This paper is devoted to study the problem of nonisothermal two-phase flow with nanoparticles transport in heterogenous porous media, numerically. For this purpose, we introduce a multiscale adapted time-splitting technique to simulate the problem under consideration. The mathematical model consists of equations of pressure, saturation, heat, nanoparticles concentration in the water–phase, deposited nanoparticles concentration on the pore–walls, and entrapped nanoparticles concentration in the pore–throats. We propose a multiscale time splitting IMplicit Pressure Explicit Saturation–IMplicit Temperature Concentration (IMPES-IMTC) scheme to solve the system of governing equations. The time step-size adaptation is achieved by satisfying the stability Courant–Friedrichs–Lewy (CFL<1) condition. Moreover, numerical test of a highly heterogeneous porous medium is provided and the water saturation, the temperature, the nanoparticles concentration, the deposited nanoparticles concentration, and the permeability are presented in graphs.
Recently, applications of nanoparticles have been considered in many branches of petroleum engineering, especially, enhanced oil recovery. The current paper is devoted to investigate the problem of nanoparticles transport in fractured porous media, numerically. We employed the discrete-fracture model (DFM) to represent the flow and transport in the fractured formations. The system of the governing equations consists of the mass conservation law, Darcy's law, nanoparticles concentration in water, deposited nanoparticles concentration on the pore-wall, and entrapped nanoparticles concentration in the pore-throat. The variation of porosity and permeability due to the nanoparticles deposition/entrapment on/in the pores is also considered. We employ the multiscale time-splitting strategy to control different time-step sizes for different physics, such as pressure and concentration. The cell-centered finite difference (CCFD) method is used for the spatial discretization. Numerical examples are provided to demonstrate the efficiency of the proposed multiscale time splitting approach.
Nanoparticles have many applications in oil and gas exploration and production. For instance, some kinds of nanoparticles may be used as tracers for exploration of oil and gas and some others can be used in oilfields. When nanoparticles are absorbed on porous walls, the wettability of the reservoir rocks can be changed into the desired one. One kind of polysilicon nanopowder with the range of 10 - 500 nm was used in oilfields to enhance water injection by changing wettability of the porous medium . Ju et al.  conducted experiments and introduced a mathematical model for the nanoparticles transport in porous media. Their mathematical model has been suggested based on the model of the particle migration through porous media . El-Amin et al. [3-7] developed some models of transport of nanoparticles in a two-phase flow in porous media. The problem of nanoparticles transport in anisotropic porous media using the multipoint flux approximation was investigated by Salama et al. . Chen et al.  introduced a numerical simulation of drag reduction effects by hydrophobic nanoparticles adsorption method in water flooding processes. Chen et al.  introduced the dynamic update of anisotropic permeability field during the transport of nanoparticles in the subsurface.
Successful exploitation of shale reservoirs largely depends on the effectiveness of hydraulic fracturing stimulation program. Favorable results have been attributed to intersection and reactivation of pre-existing fractures by hydraulically-induced fractures that connect the wellbore to a larger fracture surface area within the reservoir rock volume. Thus, accurate estimation of the stimulated reservoir volume (SRV) becomes critical for the reservoir performance simulation and production analysis. Micro-seismic events (MS) have been commonly used as a proxy to map out the SRV geometry, which could be erroneous because not all MS events are related to hydraulic fracture propagation. The case studies discussed here utilized a fully 3-D simulation approach to estimate the SRV.
The simulation approach presented in this paper takes into account the real-time changes in the reservoir's geomechanics as a function of fluid pressures. It is consisted of four separate coupled modules: geomechanics, hydrodynamics, a geomechanical joint model for interfacial resolution, and an adaptive re-meshing. Reservoir stress condition, rock mechanical properties, and injected fluid pressure dictate how fracture elements could open or slide. Critical stress intensity factor was used as a fracture criterion governing the generation of new fractures or propagation of existing fractures and their directions. Our simulations were run on a Cray XC-40 HPC system.
The studies outcomes proved the approach of using MS data as a proxy for SRV to be significantly flawed. Many of the observed stimulated natural fractures are stress related and very few that are closer to the injection field are connected. The situation is worsened in a highly laminated shale reservoir as the hydraulic fracture propagation is significantly hampered. High contrast in the in-situ stresses related strike-slip developed thereby shortens the extent of SRV. However, far field nature fractures that were not connected to hydraulic fracture were observed being stimulated.
These results show the beginning of new understanding into the physical mechanisms responsible for greater disparity in stimulation results within the same shale reservoir and hence the SRV. Using the appropriate methodology, stimulation design can be controlled to optimize the responses of in-situ stresses and reservoir rock itself.
