PROPERTIES IN SHALES

RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No. 62/417,512, filed November 4, 2016, which is incorporated herein by reference. BACKGROUND

Extraction of hydrocarbon fuels (e.g., oil and natural gas) is time consuming and quite costly. Accordingly, it is important to understand how oil is situated and flowing throughout an oil field in order to decide where to drill, how deep to drill, how many wells to drill, as well as how to chemically enhance hydrocarbon recovery. Vast resources may be expended in modeling such an oil field to facilitate decisions based on these considerations. The behavior of fluids and gases in nanometer-scale pores of target reservoir rocks (e.g., shale rocks) can have a strong functional dependence on the pore size and surface chemistry of the particular target reservoir rocks for fracking processes to extract natural gas, for instance.

Computer-generated models are typically used to simulate the field (and the target reservoir rocks), but such simulations do not allow engineers to sufficiently understand how oil is flowing through the target reservoir rocks at a nanoscale. For example, current Digital Rock Physics (DRP) technology includes digitalizing a rock sample into a three- dimensional computer model by scanning or imaging the rock sample, thereby generating a modeled and complex network of channels and pores representative of the rock sample. This can be achieved by using a focused ion beam scanning electron microscope (FIB- SEM), X-ray microscopy (XRM), or other similar tools. Current simulators in the market then run physics based simulations that result in calculated fluid thermodynamic and transport properties in the rock sample which are estimates of corresponding real properties. However, such computer simulations only modestly represent accurately the true subsurface environment and physical characteristics of the particular field and its target reservoir rocks. Some technical hurdles of these known methods include identifying relevant nanoscale sub-surface physics in the target reservoir rocks, such as fluid flow in the nanochannels present in low-permeability formations of the target reservoir rocks. Because these fluid flow in nanochannels is not ideally or readily represented in such DRP -based computer simulations, actual performance of hydrocarbons (and other test materials) cannot be reliably predicted or applied to an actual physical representation of the model. Thus, these computer-aided simulations cannot reflect real-world properties and characteristics of target reservoir rocks with a high-degree of certainty and reliability before expending vast resources on oil recovery efforts. As a result, improvements continue to be sought in assessing reservoir rock permeability and properties to enhance hydrocarbon recovery design and efforts.

SUMMARY

A nanofluidic device is disclosed herein for measuring fluid thermodynamic and fluid transport properties in a low-permeability rock structure. The nanofluidic device can include a substrate and a fluidic channel network formed onto the substrate. The multimodal fluidic channel network can include at least one sized channels arranged in a deconstruction model such that the fluidic channel network represents fluid flow in the low-permeability rock structure. The channels can optionally include at least two different sized channels which includes a nanofluidic channel. The nanofluidic device can include a fluid inlet in fluid communication with the fluidic channel network, and a fluid outlet in fluid communication with the fluid inlet via the fluidic channel network. Fluid is flowable into the fluid inlet, through the fluidic channel network, and out the fluid outlet, for measurement of fluid thermodynamic properties and fluid transport properties of the low- permeability rock structure represented by the fluidic channel network.

In one example, the fluidic channel network can comprise a two-dimensional (2D) structure representative of a three-dimensional (3D) low-permeability rock structure. In some examples, channel walls of the fluidic channel network are treated to achieve a predefined wettability. In some examples, the fluidic channel network approximates a multimodal pore distribution including pluralities of micropores and nanopores. A system is disclosed herein for simulating fluid thermodynamic and fluid transport properties of a low-permeability rock structure with the nanofluidic device.

A method is also disclosed herein for simulating fluid thermodynamic and fluid transport properties of a low-permeability rock structure with a rock fluidic channel reduction. The method can include: collecting data describing physical characteristics of a low-permeability rock structure; fabricating a rock fluidic channel reduction representing the physical characteristics of the low-permeability rock structure (e.g., forming a fluidic channel network onto a substrate wherein the rock fluidic channel reduction is a modeled reduction of the low-permeability rock structure); flowing fluid through the fluidic channel network; and measuring fluid thermodynamic properties and fluid transport properties of the rock fluidic channel reduction.

There has thus been outlined, rather broadly, the more important features of the invention so that the detailed description thereof that follows may be better understood, and so that the present contribution to the art may be better appreciated. Other features of the present invention will become clearer from the following detailed description of the invention, taken with the accompanying drawings and claims, or may be learned by the practice of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram illustrating a system and process for generating or forming a nanofluidic device for simulating fluid thermodynamic and fluid transport properties of a low-permeability rock structure with a rock fluidic channel reduction of the nanofluidic device in accordance with an example of the present disclosure.

