Upscaled Model Research Articles

Dynamic Effects during the Capillary Rise of Fluids in Cylindrical Tubes.

The mathematical models for the capillary-driven flow of fluids in tubes typically assume a static contact angle at the fluid-air contact line on the tube walls. However, the dynamic evolution of the fluid-air interface is an important feature during capillary rise. Furthermore, inertial effects are relevant at early times and may lead to oscillations. To incorporate and quantify the different effects, a fundamental description of the physical processes within the tube is used to derive an upscaled model of capillary-driven flow in circular cylindrical tubes. The upscaled model extends the classical Lucas-Washburn model by incorporating a dynamic contact angle and slip. It is then further extended to account for inertial effects. Finally, the solutions of the different models are compared to experimental data. In contrast to the Lucas-Washburn model, the models with dynamic contact angle match well the experimental data, both the rise height and the contact angle, even at early times. The models have a free parameter through the dynamic contact angle description, which is fitted using the experimental data. The findings here suggest that this parameter depends only on the properties of the fluid but is independent of geometrical features, such as the tube radius. Therefore, the presented models can predict the capillary-driven flow in tubular systems upon knowledge of the underlying dynamic contact-angle relation.

Impacts of model resolution on multiple prediction

Despite theoretical advancements in multiple identification and elimination, the application and success of these advancements are questionable in some cases and are limited to marine environments, especially deepwater. In land seismic, however, a clear understanding of the internal multiple generators is not readily available; thus, efforts to attenuate them often are quite ineffective. We have analyzed, in the case of many thin layers, how the primaries and multiples are affected by fine-scale variations in the velocity model. Cross-coherence is used to measure the similarity of the original primaries/multiples and the ones generated from upscaled velocity models. The combined use of kurtosis and the cross-coherence method enables us to precisely quantify the impact of fine layering on multiples. Test results demonstrate that surface-related multiples and internal multiples are much more sensitive than the primaries to thickness variations of the velocity model. As the thickness of each upscaled layer varies from 1 to 21 m, multiples change rapidly, whereas primaries are almost the same. The high sensitivity of internal multiples on fine layering suggests that the detailed model information should be considered in model parameterization in the internal multiple removal, especially for model-driven methods.

Numerical tools for the simulation of enzymatic bio porous-electrodes operating in DET mode

Modeling of diffusion/enzymatic reaction in porous electrodes operating in direct electron transfer mode is developed. The solution at the pore-scale is extremely cumbersome due to the complex geometry of the porous material. The upscaled model is much easier to solve, while keeping the essential of the physico-chemical behavior. The method to carry out the solution can be described as follows•The effective diffusion coefficient involved in the macroscopic equations is accurately computed by solving a closure problem in a representative elementary volume.•Electrochemical parameters are identified by a direct resolution of the macroscopic model solved with a COMSOL Multiphysics code coupled to a curve fit procedure carried out on voltammetry experimental results using a Matlab code. Electrodes with different thicknesses may be considered in the fitting procedure to improve accuracy. An alternative use of the COMSOL Multiphysics code is to predict the electrode behavior and further optimize its design, if all the electrochemical parameters are identified.•To validate the upscaled model, the pore scale model may be solved with direct numerical simulations carried out in a 3D microstructure using another COMSOL Multiphysics code to compare with the solution of the upscaled model in the 1D-reduced geometry.

Comparisons of predictive ability of THAI in situ combustion process models with pre-defined fuel against that having fuel deposited based on Arrhenius kinetics parameters

