Oil at the Nanoscale Spells Huge Production Potential

Big Oil’s next big gusher will happen at a tiny, tiny scale, according to scientists at IBM.

Research at IBM’s Nano Lab in Rio de Janeiro, led by Mathias Steiner, manager of industrial technology and science for IBM Research Brazil, yields evidence that everything the industry knows about extracting oil is quite different at the nanoscale.

Here’s a quick look at the blueprint.

Imagine an oil droplet that — instead of being spherical, as one might ordinarily think — is flat.

It’s what happens when the drop is small — really small.

Think “small” to the scale of one billionth of a billionth of a liter, or an “attoliter.”

At the nanoscale, where items typically measure 0.1 to 100 nanometers long, properties of liquid oil molecules behave in different, unexpected ways than macroscopic molecules when in contact with a solid material. A drop of oil actually assumes a whole new shape in this instance.

As droplet volumes ultimately shrink to the attoliter scale, surface interactions become consequential as the droplets take on distorted shapes, ultimately flattening to form layer-like molecular assemblages at the solid surface, according to the IBM scientists. The ensuing increased surface coverage entails far more wetting than had been accounted for in ordinary macroscopic measurements.

Image Caption

Droplet adsorption energy: underestimated at the nanoscale. (a) Comparison of the actual surface with an idealized spherical cap fit to the same data. (b) Difference between adsorption energy for the actual surface and that of the spherical cap approximation. The negative differences indicate that the fitted spherical cap underestimates adsorption energy, just as it underestimates contact area. For volumes larger than 106 nm3 a spherical cap fit provides a robust estimate of the adsorption energy α. (Figure b acronyms: AFM-Atomic Force Microscope Measurement, AAMD-All Atom Molecular Dynamics Simulation, CGMD-Course Grain Molecular Dynamics Simulation.” Image reprinted from Scientific Reports’ “Adsorption energy as a metric for wettability at the nanoscale.”

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Big Oil’s next big gusher will happen at a tiny, tiny scale, according to scientists at IBM.

Research at IBM’s Nano Lab in Rio de Janeiro, led by Mathias Steiner, manager of industrial technology and science for IBM Research Brazil, yields evidence that everything the industry knows about extracting oil is quite different at the nanoscale.

Here’s a quick look at the blueprint.

Imagine an oil droplet that — instead of being spherical, as one might ordinarily think — is flat.

It’s what happens when the drop is small — really small.

Think “small” to the scale of one billionth of a billionth of a liter, or an “attoliter.”

At the nanoscale, where items typically measure 0.1 to 100 nanometers long, properties of liquid oil molecules behave in different, unexpected ways than macroscopic molecules when in contact with a solid material. A drop of oil actually assumes a whole new shape in this instance.

As droplet volumes ultimately shrink to the attoliter scale, surface interactions become consequential as the droplets take on distorted shapes, ultimately flattening to form layer-like molecular assemblages at the solid surface, according to the IBM scientists. The ensuing increased surface coverage entails far more wetting than had been accounted for in ordinary macroscopic measurements.

Minimal Scale for Maximum Production

Quantifying wettability, or the affinity of a liquid for a solid surface, presents a challenge to anyone wanting to produce a reservoir to the max. The convoluted liquid shapes that form at the attoliter scale elevate the challenge given their inclination to stay put.

In fact, in this environment a droplet’s adsorption energy density has been introduced as a new metric for a liquid’s affinity for a surface.

This is significant given that these particular molecules require increased energy for extraction — much more energy than provided by the simulation tools and techniques ordinarily used by the oil industry.

Steiner commented that the world consumed close to 97 million barrels of oil per day in 2016, noting that many barrels are left behind in the producing wells.

“Deep inside the rock, 60 percent and more of a reservoir’s oil remains trapped in capillaries, which sometimes are only tens to hundreds of nanometers wide,” he emphasized.

Producing wells don’t yield all of a reservoir’s bounty owing to any number of reasons, including pressure problems, oil viscosity, permeability/porosity issues and much more.

Now, the IBM team’s foray into the nano-environment provides a whole new perspective on this issue.

Much of the scientists’ work in this arena is available in the public domain through “Scientific Reports,” an online open access scientific journal published by Nature, said Chris Nay, external communications lead for IBM Research. The array of written material includes discussion about the unique measurement method for revealing properties of droplets at the nanoscale.

Detecting the change in shape at the nano-level encouraged the science team to develop oil flow simulations to better predict oil extraction from the reservoir.

This had to be done differently than with an oil company, where reams of various data are at hand routinely.

“In order to build a computational representation of a reservoir at the nanoscale, we took rock characterization data from public repositories, such as ETH Zurich’s Rock Physics Network,” Steiner said. “Based on the ‘reservoir template’ made from the geometrical data, we’re now able to deploy the nanoscale wetting and flow science that hadn’t been done before.”

The scientists then revealed this new template to oil and gas companies to illustrate how their nano-flow simulation serves to address the properties of the oil trapped within the capillaries of their wells.

Admittedly, the simulation doesn’t suggest how to recover 100 percent of the trapped hydrocarbons. But extracting even one percent more can be significant. Steiner cited Brazil, for example, which pumps 2.4 million bopd. A one percent production increase would tally 24,000 more barrels per day, and 8.8 million for the year.

He commented that, ideally, with better simulation technology and functional materials, the industry could get much closer to recovering the remaining 59 percent of oil.

Something New from Something Old

Characterization of droplet shapes and activity at the nanoscale is a giant step forward in furthering knowledge of recovery issues, but considerable work remains to be done.

The current focus is on taking the results yielded thus far and using these data to more effectively calibrate flow simulations of oil in nano-capillaries and their networks, according to Steiner.

The IBM team already has devised a dedicated fluid-flow-on-chip platform to enable investigators to provisionally validate flow physics for building increased accuracy simulations that connect flow at the nanoscale with that at greater scales.

“The application of electronic and optical sensing in the platform allows for differentiating between liquids electronically, for determining a liquid’s molecular fingerprint, and for monitoring surface wetting dynamics in real time,” Steiner commented.

By conducting these flow simulations in computational 3-D representations of true reservoir rock, the research team is currently developing an enhanced oil recovery (EOR) adviser technology that leverages a nano-EOR simulator and integrates various data sources.

EOR became an industry priority years ago, encouraged in large part by the 1973 Arab oil embargo. To the chagrin of many producers, the Big Downturn that got underway in the early 1980s dampened enthusiasm for the pricier methods — carbon dioxide injection, chemicals and more — used to increase oil recovery.

Technology often is key to turning something old into something new, often through increased efficiency, and EOR is an apt target for nanoscience research and application.

The IBM researchers noted that nanoscience-based flow simulations built on reservoir specific data input, including rock tomography and chemical compositions, are anticipated to predict more accurately the efficiency of a specific EOR agent for enhancing oil displacement in a pore network with feature sizes spanning six orders of magnitude on the physical length scale.

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