FIG. 2A is a top-down view of a nanofluidic device for measuring fluid thermodynamic and fluid transport properties in a low-permeability rock structure in accordance with an example of the present disclosure. FIG. 2B is a close-up view of a portion of a fluidic channel network of the nano fluidic device of FIG. 2 A in accordance with an example of the present disclosure.

FIG. 2C is a close-up view of a portion of the fluidic channel network of FIG. 2A in accordance with an example of the present disclosure.

FIG. 3 A is a top-down view of a multimodal nanofluidic device for measuring fluid thermodynamic and fluid transport properties in a low-permeability rock structure in accordance with an example of the present disclosure.

FIG. 3B is a close-up view of a portion of a multimodal fluidic channel network of the nanofluidic device of FIG. 3 A in accordance with an example of the present disclosure.

FIG. 4A-4G illustrates a method of fabricating a nanofluidic device, such as in

FIGS. 2A or 3 A, in accordance with an example of the present disclosure.

FIG. 5 illustrates a system and method for simulating fluid thermodynamic and fluid transport properties of a low-permeability rock structure with a rock fluidic channel reduction of a nanofluidic device in accordance with an example of the present disclosure.

FIG. 6 is a flow chart showing a method for simulating fluid thermodynamic and fluid transport properties of a low-permeability rock structure with a rock fluidic channel reduction of a nanofluidic device in accordance with an example of the present disclosure.

These drawings are provided to illustrate various aspects of the invention and are not intended to be limiting of the scope in terms of dimensions, materials, configurations, arrangements or proportions unless otherwise limited by the claims.

DETAILED DESCRIPTION

While these exemplary embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, it should be understood that other embodiments may be realized and that various changes to the invention may be made without departing from the spirit and scope of the present invention. Thus, the following more detailed description of the embodiments of the present invention is not intended to limit the scope of the invention, as claimed, but is presented for purposes of illustration only and not limitation to describe the features and characteristics of the present invention, to set forth the best mode of operation of the invention, and to sufficiently enable one skilled in the art to practice the invention. Accordingly, the scope of the present invention is to be defined solely by the appended claims.

Definitions

In describing and claiming the present invention, the following terminology will be used.

The singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a channel" includes reference to one or more of such features and reference to "etching" refers to one or more such steps.

As used herein with respect to an identified property or circumstance, "substantially" refers to a degree of deviation that is sufficiently small so as to not measurably detract from the identified property or circumstance. The exact degree of deviation allowable may in some cases depend on the specific context.

As used herein, the term "about" is used to provide flexibility and imprecision associated with a given term, metric or value. The degree of flexibility for a particular variable can be readily determined by one skilled in the art. However, unless otherwise enunciated, the term "about" generally connotes flexibility of less than 5%, and most often less than 1%, and in some cases less than 0.01%.

As used herein, "adjacent" refers to the proximity of two structures or elements. Particularly, elements that are identified as being "adjacent" may be either abutting or connected. Such elements may also be near or close to each other without necessarily contacting each other. The exact degree of proximity may in some cases depend on the specific context.

As used herein, "nanofluidic channels" refer to fluid conduits which have a nanometer scale width. Nanofluidic channels can have any suitable cross-sectional profile such as, but not limited to, rectangular, square, circular, elliptical, and the like. Nanoscale width can generally range from about 1 nm to less than 500 nm, and most often from about 1 nm to about 100 nm.

As used herein, "microfluidic channels" refer to fluid conduits which have a micrometer scale width. Microfluidic channels can have any suitable cross-sectional profile such as, but not limited to, rectangular, square, circular, elliptical, and the like. Microscale width can generally range from 0.5 μιη to less than 1 mm, and most often from about 1 μιη to about 500 μιη.

As used herein, "macrofluidic channels" refer to fluid conduits which have a macroscale width. Microfluidic channels can have any suitable cross-sectional profile such as, but not limited to, rectangular, square, circular, elliptical, and the like. Macroscale width can generally range greater than about 1 mm, and most often from about 1 mm to about 5 mm.

As used herein, a plurality of items, structural elements, compositional elements, and/or materials may be presented in a common list for convenience. However, these lists should be construed as though each member of the list is individually identified as a separate and unique member. Thus, no individual member of such list should be construed as a de facto equivalent of any other member of the same list solely based on their presentation in a common group without indications to the contrary.

As used herein, the term "at least one of is intended to be synonymous with "one or more of." For example, "at least one of A, B and C" explicitly includes only A, only B, only C, or combinations of each.