Toe-to-heel air injection (THAI) is an in situ thermal-enhanced oil upgrading and recovery technology that makes use of a horizontal producer well for mobilised partially upgraded oil production to the surface. To design operation of the THAI process requires up-scaling lab-scale numerical model to field-scale reservoir numerical model. There are a number of up-scaling methods that were developed. However, these previous up-scaling methods only concentrated on the qualitative nature of the physicochemical processes. Furthermore, these methods have deficiencies ranging from assumption of 100% oxygen utilisation, failing to compare oil production rates for up-scaled reservoir models with and without fuel pre-defined, not reporting on the dynamics inside the reservoirs with and without fuel pre-defined, etc. As a result, this work provided in depth comparative studies of both the qualitative and quantitative physicochemical processes in numerical models containing Arrhenius-based coke deposition thermal cracking reaction (i.e. model A) and that having pre-defined fuel concentration (i.e. model F) as an initial parameter respectively. It is found that oil production started earlier in model A compared to in model F even though they have approximately similar trajectories. It is shown that by the end of the combustion period, oil recovery of 28.5% OOIP is achieved in model F which is greater than that in model A by an additional of 4.8% OOIP. It is found that the peak temperature, which indicates how healthy the combustion is at a single point only at different times, is generally considerably higher in model A than that in model F. It is further discovered that in some cases the combustion at all points might be stable and rigorous but in other cases the combustion might not be stable and rigorous at all points thereby implying that the peak temperature alone does not give the measure of the efficiency and spread of the combustion front. It is shown for the first time that pre-defining fuel concentration throughout the reservoir as is done in model F resulted in faster downward advancement and expansion of the combustion front compared to in the reservoir where the fuel is deposited based on the Arrhenius kinetics parameters (i.e. like in model A). It is also discovered that higher areal sweep of the reservoir is achieved in model F when compared to that achieved in model A. Overall, it then follows that higher volume of the reservoir of model F is combustion-swept, heat-affected, and oil-depleted compared to that in model A. These findings explain the reason why more oil is produced during the combustion period in model F than in model A. Conclusively, this first-of-a-kind study shows that pre-defining the fuel has no effect on the qualitative nature of the physicochemical processes, but has considerable influence on the quantitative parameters such as the rate of and cumulative oil production, peak temperature, areal and volumetric sweeps by the combustion zone, size of the oil-depleted zone, and size of the heat-affect zone. • Full analysis of predictive ability of THAI model F with pre-defined fuel is reported. • Model F predicted unrealistic high oil production rate & thus cumulative oil recovery. • Model F has faster downward-advancement & general expansion of the combustion fronts. • Higher reservoir volume is combustion-swept, heat-affected, & oil-depleted in model F. • Qualitative behaviours in model F are similar to those in the Arrhenius-based model A.

An experimental approach to determine local heat transfer characteristics in additively manufactured cooling configurations

Transient heat transfer measurements are performed on an additively manufactured real-scale cooling configuration with ribs on one side. A test rig is presented that operates at elevated pressure and provides a sudden temperature step in the fluid to heat the model walls. It enables the establishment of application-relevant flow conditions under which the local heat transfer characteristics are investigated while the manufacturing-related wall roughness can be preserved. The small dimensions prevent a direct temperature measurement in the cooling channels and a direct observation of the heat transfer surface is not possible. Thus, the fluid temperature is measured upstream and downstream of the model and the temperature response on the outer surface is measured by infrared thermography. Analytical modeling of the fluid temperature and a numerical method for calculating the 3D temperature propagation inside the model wall enable the determination of local heat transfer coefficients on the inner heat transfer surface. The crucial temperature data filtering and its effect on the results is described. A sensitivity analysis is performed to determine the best-suited evaluation times locally. The results of the developed method are compared to results from former measurements applying a well-established evaluation method on an up-scaled model with similar geometry.

Thermal Management for Hydrogen Charging and Discharging in a Screened Metal-Organic Framework Particle Tank.

Thermal management of H2 gas storage in a tank is crucial for determining the H2 gas deliverable capacity. In this study, a strategy for the design of an excellent comprehensive performance fuel storage tank from the screening of microscopic materials to the design of macroscopic particle adsorption tank performance is proposed. The best metal-organic framework (MOF) for H2 deliverable capacity in a computation-ready experimental MOF database is first screened using a grand canonical Monte Carlo (GCMC) method. An upscale model that combines the finite volume method with GCMC is then established to investigate the H2 charging and discharging processes in a screened best MOF-filled adsorption particle tank that is integrated with a phase-change material (PCM) jacket. The process of the heat and mass transfer in the screened best MOF particle adsorption tank with and without the PCM jacket-inserted metal foam is studied. The results show that the prescreened XAWVUN has the highest gravimetric and considerable volumetric deliverable capacity among 503 MOFs, which can reach up to 23.1 mol·kg-1 and 20.8 kg·m-3 at 298 K and pressures between 35 000 kPa (adsorption pressure) and 160 kPa (desorption pressure), respectively. The H2 deliverable capacity can be maximized by 3.2 and 12.1% for PCM jackets inserted with metal foam in the H2 charging and discharging processes when it is compared with the case without the PCM jacket, respectively. The above study will facilitate the development of new equipment for hydrogen storage.

