In petroleum engineering, the transport phenomenon of proppants in a fracture caused by hydraulic fracturing is captured by hyperbolic partial differential equations (PDEs). The solution of this kind of PDEs may encounter smooth transitions, or there can be large gradients of the field variables. The numerical challenge posed in a shock situation is that high-order finite difference schemes lead to significant oscillations in the vicinity of shocks despite that such schemes result in higher accuracy in smooth regions. On the other hand, first-order methods provide monotonic solution convergences near the shocks, while giving poorer accuracy in the smooth regions. Accurate numerical simulation of such systems is a challenging task using conventional numerical methods. In this paper, we investigate several shock-capturing schemes. The competency of each scheme was tested against one-dimensional benchmark problems as well as published numerical experiments. The numerical results have shown good performance of high-resolution finite volume methods in capturing shocks by resolving discontinuities while maintaining accuracy in the smooth regions. These methods along with Godunov splitting are applied to model proppant transport in fractures. It is concluded that the proposed scheme produces non-oscillatory and accurate results in obtaining a solution for proppant transport problems.

Simultaneous-source acquisition has been recognized as an economic and efficient acquisition method, but the direct imaging of the simultaneous-source data produces migration artifacts because of the interference of adjacent sources. To overcome this problem, we propose the regularized least-squares reverse time migration method (RLSRTM) using the singular spectrum analysis technique that imposes sparseness constraints on the inverted model. Additionally, the difference spectrum theory of singular values is presented so that RLSRTM can be implemented adaptively to eliminate the migration artifacts. With numerical tests on a flat layer model and a Marmousi model, we validate the superior imaging quality, efficiency and convergence of RLSRTM compared with LSRTM when dealing with simultaneous-source data, incomplete data and noisy data.

In water-lubricated pipeline transportation of heavy oil and bitumen, a thin oil film typically coats the pipe wall. A detailed study of the hydrodynamic effects of this fouling layer is critical to the design and operation of oil-water pipelines, as it can increase the pipeline pressure loss (and pumping power requirements) by 15 times or more. In this study, a parametric investigation of the hydrodynamic effects caused by the wall coating of viscous oil was conducted. A custom-built rectangular flow cell was used. A validated CFD-based procedure was used to determine the hydrodynamic roughness from the measured pressure losses. A similar procedure was followed for a set of pipe loop tests. The effects of the thickness of the oil coating layer, the oil viscosity, and water flow rate on the hydrodynamic roughness were evaluated. Oil viscosities from 3 to 21300 Pa s were tested. The results show that the equivalent hydrodynamic roughness produced by a wall coating layer of viscous oil is dependent on the coating thickness but essentially independent of oil viscosity. A new correlation was developed using these data to predict the hydrodynamic roughness for flow conditions in which a viscous oil coating is produced on the pipe wall.

Emulsifier-free poly(methyl methacrylate-styrene) [P(MMA-St)] nanospheres with an average particle size of 100 nm were synthesized in an isopropyl alcohol-water medium by a solvothermal method. Then, through radical graft copolymerization of thermo-sensitive monomer -isopropylacrylamide (NIPAm) and hydrophilic monomer acrylic acid (AA) onto the surface of P(MMA-St) nanospheres at 80 °C, a series of thermo-sensitive polymer nanospheres, named SD-SEAL with different lower critical solution temperatures (LCST), were prepared by adjusting the mole ratio of NIPAm to AA. The products were characterized by Fourier transform infrared spectroscopy, transmission electron microscopy, thermogravimetric analysis, particle size distribution, and specific surface area analysis. The temperature-sensitive behavior was studied by light transmittance tests, while the sealing performance was investigated by pressure transmission tests with Lungmachi Formation shales. The experimental results showed that the synthesized nanoparticles are sensitive to temperature and had apparent LCST values which increased with an increase in hydrophilic monomer AA. When the temperature was higher than its LCST value, SD-SEAL played a dual role of physical plugging and chemical inhibition, slowed down pressure transmission, and reduced shale permeability remarkably. The plugged layer of shale was changed to being hydrophobic, which greatly improved the shale stability.

The conventional Markov chain Monte Carlo (MCMC) method is limited to the selected shape and size of proposal distribution and is not easy to start when the initial proposal distribution is far away from the target distribution. To overcome these drawbacks of the conventional MCMC method, two useful improvements in MCMC method, adaptive Metropolis (AM) algorithm and delayed rejection (DR) algorithm, are attempted to be combined. The AM algorithm aims at adapting the proposal distribution by using the generated estimators, and the DR algorithm aims at enhancing the efficiency of the improved MCMC method. Based on the improved MCMC method, a Bayesian amplitude versus offset (AVO) inversion method on the basis of the exact Zoeppritz equation has been developed, with which the P- and S-wave velocities and the density can be obtained directly, and the uncertainty of AVO inversion results has been estimated as well. The study based on the logging data and the seismic data demonstrates the feasibility and robustness of the method and shows that all three parameters are well retrieved. So the exact Zoeppritz-based nonlinear inversion method by using the improved MCMC is not only suitable for reservoirs with strong-contrast interfaces and long-offset ranges but also it is more stable, accurate and anti-noise.