Numerical data may be presented herein in a range format. It is to be understood that such range format is used merely for convenience and brevity and should be interpreted flexibly to include not only the numerical values explicitly recited as the limits of the range, but also to include all the individual numerical values or sub-ranges encompassed within that range as if each numerical value and sub-range is explicitly recited. For example, a numerical range of about 1 to about 4.5 should be interpreted to include not only the explicitly recited limits of 1 to about 4.5, but also to include individual numerals such as 2, 3, 4, and sub-ranges such as 1 to 3, 2 to 4, etc. The same principle applies to ranges reciting only one numerical value, such as "less than about 4.5," which should be interpreted to include all of the above-recited values and ranges. Further, such an interpretation should apply regardless of the breadth of the range or the characteristic being described.

Any steps recited in any method or process claims may be executed in any order and are not limited to the order presented in the claims. Means-plus-function or step-plus- function limitations will only be employed where for a specific claim limitation all of the following conditions are present in that limitation: a) "means for" or "step for" is expressly recited; and b) a corresponding function is expressly recited. The structure, material or acts that support the means-plus function are expressly recited in the description herein. Accordingly, the scope of the invention should be determined solely by the appended claims and their legal equivalents, rather than by the descriptions and examples given herein.

Nanofluidic Devices for Measuring the Thermodynamic Fluid and Transport Properties in Shales

FIG. 1 is a block diagram illustrating a system 10 for generating a nanofluidic device for measuring fluid thermodynamic and fluid transport properties of a low- permeability rock structure with a rock fluidic channel reduction pattern of the nanofluidic device in accordance with an example of the present disclosure. As further exemplified below regarding various aspects of FIGS. 2A-6, the system 10 of FIG. 1 comprises a low- permeability rock structure 12, such as a shale rock sample obtained from rock formation associated with a particular target oil and/or gas reservoir. An imager or scanner 14 (e.g., TEM, FIB-SEM, XRM) can be operated to scan the low-permeability rock structure 12, although any suitable approach can be used to obtain a 3-D digital representation of the actual rock sample by means of tomography. TEM and FIB-SEM are destructive imaging techniques while the XRM is a non-destructive imaging technique. In case of a destructive technique, the sequence of images such as FIB-SEM image stack are segmented to reconstruct a digital model of the rock which is then used to get a precise pore or fracture network model.

A computer system 16 having memory, can be coupled to the scanner 14, or can otherwise receive data associated with the scanned low-permeability rock structure 14 (e.g., in one aspect, the computer system may have a scanning module to facilitate the scanning with the scanner 14. Common laboratory tests can be performed for estimating the wettability of the rock such as, but not limited to, contact angles (e.g. sessile drop method), imbibition and forced displacement volumes (e.g. Amott method), USBM, electrical resistivity, imbibition, flotation, glass slide method, permeability curves, capillary pressure curves, capillarimetric methods, displacement capillary pressure, MR and dye adsorption, and the like.

Based on the scanned low-permeability rock structure 14, a 3D pore network model module 18, coupled to a processor 22 of the computer 16, may generate a 3D pore network model (i.e., forming a digital model of the actual pore network of the native rock). Accordingly, the 3D pore network model is generally representative of the actual pore network of the low-permeability rock structure 12. A deconstruction module 20, coupled to the processor 22, may be configured to deconstruct the 3D pore network model into a 2D rock fluidic channel reduction model 24.

A patterning device, such as a photolithography device 26, can be configured to receive data or instructions from the computer 16 associated with the 2D rock fluidic channel reduction model 24. The photolithography device 26 can include several sub- devices such as a mask pattern generator, a spinner to spin photo resist on silicon wafer, an aligner to expose silicon wafer through a mask, a dry and a wet etcher, an equipment for atomic layer deposition and chemical vapor deposition. The photolithography device 26 can be operated to generate or form a nanofluidic device 28 having a 2D rock channel fluid channel reduction based on the 2D rock fluidic channel reduction model (see e.g., FIGS. 2A-4). In one aspect, the computer 16 can be operated to control the photolithography device 26. Once the nanofluidic device 28 is generated or formed, it can be utilized with a simulation and testing system 30 (e.g., FIG. 5) for measuring fluid thermodynamic and fluid transport properties of the low-permeability rock structure with the nanofluidic device 28. Various examples of aspects and operations associated with FIG. 1 will be further detailed below.

FIG. 2 A illustrates a nanofluidic device 100 in accordance with an example of the present disclosure. The nanofluidic device 100 can be formed via the system 10 of FIG. 1, so the nanofluidic device 100 can be utilized for measuring fluid thermodynamic and fluid transport properties in a low-permeability rock structure, as further detailed below (e.g., FIGs. 5 and 6 for simulation and measurement processes). The nanofluidic device 100 provides a rapid, small scale, conclusive method to test and refine materials and processes to experimentally and effectively stimulate reservoirs before field scale testing. Such devices can also provide a reusable and a fundamentally more robust platform compared to real rock that allows you to visualize fluid flow through the porous media in real time using a microscope and a computer monitor.