In-situ Combustion Simulation from Laboratory to Field Scale

In-situ combustion simulation from laboratory to field scale has always been challenging, due to difficulties in deciding the reaction model and Arrhenius kinetics parameters, together with erroneous results observed in simulations when using large-sized grid blocks. We present a workflow of successful simulation of heavy oil in-situ combustion process from laboratory to field scale. We choose the ongoing PetroChina Liaohe D block in-situ combustion project as a case of study. First, we conduct kinetic cell (ramped temperature oxidation) experiments, establish a suitable kinetic reaction model, and perform corresponding history match to obtain Arrhenius kinetics parameters. Second, combustion tube experiments are conducted and history matched to further determine other simulation parameters and to determine the fuel amount per unit reservoir volume. Third, we upscale the Arrhenius kinetics to the upscaled reaction model for field-scale simulations. The upscaled reaction model shows consistent results with different grid sizes. Finally, field-scale simulation forecast is conducted for the D block in-situ combustion process using computationally affordable grid sizes. In conclusion, this work demonstrates the practical workflow for predictive simulation of in-situ combustion from laboratory to field scale for a major project in China.

Practical implementation of a method for global single-phase flow-based transmissibility upscaling using generic flow boundary conditions and its application on models with non-local heterogeneities

Local upscaling techniques fall short in capturing the dynamic effects of laterally continuous non-local geologic heterogeneities, for example, high-permeability channels, vertically thin, yet, horizontally extensive shale layers. Global upscaling techniques have been introduced to remedy the shortcomings of local scale-up approaches. In order to address the upscaling challenges associated with non-local heterogeneities, we have developed a practical and effective flow-based transmissibility scale-up method that computes coarse-scale transmissibilities using flux derived from single-phase flow simulations with generic global boundary conditions, referred to as the global transmissibility upscaling (GTU) method. GTU targets more accurate upscaling of laterally continuous non-local heterogeneities including the ones modeled on distorted cornerpoint grids. A variant of GTU is developed in this context that uses fluxes computed by use of the multi-point flux approximation (MPFA) discretization technique at the fine scale. While various global upscaling methods were described in the literature, they are rarely used in industrial applications due to challenges related to implementation. We describe in detail an effective practical implementation of the GTU method in a comprehensive industrial-grade simulation package and share our learnings with GTU on aggressively upscaled models with non-local heterogeneities. We demonstrate the application of GTU to several challenging reservoir models. Comparisons of GTU-based model responses are made with ones stemming from local upscaling techniques popularly utilized in the industry using fine-scale model predictions as reference. Investigated numerical examples demonstrate that the GTU method leads to notable improvements in the accuracy delivered by coarse-scale models. Especially, the application of GTU is most impactful for high-upscaling-ratio models with complex fine-scale connectivity because GTU preserves the fine-scale behavior more authentically compared to local techniques. We demonstrate that GTU naturally complements an innovative regional multiphase upscaling (RMU) method on aggressively upscaled models with strong multiphase flow associated with displacement-type recovery mechanisms. It has also been observed that using MPFA on cornerpoint grids to obtain fine-scale fluxes for GTU gives rise to more accurate coarse-scale pressure behavior. We have also observed that GTU is especially effective when combined with a regional multiphase upscaling method for ultimate accuracy in simulations of displacement-based recovery mechanisms. • A practical global transmissibility upscaling method using global flows enables fast and accurate flow simulations. • Global transmissibility upscaling preserves the fine-scale information more authentically compared to local techniques. • Global transmissibility upscaling combined with regional multiphase upscaling for fast and accurate flow simulation. • Speed-up values in the order of 10–50 fold are achieved over fine-scale model with a good compromise of accuracy.

Experimental and Numerical Investigations of Cement Bonding Properties.

