Abstract: Methods and systems for a novel three-dimensional (“3D”) pore roughness quantification are disclosed. The methods include obtaining an image of a pore space. The methods further include, using an image analysis system: discretizing the 3D image to generate a meshed surface; constructing a reference surface and a constructed surface from the meshed surface; evaluating a plurality of surface distances; and determining a roughness coefficient. The methods further include obtaining an observed T2 time for at least one sample depth in a well; determining a corrected T2 time from the observed T2 time; and determining an average pore size in a rock formation.

Abstract: A method includes modeling a reservoir using a lab scale set of models and a field scale set of models. The reservoir is modeled using the lab scale set of models by scanning a sample of the reservoir into the lab scale set of models to create modeled fractures, estimating hydraulic properties of the modeled fractures, estimating multi-phase dynamic properties of the modeled fractures, and determining characteristics of a flow regime of a fluid flowing through the modeled fractures. The reservoir is modeled using the field scale set of models by modeling a discrete fracture network of the reservoir, upscaling the discrete fracture network, and calibrating the discrete fracture network. An enhanced oil recovery operation is designed and performed on the reservoir using the calibrated discrete fracture network.

Abstract: A method may include obtaining fracture image data regarding a geological region of interest. The method may further include determining various fractures in the fracture image data using a first artificial neural network and a pixel-searching process. The method may further include determining a fracture model using the fractures, a second artificial neural network, and borehole image data. The method may further include determining various fracture permeability values using the fracture model and a third artificial neural network. The method may further include determining various matrix permeability values for the geological region of interest using core sample data. The method may further include generating a coarsened grid model for the geological region of interest using a fourth artificial neural network, the matrix permeability values, and the fracture permeability values.

Abstract: A method for water drainage of a substrate includes creating, on a surface of the substrate, a designated hydrophobic region having hydrophobic surfaces of a hydrophobic film. Electronic circuitries are fabricated in the designated hydrophobic region of the substrate. The method further includes creating, on the surface of the substrate, a designated hydrophilic region having hydrophilic surfaces of the substrate. A drainage channel is formed in the designated hydrophilic region. The method further includes facilitating, based on capillary imbibition of the drainage channel, fluid flow from the designated hydrophobic region to a drainage/evaporation port to prevent damage of the electronic circuitries by moisture accumulation in the designated hydrophobic region.

Abstract: Systems and methods for correcting NMR T2 times are disclosed. The method may include creating a plurality of 3D rough surface pore models, where each 3D rough surface pore model includes a rough surface, for each of the plurality determining a pore roughness coefficient (PRC) and a volume; and simulating a first T2 relaxation time based on the 3D rough surface pore model. The method may further include determining a smooth surface pore model, with the same volume as the 3D rough surface pore model, and simulating a second T2 relaxation time based on the smooth surface pore model. The method may still further includes determining a T2 rough surface correction factor based on the first and the second T2 relaxation times, and forming a data pair comprising the pore roughness coefficient (PRC) and the T2 rough surface correction factor; and fitting a T2 correction curve to the data pairs.

Abstract: Techniques for determining reservoir formation properties include generating digital models of core samples taken from one or more reservoir formations based on corresponding images of the core samples; determining a pore throat size distribution of the core samples based on the generated digital models; determining corresponding capillary pressure curves and corresponding NMR value distributions of the core samples with one or more numerical simulations; generating one or more machine-learning (ML) models based on the pore throat size distribution, corresponding capillary pressure curves, and corresponding NMR value distributions of the core samples; adjusting the one or more ML models with one or more reservoir data of the one or more reservoir formations; generating adjusted capillary pressure curves and NMR value distributions from the one or more adjusted ML models; and determining a reservoir formation specific pore throat size distribution from at least one of the adjusted capillary pressure curves or

Abstract: Techniques for determining reservoir formation properties include generating digital models of core samples taken from one or more reservoir formations based on corresponding images of the core samples; determining a pore throat size distribution of the core samples based on the generated digital models; determining corresponding capillary pressure curves and corresponding NMR value distributions of the core samples with one or more numerical simulations; generating one or more machine-learning (ML) models based on the pore throat size distribution, corresponding capillary pressure curves, and corresponding NMR value distributions of the core samples; adjusting the one or more ML models with one or more reservoir data of the one or more reservoir formations; generating adjusted capillary pressure curves and NMR value distributions from the one or more adjusted ML models; and determining a reservoir formation specific pore throat size distribution from at least one of the adjusted capillary pressure curves or

Abstract: A method for manufacturing a micromodel with a mixed wettability surface representing a hydrocarbon reservoir is disclosed. The method includes coating a top surface of a hydrophilic substrate with photoresist, covering a top of the photoresist with a photomask, exposing the covered top of the photoresist to UV light that changes a chemical property of a region of the photoresist corresponding to a pattern of the photomask, removing the photomask, removing the region of the photoresist corresponding to the pattern of the photomask based on the chemical property of the region, depositing a hydrophobic thin-film on top of the hydrophilic substrate, and removing a remaining photoresist covered with the thin-film, such that the surface of the hydrophilic substrate is patterned with both a region covered with the hydrophobic thin-film and an uncovered region of the hydrophilic substrate, creating a mixed wettability surface on the hydrophilic substrate that represents the micromodel.