The nanofluidic device 100 can comprise a substrate 102 and a fluidic channel network 104 formed onto or as part of the substrate 102. As best illustrated in FIG. 2B, the multimodal fluidic channel network 104 can include at least two different sized channels 206a and 206n arranged in a deconstruction model such that the multimodal fluidic channel network 104 represents fluid flow in the low-permeability rock structure (e.g., in a miniaturized scale).

The fluidic channel network 104 can be defined by a rock fluidic channel reduction pattern that represents the physical characteristics of the low-permeability rock structure (e.g., a rock shale sample), such as described regarding FIG. 1. Generally, the rock fluidic channel reduction pattern can be a collection of interconnected channel segments arranged in a common plane. The reduction pattern can include at least one portion of segments which are nanofluidic channels and a second portion of segments which are microfluidic channels. Thus, various dimensions of channel segments can be varied, as well as connection patterns. For example, dimensions such as width, length and cross-section shape can be varied. Similarly, patterns can range from triangulation (e.g. FIG. 2B), cross- connected ladder configurations (e.g. FIG. 3B), branched networks, and the like. Notably, the fluidic channel network can be monomodal, bimodal, or have any number of size ranges. In some cases, a monomodal channel network can provide sufficient accuracy. In some cases, a multimodal (e.g. 2, 3, 4, or more sizes) channel network can be used to approximate the rock structure. The 2D network may include any possible configuration that represents the same porosity as the original rock volume, The pore-size distribution from the digital rock model can be used to obtain a corresponding network configuration with same porosity in order to represent the actual pore network. As a general rule, the proportion of nanometer scale channels (nano channels) can cover from about 0% to about 100% by volume of the multimodal fluidic channel network, and in some cases 50% to 100%). Similarly, the microfluidic channels can often cover about 0% to about 100% by volume of the multimodal fluidic channel network, and in some cases 0% to 50%. Thus, the distribution of channel size can be monomodal (i.e. only nano meter channels or only micro meter channels), bimodal (i.e. both nano channels and micro channels) or higher- order multi modal (multiple size distributions of nano channels and/or microchannels). Furthermore, multiple 2D networks can be optionally stacked in parallel.

In FIG. 2B, at least one of the two different sized channels 106a and 106b can include a nanofluidic channel (i.e., having a diameter, or cross- sectioned channel area, sized in nanometers). In this example, a plurality of channels 106a-n can be formed, which can include a plurality of nanofluidic channels and/or microfluidic channels, and even some macrofluidic channels in some examples, all interconnected together to define the multimodal fluidic channel network 104. The nanofluidic device 100 can comprise a fluid inlet 110a (best shown in FIG. 2C) in fluid communication with the multimodal fluidic channel network 104, and a fluid outlet 110b (FIG. 2 A) in fluid communication with the fluid inlet 110a via the multimodal fluidic channel network 104. In many configurations, the fluid inlet can include a plurality of access points into the channel network. In this manner, the fluid inlet acts as a common inlet chamber adjacent to a multi-inlet channel network. Similarly, a common outlet chamber can be oriented adjacent to an opposing end of the channel network 104. The common outlet chamber can be commonly fluidly associated with a plurality of outlet access points of the channel network 104.

As further detailed below, during simulation processes a fluid (e.g., oil and/or gas) can be flowed into the fluid inlet 110a, through the multimodal fluidic channel network 104, and then out the fluid outlet 110b, so that measurements can be taken of fluid thermodynamic properties and fluid transport properties of the low-permeability rock structure represented by the multimodal fluidic channel network 104. The measurement equipment can include inlets and outlets of nanofluidic devices connected to a pump with an inline pressure transducer. The device with anodically bonded glass lid on top is held under a microscope connected to a computer monitor to visualize the fluid flow in the device. For example, water and oil transport can be measured saturating the nanofluidic device with oil and flooding water from one end.