Well integrity is of high importance during the entire well life span especially when renewable energy resources such as geothermal are designed to cover the increasing world energy demand. Many studies have documented the importance of the casing–cement interfacial bonding to ensure critical well integrity achievements; however, laboratory experiments and field data are not always aligned. Furthermore, Finite Element Analysis shows relatively high discrepancies compared with the results of various scholarly published works. The limitations in the FEA are most probably generated by the casing–cement interaction modeling parameters. Typically, the contact between casing and cement is modeled using the so-called CZM method, which includes the shear debonding process into the FEA. Several setups have been used in the past to determine the interfacial casing–cement bonding shear strength. Some of these setups are briefly summarized herein. The novelty of this paper consists in the combination of a relatively simple experimental setup with the finite element modeling of the experiment itself to demonstrate that it is important to acquire accurate laboratory data for debonding simulations and, thus, to improve the well integrity prediction. The aim of this paper is to better understand the limitations of the finite element method when modeling shear bonding of the cement and, in the same, to verify that the proposed experimental setup can be modelled using numerical approaches. The successful numerical simulation can later be used for upscaled models. The results confirm the experimental push down setup and aid engineers to further understand and validate CZM models and optimize the well design to achieve maximum well integrity potential. Our results are within 1% error from the average field data.

Upscaled modeling of complex DNAPL dissolution

A straightforward, upscaled DNAPL mass dissolution model is developed using relatively simple input consisting of characteristic dimensions and saturations of a DNAPL accumulation. Multiple accumulations are aggregated into a single source zone volume. Physically, the dissolution process is a combination of flow through the mass (advective component) and flow around the mass (dispersive component). The contribution of each component is based on initial characteristic length scales and the average initial saturation. Changes over time with the depletion of mass are captured with a changing relative permeability and a power law relationship for the fraction of initial mass remaining. The utility of the upscaled process model is demonstrated with data from three studies: numerical simulation of multiple pools, two-dimensional test cell experiments with mixed architecture and with heterogeneous soil, and a controlled field study of multicomponent DNAPL release and depletion. Use of the model successfully reproduced the observed multistage mass discharge in each study and illuminated the governing processes. The power law exponent was relatively constant for the various conditions and relative permeability changes were integral to the success. The numerical and experimental studies were run to complete mass depletion which the upscaled model matched. The input parameters are minimal and are found in typical DNAPL source zone characterization data.

Analyzing the Impacts of Meshing and Grid Alignment in Dual-Porosity Dual-Permeability Upscaling

SummaryThe discrete fracture network (DFN) model is widely used to simulate and represent the complex fractures occurring over multiple length scales. However, computational constraints often necessitate that these DFN models be upscaled into a dual-porosity dual-permeability (DPDK) model and discretized over a corner-point grid system, which is still commonly implemented in many commercial simulation packages. Many analytical upscaling techniques are applicable, provided that the fracture density is high, but this condition generally does not hold in most unconventional reservoir settings. A particular undesirable outcome is that connectivity between neighboring fracture cells could be erroneously removed if the fracture plane connecting the two cells is not aligned along the meshing direction.In this work, we propose a novel scheme to detect such misalignments and to adjust the DPDK fracture parameters locally, such that the proper fracture connectivity can be restored. A search subroutine is implemented to identify any diagonally adjacent cells of which the connectivity has been erroneously removed during the upscaling step. A correction scheme is implemented to facilitate a local adjustment to the shape factors in the vicinity of these two cells while ensuring the local fracture intensity remains unaffected. The results are assessed in terms of the stimulated reservoir volume calculations, and the sensitivity to fracture intensity is analyzed.The method is tested on a set of tight oil models constructed based on the Bakken Formation. Simulation results of the corrected, upscaled models are closer to those of DFN simulations. There is a noticeable improvement in the production after restoring the connectivity between those previously disconnected cells. The difference is most significant in cases with medium DFN density, where more fracture cells become disconnected after upscaling (this is also when most analytical upscaling techniques are no longer valid); in some 2D cases, up to a 22% difference in cumulative production is recorded. Ignoring the impacts of mesh discretization could result in an unintended reduction in the simulated fracture connectivity and a considerable underestimation of the cumulative production.