Hussain, Maaruf (Baker Hughes) | Saad, Bilal (Baker Hughes) | Negara, Ardiansyah (Baker Hughes) | Elgassier, Mokhtar (Baker Hughes) | Agrawal, Gaurav (Baker Hughes) | Sun, Shuyu (University of Science & Technology) | Abdullah, King (University of Science & Technology)
It is often reported that around 60% of hydraulic fracturing stages are ineffective. If so, it is likely that the design accuracy is limited by the current state of modeling and hydraulic fracture (HF) simulations. Our study presents a new alternative – a full 3-D simulation with geomechanics coupled to fluid flow. With the conventional simulation, it is extremely hard to model opening of weak lamination (Lam) and nearly impossible to generate induced horizontal fractures against the vertical overburden stress. However, horizontal fractures are routinely evident in shale reservoirs as healed fractures observed along the bedding planes. Hence, the need and importance of a true 3-D simulator that could incorporate complex geology and dynamically simulate fracture propagation by accounting for realtime changes in geomechanics and fluid pressures. Case study uses shale reservoirs, which are heavily laminated with complex natural fractures (NFs). Numerical simulations consisted of four separate coupled modules - geomechanics, hydrodynamics, a geomechanical joint model for interfacial resolution, and an adaptive remeshing module. Reservoir stress condition, rock mechanical properties, and injected fluid pressure dictate how fracture elements could open or slide. Critical stress intensity factor was used as a fracture criterion governing the generation of new fractures or propagation of existing fractures and their directions. Simulation was run on a Cray XC-40 HPC system. Typical laminated shale reservoirs anisotropic geomechanical properties obtained from literature were used to estimate a 3-D geomechanical model and NF network. HF geometry was significantly different in the presence of weak bedding, compared to when bedding was strong enough to transmit crack tip stresses across the interface. Significant amounts of fracturing fluid can be diverted into creation of horizontal fractures, even when the pressure was below the vertical stress, once bedding discontinuities are activated. Choices of NF network and Lam thickness significantly affected observed fracture propagation. The value of 3-D modeling was clearly established. This method provides more accurate solutions for stimulation design optimization, e.g., landing points, number of stages, number of clusters, spacing between stages, and stimulated reservoir volume.
Bao, Kai (King Abdullah University of Science and Technology) | Yan, Mi (IBM) | Allen, Rebecca (King Abdullah University of Science and Technology) | Salama, Amgad (King Abdullah University of Science and Technology) | Lu, Ligang (IBM) | Jordan, Kirk E. (IBM) | Sun, Shuyu (King Abdullah University of Science and Technology) | Keyes, David (King Abdullah University of Science and Technology)
The present work describes a parallel computational framework for carbon dioxide (CO2) sequestration simulation by coupling reservoir simulation and molecular dynamics (MD) on massively parallel high-performance-computing (HPC) systems. In this framework, a parallel reservoir simulator, reservoir-simulation toolbox (RST), solves the flow and transport equations that describe the subsurface flow behavior, whereas the MD simulations are performed to provide the required physical parameters. Technologies from several different fields are used to make this novel coupled system work efficiently.
One of the major applications of the framework is the modeling of large-scale CO2 sequestration for long-term storage in subsurface geological formations, such as depleted oil and gas reservoirs and deep saline aquifers, which has been proposed as one of the few attractive and practical solutions to reduce CO2 emissions and address the global-warming threat. Fine grids and accurate prediction of the properties of fluid mixtures under geological conditions are essential for accurate simulations. In this work, CO2 sequestration is presented as a first example for coupling reservoir simulation and MD, although the framework can be extended naturally to the full multiphase multicomponent compositional flow simulation to handle more complicated physical processes in the future.
Accuracy and scalability analysis are performed on an IBM BlueGene/P and on an IBM BlueGene/Q, the latest IBM supercomputer. Results show good accuracy of our MD simulations compared with published data, and good scalability is observed with the massively parallel HPC systems. The performance and capacity of the proposed framework are well-demonstrated with several experiments with hundreds of millions to one billion cells.
To the best of our knowledge, the present work represents the first attempt to couple reservoir simulation and molecular simulation for large-scale modeling. Because of the complexity of subsurface systems, fluid thermodynamic properties over a broad range of temperature, pressure, and composition under different geological conditions are required, although the experimental results are limited. Although equations of state can reproduce the existing experimental data within certain ranges of conditions, their extrapolation out of the experimental data range is still limited. The present framework will definitely provide better flexibility and predictability compared with conventional methods.