More specifically, and in one example mentioned above regarding creation of a channel network reduction, imaging and/or scanning technology can be utilized (along with known CAD tools) to generate a 3D model of pore network distribution of the low- permeability rock structure. Based on this 3D model, pseudo 3D pore geometry can be calculated using Delaunay triangulation calculation techniques, and computer-readable instructions can be generated therefrom for forming the multimodal fluidic channel network 104 onto the substrate 102. Alternatively, an actual realistic representation of the pore structure of an actual rock can be obtained using any suitable triangulation process which can reproduce a given pore size distribution. Non-limiting examples of alternative triangulation methods can include polygon triangulation, point set triangulation, radial sweep triangulation, Greedy triangulation, Garey triangulation, finite element methods, constrained Delaunay triangulation, pseudotriangulation, and the like. In either scenario, based on the calculated pseudo 3D pore geometry, a 2D rock fluidic channel reduction model can be generated. This "calculated" 2D rock fluidic channel reduction model can then be utilized for forming the multimodal fluidic channel network 104 onto the substrate 102 via photolithography processes (e.g., FIGS. 1 and 4) to generate the nanofluidic device 100.

In some examples detailed below, surface treatments can be performed on surfaces of the nanofluidic device 100 to tailor or define the wettability, for instance, of channel walls of the multimodal fluidic channel network 104. Once formed, simulation processes can then be performed on the nanofluidic device 100, as further detailed below regarding FIG. 5. Optionally, surfaces can also be modified over time such that a single nanofluidic device 100 may be customizable by varying channel surface chemistry for different experimental runs.

In one specific example to determine pore size distribution, assume 2000 pores are derived from scanning a particular sample of a low-permeability rock structure, which has 6 percent pore porosity (a typical shale rock sample). Assume that the mean pore size is 40 μπι, and σ ² is 60 μπι. Further assume that the minimum pore size is 25 μπι, while the maximum pore size is 100 μπι, which could result in a longnormal curve distribution of the 2000 pores. In this example, assume the number of pore throats is 5980 (derived from triangulation), while the mean throat width distribution has a mean of 30 μπι, and σ ² of 60 μπι. Further assume that the minimum throat width is 10 μπι, while the maximum throat width is 50 μπι. Therefore, when generating a 2D rock fluidic channel reduction model, the positions of the channels (e.g., 106n, as representing pore size distribution) can be randomly assigned in 5 mm x 35 mm in 2D space for formation onto the substrate to form a multimodal fluidic channel network. And, throat width can be adjusted to some percent (less than 100%) of the minimum size of one of the connected pores if width is greater or equal to the minimum sized of one of the connected pores as defined by the channel network. In one example, the throat width is 70% of the size of the smallest of all the connected pores. The size of pore throats is relatively important because they determine the productivity of shale reservoirs and govern the storage and migration of oil and gas.

FIGS. 3A and 3B illustrate another example of a nanofluidic device 200 that can be used for measuring fluid thermodynamic and fluid transport properties in a low- permeability rock structure, as further detailed below (e.g., see FIGS. 5 and 6 for simulation and measurement processes).

The nanofluidic device 200 can be generated and formed via the system of FIG. 1, for instance. Here, the nanofluidic device 200 can comprise a substrate 202 and a multimodal fluidic channel network 204 formed onto or as part of the substrate 202. As best illustrated in FIG. 3B, the multimodal fluidic channel network 204 can include at least two different sized channels arranged in a deconstruction model such that the multimodal fluidic channel network 204 represents fluid flow in a low-permeability rock structure. Specifically, a first channel 206a can be a microfluidic channel (or even a macrofluidic channel), and a second channel 208a can be a nanofluidic channel.

The nanofluidic device 200 can comprise a fluid inlet 210a in fluid communication with the multimodal fluidic channel network 204, and a fluid outlet 210b in fluid communication with the fluid inlet 210a via the multimodal fluidic channel network 204. As further detailed below regarding FIGS. 5 and 6, fluid (e.g., oil and/or gas) can be flowed into the fluid inlet 210a, then through the multimodal fluidic channel network 204, and the out the fluid outlet 210b, so that measurements can be taken of fluid thermodynamic properties and fluid transport properties of the low-permeability rock structure represented by the multimodal fluidic channel network 204.

As shown in FIG. 3B, the multimodal fluidic channel network 204 can be defined as a plurality of nanofluidic channels 208a-n and a plurality of microfluidic channels 206a- n interconnected to each other, and in a more orderly manner (as opposed to being more randomly assigned, as in FIG. 1 A). That is, generalized "ladders" of microfluidic channels 206a-n and nanofluidic channels 208a-n can be generally laterally formed along the nanofluidic device 200 as extending between the fluid inlet 210a and the fluid outlet 210b. One or more of such "ladders" can be formed to define a particular multimodal fluidic channel network, and as shown in this example, such "ladders" may be interconnected to each other by the pluralities of nanofluidic channels 208a-n, whether being formed randomly or more orderly/intentional.