In-depth understanding of interactions between crude oil and CO provides insight into the CO-based enhanced oil recovery (EOR) process design and simulation. When CO contacts crude oil, the dissolution process takes place. This phenomenon results in the oil swelling, which depends on the temperature, pressure, and composition of the oil. The residual oil saturation in a CO-based EOR process is inversely proportional to the oil swelling factor. Hence, it is important to estimate this influential parameter with high precision. The current study suggests the predictive model based on the least-squares support vector machine (LS-SVM) to calculate the CO-oil swelling factor. A genetic algorithm is used to optimize hyperparameters ( and ) of the LS-SVM model. This model showed a high coefficient of determination (  = 0.9953) and a low value for the mean-squared error (MSE = 0.0003) based on the available experimental data while estimating the CO-oil swelling factor. It was found that LS-SVM is a straightforward and accurate method to determine the CO-oil swelling factor with negligible uncertainty. This method can be incorporated in commercial reservoir simulators to include the effect of the CO-oil swelling factor when adequate experimental data are not available.

The recovery factor from tight gas reservoirs is typically less than 15%, even with multistage hydraulic fracturing stimulation. Such low recovery is exacerbated in tight gas condensate reservoirs, where the depletion of gas leaves the valuable condensate behind. In this paper, three enhanced gas recovery (EGR) methods including produced gas injection, CO injection and water injection are investigated to increase the well productivity for a tight gas condensate reservoir in the Montney Formation, Canada. The production performance of the three EGR methods is compared and their economic feasibility is evaluated. Sensitivity analysis of the key factors such as primary production duration, bottom-hole pressures, and fracture conductivity is conducted and their effects on the well production performance are analyzed. Results show that, compared with the simple depletion method, both the cumulative gas and condensate production increase with fluids injected. Produced gas injection leads to both a higher gas and condensate production compared with those of the CO injection, while waterflooding suffers from injection difficulty and the corresponding low sweep efficiency. Meanwhile, the injection cost is lower for the produced gas injection due to the on-site available gas source and minimal transport costs, gaining more economic benefits than the other EGR methods.

The most prominent aspect of multiphase flow is the variation in the physical distribution of the phases in the flow conduit known as the flow pattern. Several different flow patterns can exist under different flow conditions which have significant effects on liquid holdup, pressure gradient and heat transfer. Gas-liquid two-phase flow in an annulus can be found in a variety of practical situations. In high rate oil and gas production, it may be beneficial to flow fluids vertically through the annulus configuration between well tubing and casing. The flow patterns in annuli are different from pipe flow. There are both casing and tubing liquid films in slug flow and annular flow in the annulus. Multiphase heat transfer depends on the hydrodynamic behavior of the flow. There are very limited research results that can be found in the open literature for multiphase heat transfer in wellbore annuli. A mechanistic model of multiphase heat transfer is developed for different flow patterns of upward gas-liquid flow in vertical annuli. The required local flow parameters are predicted by use of the hydraulic model of steady-state multiphase flow in wellbore annuli recently developed by Yin et al. The modified heat-transfer model for single gas or liquid flow is verified by comparison with Manabe's experimental results. For different flow patterns, it is compared with modified unified Zhang et al. model based on representative diameters.

This paper examines the relationships between natural resource dependence, public education investment, and human capital accumulation. It addresses why the "blessing" of abundant natural resources often turns into a "curse" in many countries and regions, focusing on the crowding-out effect of natural resources on human capital. According to our empirical analysis of provincial panel data from China, natural resource dependence is significantly and negatively correlated with human capital accumulation. The crowding-out effect of natural resources on human capital exists only in the central and western regions of China. Our introduction of an interaction term for natural resource dependence and public education investment underscores the possibility of investing in public education to reduce the crowding-out effect of natural resource dependence on human capital. The government should utilize the income of the natural resource sector to increase investment in education to enhance local human capital.

The main objective of this work is to predict the mixing of two different miscible oils in a very long channel. The background to this problem relates to the mixing of heavy and light oil in a pipeline. As a first step, a 2D channel with an aspect ratio of 250 is considered. The batch-mixing of two miscible crude oils with different viscosities and densities is modeled using an unsteady laminar model and unsteady RANS model available in the commercial CFD solver ANSYS-Fluent. For a comparison, a LES model was used for a 3D version of the 2D channel. The distinguishing feature of this work is the Lagrangian coordinate system utilized to set no-slip wall boundary conditions. The global CFD model has been validated against classical analytical solutions. Excellent agreement has been achieved. Simulations were carried out for a Reynolds number of 6300 (calculated using light oil properties) and a Schmidt number of . The results show that, in contrast to the unsteady RANS model, the LES and unsteady laminar models produce comparable mixing dynamics for two oils in the channel. Analysis of simulations also shows that, for a channel length of 100 m and a height of 0.4 m, the complete mixing of two oils across the channel has not been achieved. We showed that the mixing zone consists of the three different mixing sub-zones, which have been identified using the averaged mass fraction of the heavy oil along the flow direction. The first sub-zone corresponds to the main front propagation area with a length of several heights of the channel. The second and third sub-zones are characterized by so-called shear-flow-driven mixing due to the Kelvin-Helmholtz vortices occurring between oils in the axial direction. It was observed that the third sub-zone has a steeper mass fraction gradient of the heavy oil in the axial direction in comparison with the second sub-zone, which corresponds to the flow-averaged mass fraction of 0.5 for the heavy oil.