Numerical simulation of different-scale fracture effects on saturation distributions in waterflooding via the finite volume method

Capturing the heterogeneity and multiple scales in fractured media is important for understanding the underlying mechanisms controlling the flow behavior, as both natural and hydraulic fractures can dominate the flow patterns in media of this type. Fracture characteristics, such as heterogeneity, multiple scales, and extreme size-to-aperture ratios, challenge standard macroscale mathematical and numerical modeling methods of the flow based on the concept of volume averaging. This paper presents a finite volume method approach for solving a two-phase flow model of discrete fractures that accounts for the heterogeneity and multiscale fracture distribution in fractured reservoirs. Fracture model combinations, obtained by restricting different models to different parts of a domain or by using models with explicit representations of fractures as a basis for upscaled continuum models, are also presented. Furthermore, the model error correction method due to fracture dimensionality reduction and an inappropriate upwind scheme is also analyzed.

Upscaling Mixing-Controlled Reactions in Unsaturated Porous Media

We study mixing-controlled chemical reactions in unsaturated porous media from a pore-scale perspective. The spatial heterogeneity induced by the presence of two immiscible phases, here water and air, in the pore space generates complex flow patterns that dominate reactive mixing across scales. To assess the impact of different macroscopic saturation states (the fraction of pore volume occupied by water) on mixing-controlled chemical reactions, we consider a fast irreversible reaction between two initially segregated dissolved species that mix as one solution displaces the other in the heterogeneous flow field of the water phase. We use the pore-scale geometry and water distributions from the laboratory experiments reported by Jiménez-Martínez et al. (Geophys. Res. Lett. 42: 5316–5324, 2015). We analyze reactive mixing in three complementary ways. Firstly, we post-process experimentally observed spatially distributed concentration data; secondly, we perform numerical simulations of flow and reactive transport in the heterogeneous water phase, and thirdly, we use an upscaled mixing model. The first approach relies on an exact algebraic map between conservative and reactive species for an instantaneous irreversible bimolecular reaction that allows to estimate reactive mixing based on experimental conservative transport data. The second approach is based on reactive random walk particle tracking simulations in the numerically determined flow field in the water phase. The third approach uses a dispersive lamella approach that accounts for the impact of flow heterogeneity on mixing in terms of effective dispersion coefficients, which are estimated from both experimental data and numerical random walk particle tracking simulations. We observe a significant increase in reactive mixing for decreasing saturation, which is caused by the stronger heterogeneity of the water phase and thus of the flow field. This is consistently observed in the experimental data and the direct numerical simulations. The dispersive lamella model, parameterized by the effective interface width, provides robust estimates of the evolution of the product mass obtained from the experimental and numerical data.

Double Averaging Analysis Applied to a Large Eddy Simulation of Coupled Turbulent Overlying and Porewater Flow

AbstractFreestream turbulence in rivers is a key contributor to the flux of dissolved nutrients, carbon, and other ecologically important solutes into porewater. To advance understanding of turbulent hyporheic exchange and porewater transport, we investigate flow over and through a rough bed of spheres using large eddy simulation (LES). We apply double averaging (combined space and time averaging) to the LES results to determine the mean velocity distribution, momentum balance, and drag forces. Our simulations show large‐scale freestream structures interacting strongly with vortices generated at the surfaces of individual spheres to control turbulent momentum fluxes into the bed. The transition between turbulent flow and Darcy flow occurs over the first row of spheres, where turbulence decays rapidly and turbulent kinetic energy, Reynolds stress, and drag forces peak. Below this region, turbulence is only present in the high‐velocity flow in open pore throats. Experimental observations suggest that minimum mean porewater velocity occurs in the first open pore space below the transition region, but our results show that the minimum occurs between the first and second pore spaces. The simulation mean porewater velocities are approximately half those captured in measurements because the model resolves the entire flow continuum while measurements can access high‐velocity fluid in open pores. The high‐resolution dual time‐space averaging of the LES resolves both turbulent and mean flow features that are important to interfacial solute and particle fluxes, providing a means to include turbulent hyporheic exchange in upscaled river models, which has not been achieved to date.