FIGs. 4A-4G illustrates a method of fabricating a nanofluidic device 300 (e.g., 28,

100, 200) in accordance with an example of the present disclosure. Referring to FIG. 4 A, in a first step, a substrate 302 is provided. The substrate can generally be a micro-scale silicon substrate such as a silicon wafer. However, other substrates may be used such as, but not limited to, silicon wafer coated with other materials (e.g. anionic surfactants, cationic surfactants, sodium dodecyl sulfate, ethoxylated sulfonates, R-N ⁺ (CH ₃ ) ₃ , and the like). In FIG. 4B, a photoresist layer 304 can be disposed onto the substrate 302. Such photoresist layers can be deposited using any suitable technique such as spin-coating processes, physical vapor deposition, drop-on-demand, chemical vapor deposition, or the like. Typically, the photoresist can be heated at a sufficient temperature to partially cure the polymer photoresist (e.g. 110 °C which can vary depending on the specific photoresist). In FIG. 4C, a photomask 306 can be mounted (and aligned) on top of (or above) the photoresist layer 304, using known techniques for applying a photomask onto a substrate. The particular pattern of the photomask can be associated with some portion or an entire portion of a model of a particular 2D multimodal fluidic channel network (e.g., 104, 204) as defined by a particular modeled rock fluidic channel reduction, as further exemplified above. In FIG. 4D and 4E, an illumination device (not shown) can be operated to transmit an ultraviolet light source (i.e., represented by the downward arrows) to replicate the particular patterning of the photomask 306 onto the photoresist layer 304. Exposure to the light source causes the photoresist to be soluble in a particular solvent if the photoresist is a positive photoresist, or is made to be insoluble in the case of a negative photoresist. In either case, a pattern of photoresist is removed exposing portions of the underlying substrate 302. In FIG. 4F, the replicated pattern formed on the photomask 306 can be etched on to the exposed portions of the substrate 302 by utilizing known dry or wet etching techniques. Finally, as illustrated in FIG. 4G, the remaining photoresist layer 304 can be removed (e.g., stripped), using known techniques of stripping. These steps can be repeated, along with surface deposition of multiple layers of materials, for obtaining additional surface features until the desired 2D pattern of channels is obtained. The substrate 302 can then be bonded to a support device substrate as a final fabrication operation. In some cases the device substrate can be glass, although other materials can be used such as, but not limited to, PDMS, polymer, ceramics, and the like. Thus, the process effectively generates a "rock-on-a-chip" device for testing and simulation purposes discussed herein.

Referring to FIG. 4G, the resulting nanofluidic device 300 comprises a multimodal fluidic channel network 308, having channels 310a-n, based on a modeled 2D rock fluidic channel reduction representative of a calculated pseudo 3D pore geometry of a low- permeability rock structure. In this example, and additional capping layer (not shown) can be added across the top in order to close the channel network. Alternatively, the device support substrate can act as the capping layer. As exemplified regarding FIGS. 1-3B, the channels 310a-n can have different sizes, such a being nanofluidic channels, microfluidic channels, and/or macrofluidic channels. As previously discussed, the channels can include multiple size distributions including one or more each of nano channels, microchannels, and optionally macrochannels. For example, a nanopore channel distribution including numerous nano sized channels can constitute a nano channel size distribution. Similarly, a micropore channel distribution can include numerous micro sized channels forming a micro channel size distribution.

Advantageously, because the nanofluidic devices exemplified herein have a 2D multimodal fluidic channel network, the surfaces of the multimodal fluidic channel network can be treated with a predefined surface treatment. For example, surface treatments can tailor a particular wettability, for simulation purposes to more accurately determine and analyze the wettability of a particular sample of a low-permeability rock structure from a target oil reservoir. This is not possible to do accurately and reliably with computer-generated 3D models that merely simulate possible wettability factors that may not accurately reflect real-world characteristics of a physical sample of a low-permeability rock structure, or of the entire target oil reservoir as a whole.

Wettability may be the foremost parameter affecting residual oil saturation in all stages of oil recovery. Wettability is a tendency of a fluid to spread on or adhere to a solid surface in the presence of other immiscible fluid. The fluid that spread or adheres to the surface is known as the wetting fluid. In the field, the solid surface is the rock, which may be shale rock of a target oil reservoir area. The fluids most commonly associated with such surfaces are water, oil, and gas. Normally, either water or oil is the wetting phase, while gas is a nonwetting phase. Wettability controls the rate and amount of spontaneous imbibition of water and the efficiency of oil displacement by injection water, with or without additives. Wettability of a system can range from strongly water-wet (e.g. water wetting angle less than 90°), to strongly oil-wet (e.g. water wetting angle greater than 90°), depending on the brined interactions with the rock surface. In a water-wet system, water will occupy the narrowest pores and will be present as a film on the pores wall while oil will reside as oil droplets in the middle of the pores. The reverse fluid distribution will exist in the case of an oil-wet reservoir or rock structure. A core sample of rock shale that imbibes only water spontaneously is said to be water-wet, and one that imbibes oil spontaneously is said to be oil-wet. Samples imbibing neither water nor oil are said to be neutral wet (e.g. water wetting angle of 90°).

