Geophysical data is relatively low-resolution: we can learn all about large, thick features. But we know nothing about small things, about a metre in size, say. Conversely, well-based data can tell us lots about small things, even very small things indeed. A vertical well can tell us about thick things, but not spatially extensive things. A horizontal well can tell us a bit more about spatially large things, but not about thick things. And in between this small-scale well data and the large-scale seismic data? A gap. 

This little gap is responsible for much of the uncertainty we encounter in the subsurface. It is where the all-important well-tie lives. It leads to silos, un-integrated behaviour, and dysfunctional teams. And it's where all the fun is!

† I've never thought about it before, but there doesn't seem to be an adjectival form of the word 'data'. 

UPDATE This figure was updated later:

Scales_of_measurement_complete.png