Abstract: A method is disclosed for modeling fluid flow through a fracture. The method includes obtaining a normal stress, and a shear stress and determining a first three-dimensional (3D) aperture model. Further, the method includes estimating a normal fracture closure displacement under the normal stress and a fracture dilation under the shear stress and simulating a fluid flow through a second 3D aperture model of the fracture. The second 3D aperture model of the fracture is based on the first 3D aperture, the normal fracture closure displacement, and the fracture dilation. Additionally, the method includes calculating a permeability of the second 3D aperture model of the fracture based on the simulated fluid flow.

Abstract: A method for history matching utilizing Bayesian Markov Chain Monte Carlo (MCMC) workflow may include selecting a reservoir simulation model of interest, identifying a mathematical model relevant to the reservoir simulation model, and identifying a plurality of history matching parameters as initial priors. The method may include constructing a first model, utilizing the initial priors, to obtain updated priors. The method may include constructing a second model to obtain posteriors. The method may include determining history matching accuracy of the reservoir simulation model by comparing medians of the posteriors and a plurality of measured data. The method may further include, upon determining accuracy of the reservoir simulation model, performing a plurality of predictions of a reservoir.

Abstract: A method for fracture dynamic hydraulic properties estimation and reservoir simulation may include obtaining a first set of images of a first fracture. The method may include obtaining a first set of fracture detections from the first set of images, generating a plurality of numerical calculations based on the first set of fracture detections, and generating a second model based on the plurality of numerical calculations and the first set of fracture detections. The method may further include obtaining a second set of images of a second fracture of a new reservoir, generating a second set of fracture detections of the second fracture, and generating dynamic hydraulic estimations of the second fracture. The method may also include generating a three-dimensional reservoir simulation and determining a plurality of recovery schemes for the new reservoir.

Abstract: A method may include obtaining fracture image data regarding a geological region of interest. The method may further include determining various fractures in the fracture image data using a first artificial neural network and a pixel-searching process. The method may further include determining a fracture model using the fractures, a second artificial neural network, and borehole image data. The method may further include determining various fracture permeability values using the fracture model and a third artificial neural network. The method may further include determining various matrix permeability values for the geological region of interest using core sample data. The method may further include generating a coarsened grid model for the geological region of interest using a fourth artificial neural network, the matrix permeability values, and the fracture permeability values.

Abstract: A conformance improvement method involves injecting, via an injection well, a first water slug into a subsurface reservoir. A second water slug is injected, via the injection well, into the subsurface reservoir. The first and second water slugs have different viscosities, at least one of the first and second water slugs includes a surfactant, and the first and second water slugs combine with oil in the subsurface reservoir to form a microemulsion in a layer of the subsurface reservoir. A fluid is injected, via the injection well, into the subsurface reservoir. Oil is collected, via a production well, from the subsurface reservoir. The injected fluid causes the oil to move into the production well.

Abstract: Systems and methods for determining a 3D hydraulic aperture of a 3D fracture are disclosed. The method includes, obtaining a geometry of the 3D fracture, determining a fluid flow direction through the 3D fracture, and dividing the 3D fracture into a plurality of 2D cross-sections oriented substantially parallel to the fluid flow direction. The method further includes dividing each 2D cross-section into a plurality of Type I and Type II fracture segments based on a segment aspect ratio and a segment roughness ratio, determining a 2D segment hydraulic aperture for each of the plurality of Type I and Type II fracture segments, and determining the 3D hydraulic aperture of the 3D fracture based, at least in part, on the 2D segment hydraulic apertures of the plurality of Type I and Type II fracture segments.

Abstract: A conformance improvement method involves injecting, via an injection well, a first water slug into a subsurface reservoir. A second water slug is injected, via the injection well, into the subsurface reservoir. The first and second water slugs have different viscosities, at least one of the first and second water slugs includes a surfactant, and the first and second water slugs combine with oil in the subsurface reservoir to form a microemulsion in a layer of the subsurface reservoir. A fluid is injected, via the injection well, into the subsurface reservoir. Oil is collected, via a production well, from the subsurface reservoir. The injected fluid causes the oil to move into the production well.

Abstract: A method, system and computer readable medium is presented for use in enhancing oil recovery in a subsurface reservoir comprising. The method, system and computer readable medium defines a plurality of grid levels on a geological model of a subsurface reservoir. Connectivities and transmissibilities are calculated between neighboring cells in the same grid and between connecting cells between different grid levels. Gas and/or fluid dynamics are simulated using dynamic grid refinement where the connectivities and transmissibilities are updated at each time step based on the previously calculated connectivities and transmissibilities.

Abstract: A method, system and computer readable medium is presented for use in enhancing oil recovery in a subsurface reservoir comprising. The method, system and computer readable medium defines a plurality of grid levels on a geological model of a subsurface reservoir. Connectivities and transmissibilities are calculated between neighboring cells in the same grid and between connecting cells between different grid levels. Gas and/or fluid dynamics are simulated using dynamic grid refinement where the connectivities and transmissibilities are updated at each time step based on the previously calculated connectivities and transmissibilities.