Because liquid condensation in shale rock may inhibit gas production in gas- condensate shale rock when pressure drops lower than the dew point, gas production can be improved by altering the rock wettability from liquid-wetness to gas-wetness. Thus, a substantial increase in gas delivery and oil recovery can result when the wettability of target reservoir rocks is altered from strong liquid-wetness to the preferred gas-wetness. However, because of these wettability factors in rock structures of target oil reservoirs, determining the most effective fracturing fluid and proppant for a particular fluid reservoir can be challenging when utilizing only computer-aided simulations of rock structures that define a particular (virtual) wettability, as defined by a user. Therefore, the chemical composition of shale rock and its pore sizes are factors in assessing volumes of recoverable shale oil reserves of a target oil reservoir.

Advantageously, the example the 2D multimodal fluidic channel networks disclosed here can be treated with various treatments to alter or tailor the wettability for testing and simulation that more closely resembles real-world rock structure characteristics. Such treatments can functionalize the surface via chemical modification of exposed surface groups, additional of functional chemical groups (e.g., using silane chemistry), physical coatings, or the like. Regardless, the surface functionalization can affect the wettability of the surface, and/or functionalizing the hydrophobicity, hydrophilicity, surface tension, etc.

For example, surface properties of the multimodal fluidic channel network (e.g., 104, 204) can be varied by means of physical vapor deposition (PVD), chemical vapor deposition (CVD), or atomic layer deposition (ALD). PVD provides a variety of vacuum deposition methods which can be used to produce thin films and coatings about the surfaces of a particular formed multimodal fluidic channel network. PVD is characterized by a process in which the material goes from a condensed phase to a vapor phase and then back to a thin film condensed phase (e.g., using sputtering or evaporation techniques). CVD is a chemical process that can be used to produce high quality, high-performance, solid materials to produce thin films on surfaces of a particular formed multimodal fluidic channel network. CVD can be used to deposit materials in various forms, including: monocrystalline, polycrystalline, amorphous, and epitaxial. These materials include: silicon (Si02, germanium, carbide, nitride, oxynitride), carbon (fiber, nanofibers, nanotubes, diamond and graphene), fluorocarbons, filaments, tungsten, titanium nitride and various high-k dielectrics. ALD is a thin film deposition technique that is based on the sequential use of a gas phase chemical process. Most ALD reactions use two chemicals, typically called precursors. These precursors can react with surfaces of the multimodal fluidic channel network one at a time in a sequential, self-limiting, manner. Through the repeated exposure to separate precursors, a thin film can slowly be deposited on the multimodal fluidic channel network. The fluidic device can be made to have dual wettability by depositing a layer of different wettability on various portions of the channels within the fluidic device. For example, a portion of the channels can be coated with a wettability control agent while a separate portion of the channels can be left uncoated or coated with a second and different wettability control agent.

Regardless of which technique is used to alter the inner channel surfaces associated with the multimodal fluidic channel network (e.g., wettability, hydrophobicity, hydrophilicity, surface tension, etc.), chemical additives can change the surface properties of the channels while keeping interfacial tension and viscosity of the fluids constant. Such chemical additives to tailor wettability, for instance, can include organic and inorganic chemicals. FIG. 5 illustrates a system and method for measuring fluid thermodynamic and fluid transport properties in a low-permeability rock structure. The system can comprise utilizing a formed nanofluidic device 400, such as any one of the nanofluidic devices 28, 100, 200, or 300 discussed herein. Accordingly, the nanofluidic device 400 can comprise a fluid inlet 410a and a fluid outlet 410b in fluid communication with each other via a multimodal fluidic channel network 404 (i.e., formed using techniques described herein) that represents fluid flow in a given low-permeability rock structure. The multimodal fluidic channel network 404 can be treated to a particular wettability or other surface characteristic, as discussed above. A fluid pump 420 (e.g., a syringe pump) can draw/receive fluid from a fluid reservoir 422, and be operated to inject such fluid into the multimodal fluidic channel network 404 of the nanofluidic device 400 via the fluid inlet 410a (e.g., multi-phase fluids can be used, such as steam, gas, C0 ₂ flooding, hydrocarbons, etc.).