Flexure resistant 3D printed zeolite-inspired structures

Polymer-based materials exhibit a good combination of strength and ductility but limited flexural strength. Here we demonstrate a family of new zeolite templated interconnected carbon nanotubes like porous networks with unique topologies with enhanced load-bearing and energy-absorbing capabilities. The structures were initially obtained from fully atomistic molecular dynamics simulations and then 3D printed using polylactide serving as an upscaled molecular model. All the structures show multi-fold enhancement in compression and flexural strength as compared to their solid counterparts. The 3D printed structure has 575.41 MPa compressive Young’s modulus and 318.87 MPa flexural modulus. The mechanical of the atomic models and 3D printed structures show some scale-independent (in a sense that atomic and macro models show similar behavior) features due to similar topological features and deformation conditions. • Zeolite-based architecture developed via atomistic molecular dynamics simulations. • Atomistic and macroscale 3D printed models were fabricated. • The compression and flexural strengths were measured. • 3D printed structure IWS-2 showing highest measured Young’s modulus of 575.41 MPa.

Treatment of model error in subsurface flow history matching using a data-space method

Subsurface flow models are inherently imperfect, and the associated model error can lead to unreliable flow predictions. In this work, we introduce treatments for model error in a data-space inversion (DSI) framework. DSI is a history matching procedure that constructs posterior flow predictions (for quantities of interest) directly, within a Bayesian setting, using a large set of prior-model flow simulation results and observed data. The model error considered in this work derives from the use of upscaled/coarsened surrogate models for the prior-model flow simulations required by DSI. Our error treatment entails the simulation of a set of corresponding pairs of fine and upscaled models. These results are used to construct a principal component analysis (PCA) representation of error. A linear regression approach is introduced to capture the coupled nature of the coarse-scale simulation output and model error. To construct posterior DSI predictions, a joint inversion on coarse-scale simulation data and model error is performed using an ensemble smoother with multiple data assimilation. Both the prior simulation data and error terms are parameterized using PCA-based procedures. Results are presented for two-phase flow in 3D channelized geomodels. The corrected prior and DSI posterior results are compared to reference results generated from fine-scale simulations. Comparisons are presented for flow statistics, Mahalanobis distance, and relative error for multiple (synthetic) true models. The coupled model error treatment is shown to provide highly accurate prior results and posterior predictions that agree closely with reference results. Significant improvement relative to uncorrected coarse models is observed. The treatments developed here can be used to represent error from many different sources in a variety of subsurface flow settings.

Development of a novel wind to electrical energy converter of passive ferrofluid levitation through its parameter modelling and optimization

The exclusive properties of passive levitation and ultra-low friction surface formation of ferrofluids have been utilized to design a highly efficient wind energy harvester. A novel design of passive ferrofluid levitation wind energy converter has been proposed and laboratory prototype has been developed. The simulation model has been developed using the ANSYS Workbench Maxwell electromagnetic software and validated by the experimental results. In this paper, different approaches such as response surface method (RSM), central composite design (CCD) and artificial neural network (ANN) modelling have been applied to relate the system output power to the input design parameters of the wind energy harvester system. The sensitivity analysis of design parameters and their interactions have been conducted. The CCD and RSM modelling have been applied for predicting the power output from the design parameters for the energy harvester where the design parameters has been optimized for the maximum power output using the genetic algorithm (GA). Also, the RSM modelling is validated by the analysis of variance. As a result, the optimal design parameter combination to produce the highest power output can be identified. The optimization result will be compared with and verified by the prediction result of the ANN model. It is found that within the range of the design parameters, the maximum power output of the wind energy harvester obtained through the RSM with the GA is close to that predicted by the ANN model. The design optimization method can be extended to develop an upscale model of the wind energy harvester for larger power output. The proposed magnetic levitation technology has many more potential applications in sensors and actuators, cooling and mechanical bearings and in health sectors.

Evaluation of forest carbon uptake in South Korea using the national flux tower network, remote sensing, and data-driven technology