Katterbauer, Klemens (King Abdullah University of Science and Technology) | Hoteit, Ibrahim (King Abdullah University of Science and Technology) | Sun, Shuyu (King Abdullah University of Science and Technology)
Increasing complexity of hydrocarbon projects and the request for higher recovery rates have driven the oil-and-gas industry to look for a more-detailed understanding of the subsurface formation to optimize recovery of oil and profitability. Despite the significant successes of geophysical techniques in determining changes within the reservoir, the benefits from individually mapping the information are limited. Although seismic techniques have been the main approach for imaging the subsurface, the weak density contrast between water and oil has made electromagnetic (EM) technology an attractive complement to improve fluid distinction, especially for high-saline water. This crosswell technology assumes greater importance for obtaining higher-resolution images of the interwell regions to more accurately characterize the reservoir and track fluid-front developments. In this study, an ensemble-Kalman-based history-matching framework is proposed for directly incorporating crosswell time-lapse seismic and EM data into the history-matching process. The direct incorporation of the time-lapse seismic and EM data into the history-matching process exploits the complementarity of these data to enhance subsurface characterization, to incorporate interwell information, and to avoid biases that may be incurred from separate inversions of the geophysical data for attributes. An extensive analysis with 2D and realistic 3D reservoirs illustrates the robustness and enhanced forecastability of critical reservoir variables. The 2D reservoir provides a better understanding of the connection between fluid discrimination and enhanced history matches, and the 3D reservoir demonstrates its applicability to a realistic reservoir. History-matching enhancements (in terms of reduction in the history-matching error) when incorporating both seismic and EM data averaged approximately 50% for the 2D case, and approximately 30% for the 3D case, and permeability estimates were approximately 25% better compared with a standard history matching with only production data.
Saad, Bilal (Baker Hughes) | Negara, Ardiansyah (Baker Hughes) | Hussain, Maaruf (Baker Hughes) | Elgassier, Mokhtar (Baker Hughes) | Sun, Shuyu (University of Science and Technology) | Abdullah, King (University of Science and Technology)
Hydraulic fracture stimulation designs are typically made of multiple stages placed along the lateral section of the well using various well completion technologies. Understanding how multiple hydraulic fractures propagate and interact with each other is essential for an effective stimulation design. The number and placement of stages are important factors for optimizing the performance of the laterals. This in turn depends on accuracy in determining fracture interference. We present advanced simulations for accurate placement of well stages. In this paper, we use a 3-D fully coupled geomechanical-fluid flow simulator which incorporates anisotropic geomechanical properties. Densely complex natural fractures and lamination are built into the model based on available core and log information. Multiple fractures are concurrently imployed to simulate real life scenarios. Fluid pressures are incrementally computed such that stress state changes dynamically with time as it happens in real field situation. Our simulations were run on Cray XC 40 HPC system. The results demonstrate that the stress shadow effects can significantly alter hydraulic fracture propagation behavior, which eventually affects the final fracture geometry. The results show that there are large differences in aperture throughout the stimulation which persists to the end of pumping. Furthermore comparison between cases with and without complex natural fractures (discrete fracture network (DFN)) and lamination was conducted with even and uneven spacing configurations. Fracture interference and spacing analysis conducted based on model with perforation frictions shows that while spacing between fractures is important, the largest impact was observed in the presence of lamination and DFN. The large differences in the way the fracture propagates highly depend on the DFN connectivity. Late-stage connection throughout the model implies later disconnection when the pressure drops. Though the computations are time intensive, we believe this is a valuable tool to use in the planning stages for asset development to increase production potential.
Gas transport in extremely low-permeability shale formations is a multi-mechanisms-coupling process that includes gas adsorption-desorption, Knudsen diffusion, and slip flow. Incorporating these mechanisms into a unified mathematical model is crucial to obtain a more accurate shale gas production behavior. The objective of this paper is to investigate the effect of each mechanism on shale gas production behavior. We establish shale gas dual-porosity dual-permeability model that incorporates gas adsorption-desorption, Knudsen diffusion, and slip flow as well as the thermodynamics calculations. Peng-Robinson equation of state (PR-EOS) was used to calculate the gas density and compressibility factor by solving the cubic equation. In our model, gas adsorption-desorption obeys the Langmuir's isotherm as a function of reservoir pressure. Furthermore, gas viscosity changes with Knudsen number during the pressure depletion; and pore radius will increase when the adsorption gas desorbs from the pore wall. In the numerical method implementation, we combine the finite volume method with the experimenting pressure field approach to obtain the pressure distribution in the matrix and fracture systems. In this study, we investigate the effects of adsorption, Knudsen diffusion, and gas-slippage (Klinkenberg effect) on shale production behavior. We switch each mechanism on and off in the model to observe its effect on the production performance. It is observed from the results that among these mechanisms, adsorption has a great influence on gas production. Ignoring adsorbed gas would lead to a lower cumulative production. Meanwhile, the effects of Knudsen diffusion and slip flow are not as significant as adsorption. In particular for the example presented in this paper, neglecting adsorption will decrease the production nearly 80% compared to 15%-18% when Knudsen diffusion and slip flow are ignored. Knudsen diffusion and slip flow have less impact on the production because both mechanisms occurs in the matrix and contribute only to the apparent permeability, while the production is mainly determined by the fracture permeability, which is critical in determining fluid flow from the fracture system to the wellbore.