One or more input lines 412a and 412b can be in fluid communication between the fluid pump 420 and the nanofluidic device 400. The fluid can flow through the multimodal fluidic channel network 404, out the fluid outlet 410b, and into a fluid receiver 424 for collection. A computer system 426 can be operatively coupled to the fluid line 412b via a pressure transducer 428, which is operated to measure the relative fluid pressure that exists by virtue of fluid flow through the multimodal fluidic channel network 404. The computer system 426 can receive signals from the pressure transducer 428 associated with said fluid pressure. This measured fluid pressure is associated with the particular permeability of the nanofluidic device 400, which is directly related to the represented "porosity" of the represented low-permeability rock structure.

In this simulation, the computer system 426 can facilitate performance of various experiments related to different processes such as water transport, C0 ₂ flooding, and sequestration and measurement of relevant properties associated with the represented low- permeability rock structure. The computer system 426 can then analyze collected data to facilitate determination of the particular fluid thermodynamic properties and fluid transport properties of the low-permeability rock structure represented by the multimodal fluidic channel network. Advantageously, because the wettability (or other surface characteristic) of the multimodal fluidic channel network has been tailored to represent in-situ wettability, for instance, of a particular low-permeability rock structure, the simulation results are more reliable and accurate than computer models that merely model wettability, because the present example nanofluidic devices have been surface treated using chemical treatments representative of actual characteristics of a low-permeability rock structure sample. Optionally, a microscope can also be optically associated with the device so that fluid flow through the device can be visually monitored in real time.

This particular simulation system and technique can assist in developing new constitutive transport laws for shales by performing flow through experiments with these nanofluidic devices on a nanoscale level. This particular simulation system and technique can also assist with understanding the effect of wettability by tailoring the wettability of these nanofluidic devices in a real-world application and environment (e.g., wettability not being modeled on a computer). This system and technique can also help with understanding the effect of channel shape and dimensions on relative permeability of certain shale rock structures. Furthermore, this system and technique can further assist with understanding the effect of confinement on pressure- volume-temperature (PVT) properties of hydrocarbon fluids. Finally, this system and technique can reduce water usage, safe and permanent C0 ₂ sequestration, remediation planning for mitigating legacy industrial waste, because in-the-field pilot projects will not be needed because the testing and simulation can be performed as discussed herein.

Based on the particular data analyzed by the computer system 426, engineers can then determine the most effective fracturing fluid and proppant to be used for a particular reservoir, which is often the most critical factor in successfully extracting hydrocarbon fluids from shale rock reservoirs. The data can also assist with understanding so-called bubble points of nano-confined oil, which is an important parameter in shale oil production, because it is important to know the position of the bubble point on a P-T (pressure- temperature) plot of the reservoir fluids. The draw-down in the reservoir largely depends upon the bubble point of the oil in the in- situ state in the reservoir rock. A larger drawdown allows higher initial rates of recovery. However, if the bottom hole pressure drops below the bubble point pressure of the reservoir, the liquid recovery is impeded due to gas production which dominates the flow. Such nano fluidic devices can also be used to measure properties of other fluids such as water and blood with applications in community health sector.

FIG. 6 illustrates a method 500 for measuring fluid thermodynamic and fluid transport properties in a low-permeability rock structure. At operation 510, the method can comprise collecting data describing physical characteristics of a low-permeability rock structure. For instance, data can be collected as associated with a pore distribution of a shale rock sample by utilizing imaging techniques, as discussed above regarding FIG. 1, to generate a modeled, complex network of channels and pores representative of the shale rock sample (e.g., along with utilizing FIB-SEM or XRM). At operation 520, the method can comprise fabricating a rock fluidic channel reduction representing the physical characteristics of the low-permeability rock structure. The rock fluidic channel reduction can define a multimodal fluidic channel network to be formed onto a substrate. Thus, the rock fluidic channel reduction is a modeled reduction of the low-permeability rock structure, as further exemplified regarding FIGS. 1-4. At operation 530, the method can comprise flowing fluid through the multimodal fluidic channel network, as exemplified regarding FIG. 5. At operation 540, the method can comprise measuring fluid thermodynamic properties and fluid transport properties of the rock fluidic channel reduction, as defining a multimodal fluidic channel network, as also exemplified regarding FIG. 5.

The foregoing detailed description describes the invention with reference to specific exemplary embodiments. However, it will be appreciated that various modifications and changes can be made without departing from the scope of the present invention as set forth in the appended claims. The detailed description and accompanying drawings are to be regarded as merely illustrative, rather than as restrictive, and all such modifications or changes, if any, are intended to fall within the scope of the present invention as described and set forth herein.