Forests provide most of the carbon sequestration of atmospheric carbon dioxide (CO2); however, accurately quantifying the uptake amount over a region remains challenging. For reginal or national estimates, the forest productivity model and forest inventories are used which provide information for national greenhouse gas inventories. However, it has some limitations, such as not considering below-ground biomass, its lack of species-specific allometric models, the restrictions it places during fieldwork, and the long period it takes to complete the survey. In contrast to inventory-based biomass estimates, the eddy covariance (EC) method can assess net CO2 exchange of a whole ecosystem continuously and automatically with a high temporal resolution. Since, these measurements only represent a site-level observation scale (∼ 1 km2), upscaling via linkages with observation data, remote sensing, and modeling methods has been used to estimate regional or national land-atmosphere carbon fluxes. In this study, we employ a data-driven method to estimate the national-scale gross primary production (GPP) and net ecosystem CO2 exchange (NEE) by combining EC flux data from 10 sites in South Korea with remote sensing data through a machine learning algorithm based on support vector regression (SVR) for the period 2000–2018. Site-level evaluation of estimated GPP and NEE from the SVR-based model shows equivalent performance compared to other continental and global upscaled models. The mean estimated annual GPP and NEE of the South Korea forests region over the period 2000–2018 were 1465 ± 37 and −243 ± 32 g C m2 year−1, respectively. The SVR-based net primary production (NPP) was consistent with the biometric-based NPP (r2 = 0.46, p < 0.05). This study shows that combining data from a national flux network and remote sensing using a data-driven approach can be used to estimate forest CO2 fluxes on a national scale.

A novel flow-based geometrical upscaling method for representing fault zones with two-phase fault rock properties into a dynamic reservoir model

Faults are generally represented in conventional upscaled models as 2D planar surfaces with transmissibility multipliers used to represent single-phase fault properties. However, faults are structurally complex 3D zones in which both single-phase and two-phase fault rock properties can be significant. Ignoring this structural and petrophysical complexity within faults may impart considerable inaccuracy on the predictive performance of upscaled models. This study has developed a two-phase flow-based geometrical upscaling method capable of representing simultaneously the complex geometry and saturation-dependent two-phase flow properties of realistic fault zones. In this approach, high-resolution sector models are built of small portions of the fault zones and assigned appropriate single-phase and two-phase fault rock properties. Steady state two-phase flow simulations at different fractional flows of oil and water are used to determine the saturation dependent upscaled pseudo relative permeability functions which are incorporated into upscaled models. The method is applied to an example model containing two 3D fault zone components and tested by comparing the flow results of upscaled model with those of a high-resolution truth model. Results show that two-phase flow-based geometrical upscaling is a promising method for representing the effects of two-phase fault rock properties and complex 3D fault zone structure simultaneously.

Cochlear Size Assessment Predicts Scala Tympani Volume and Electrode Insertion Force- Implications in Robotic Assisted Cochlear Implant Surgery.

Objectives: The primary aim was to measure the volume of the scala tympani (ST) and the length of the straight portion of the cochlear basal turn from micro-computed tomography (μCT) images. The secondary aim was to estimate the electrode insertion force based on cochlear size and insertion speed. Both of these objectives have a direct clinical relevance in robotic assisted cochlear implant (CI) surgery.Methods: The ST was segmented in thirty μCT datasets to create a three-dimensional (3D) model and calculate the ST volume. The diameter (A-value), the width (B-value), and the straight portion of the cochlear basal turn (S-value) were measured from the oblique coronal plane. Electrode insertion force was measured in ST models of two different sizes, by inserting FLEX24 (24 mm) and FLEX28 (28 mm) electrode arrays at five different speeds (0.1, 0.5, 1, 2, and 4 mm/s).Results: The mean A-, B-, and S-values measured from the 30 μCT datasets were 9.0 ± 0.5, 6.7 ± 0.4, and 6.9 mm ± 0.5, respectively. The mean ST volume was 34.2 μl ± 7 (range 23–50 μl). The ST volume increased linearly with an increase in A- and B-values (Pearson's coefficient r = 0.55 and 0.56, respectively). The A-value exhibited linear positive correlation with the B-value and S-value (Pearson's coefficient r = 0.64 and r = 0.66, respectively). In the smaller of the two ST models, insertion forces were higher across the range of insertion speeds during both array insertions, when compared to the upscaled model. Before the maximum electrode insertion depths, a trend toward lower insertion force for lower insertion speed and vice-versa was observed.Conclusion: It is important to determine pre-operative cochlear size as this seems to have an effect upon electrode insertion forces. Higher insertion forces were seen in a smaller sized ST model across two electrode array lengths, as compared to an upscaled larger model. The ST volume, which cannot be visualized on clinical CT, correlates with clinical cochlear parameters. This enabled the creation of an equation capable of predicting ST volume utilizing A- and B-values, thus enabling pre-operative prediction of ST volume.