Negara, Ardiansyah (Baker Hughes) | Salama, Amgad (King Abdullah University of Science and Technology) | Sun, Shuyu (King Abdullah University of Science and Technology) | Elgassier, Mokhtar (Baker Hughes) | Wu, Yu-Shu (Colorado School of Mines)
Shale gas resources have received great attention in the last decade due to the decline of the conventional gas resources. Unlike conventional gas reservoirs, the gas flow in shale formations involves complex processes with many mechanisms such as Knudsen diffusion, slip flow (Klinkenberg effect), gas adsorption and desorption, strong rock-fluid interaction, etc. Shale formations are characterized by the tiny porosity and extremely low-permeability such that the Darcy equation may no longer be valid. Therefore, the Darcy equation needs to be revised through the permeability factor by introducing the apparent permeability. With respect to the rock formations, several studies have shown the existence of anisotropy in shale reservoirs, which is an essential feature that has been established as a consequence of the different geological processes over long period of time. Anisotropy of hydraulic properties of subsurface rock formations plays a significant role in dictating the direction of fluid flow. The direction of fluid flow is not only dependent on the direction of pressure gradient, but it also depends on the principal directions of anisotropy. Therefore, it is very important to take into consideration anisotropy when modeling gas flow in shale reservoirs. In this work, the gas flow mechanisms as mentioned earlier together with anisotropy are incorporated into the dual-porosity dual-permeability model through the full-tensor apparent permeability. We employ the multipoint flux approximation (MPFA) method to handle the full-tensor apparent permeability. We combine MPFA method with the experimenting pressure field approach, i.e., a newly developed technique that enables us to solve the global problem by breaking it into a multitude of local problems. This approach generates a set of predefined pressure fields in the solution domain in such a way that the undetermined coefficients are calculated from these pressure fields. In other words, the matrix of coefficients is constructed automatically within the solver. We ran a numerical model with different scenarios of anisotropy orientations and compared the results with the isotropic model in order to show the differences between them. We investigated the effect of anisotropy in both the matrix and fracture systems. The numerical results show anisotropy plays a crucial role in dictating the pressure fields as well as the gas flow streamlines. Furthermore, the numerical results clearly show the effects of anisotropy on the production rate and cumulative production. Incorporating anisotropy together with gas flow mechanisms in shale formations into the reservoir model is essential particularly for predicting maximum gas production from shale reservoirs.
Katterbauer, Klemens (King Abdullah University of Science and Technology) | Hoteit, Ibrahim (King Abdullah University of Science and Technology) | Sun, Shuyu (King Abdullah University of Science and Technology)
Electromagnetic (EM) heating is becoming a popular method for heavy-oil recovery because of its cost-efficiency and continuous technological improvements. It exploits the relationship that the viscosity of hydrocarbons decreases for increasing temperature; the heavy-oil components become more fluid-like, and hence easier to extract from the reservoir. Although several field studies have considered the effects of heating on the viscosity of the hydrocarbons, there has been very little research on the long-term effects of field production and the forecasting of the development of the reservoir. Increased flow rates within the reservoir render the moving fluids less viscous, implying fast-changing fluid-propagation patterns and increased uncertainty about the state of the oil displacement. This means, in the long term, strongly varying production projections, strong dependence on the permeability of the reservoir, and potentially undesirable fluid migration. To improve the forecasting of production in heavy-oil fields and to accurately capture the dynamics of the fluid movements, we present a history-matching framework incorporating well data and seismic and EM crosswell-imaging techniques. The incorporation of seismic and EM data into the history-matching process counteracts the changing reservoir dynamics caused by increased fluid velocity caused by heating and is shown to significantly improve reservoir matching and forecasts for a variety of different heating scenarios.