Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Reservoir modeling consists of two key components: the reproduction of the historical performance and the prediction of the future reservoir performance. Industry-standard reservoir simulators must run fast on enormous and possibly unstructured grids while yet guaranteeing a reasonable representation of physical and chemical processes. However, computational demands limit simulators in capturing involved physical and geochemical mechanisms, especially when chemical reactions interfere with reservoir flow. This paper presents a mathematical workflow, implemented in IORSim, that makes it possible to add geochemical calculations to porous media flow simulators without access to the source code of the original host simulator. An industry-standard reservoir simulator calculates velocity fields of the fluid phases (e.g., water, oil, and gas), while IORSim calculates the transport and reaction of geochemical components. Depending on the simulation mode, the geochemical solver estimates updated relative and/or capillary pressure curves to modify the global fluid flow. As one of the key innovations of the coupling mechanism, IORSim uses a sorting algorithm to permute the grid cells along flow directions. Instead of solving an over-dimensionalized global matrix calling a Newton–Raphson solver, the geochemical software tool treats the species balance as a set of local nonlinear problems. Moreover, IORSim applies basis swapping and splay tree techniques to accelerate geochemical computations in complex full-field reservoir models. The presented work introduces the mathematical IORSim concept, verifies the chemical species advection, and demonstrates the IORSim computation efficiency. After validating the geochemical solver against reference software, IORSim is used to investigate the impact of seawater injection on the NCS Ekofisk reservoir chemistry. Article Highlights The IORSim sorting algorithm decouples the nonlinear geochemical reaction calculations into recurring one-dimensional problems to assure numerical stability and computation efficiency. To the best of our knowledge, this work presents the mathematical concept, implementation, and application of topological sorting for the first time on (industry) field-scale problems. IORSim combines topological sorting with basis swapping and splay trees to significantly reduce computation times. Moreover, a high-speed forward simulation mode was developed to allow the post-advection of chemical components to visualize species distribution, water chemistry, and mineral interactions. If the geochemical reactions interfere with the fluid flow, the IORSim backward mode uses relative permeability curves to update the global fluid flow at each time step. We validate the implemented topological scheme on a reservoir grid, show the computation efficiency, and compare the impact of explicit, implicit, and grid refinement on numerical dispersion. The decoupled flow simulator and geochemical reaction calculations allow seamless integration of full-field reservoir models that contain complex geological structures, a large number of wells, and long production histories. The computation capabilities of IORSim are demonstrated by simulating and reproducing the impact of seawater injection in the southern segment of the giant Ekofisk field (more than 50 years of injection and production history). IORSim shows that seawater injection changed the Ekofisk mineralogy and impacted the produced water chemistry. In the investigated Ekofisk case, seawater promoted calcite dissolution and led to the precipitation of magnesite and anhydrite. Moreover, surface complexation modeling revealed that sulfate is adsorbed on the calcite surface.
Reservoir modeling consists of two key components: the reproduction of the historical performance and the prediction of the future reservoir performance. Industry-standard reservoir simulators must run fast on enormous and possibly unstructured grids while yet guaranteeing a reasonable representation of physical and chemical processes. However, computational demands limit simulators in capturing involved physical and geochemical mechanisms, especially when chemical reactions interfere with reservoir flow. This paper presents a mathematical workflow, implemented in IORSim, that makes it possible to add geochemical calculations to porous media flow simulators without access to the source code of the original host simulator. An industry-standard reservoir simulator calculates velocity fields of the fluid phases (e.g., water, oil, and gas), while IORSim calculates the transport and reaction of geochemical components. Depending on the simulation mode, the geochemical solver estimates updated relative and/or capillary pressure curves to modify the global fluid flow. As one of the key innovations of the coupling mechanism, IORSim uses a sorting algorithm to permute the grid cells along flow directions. Instead of solving an over-dimensionalized global matrix calling a Newton–Raphson solver, the geochemical software tool treats the species balance as a set of local nonlinear problems. Moreover, IORSim applies basis swapping and splay tree techniques to accelerate geochemical computations in complex full-field reservoir models. The presented work introduces the mathematical IORSim concept, verifies the chemical species advection, and demonstrates the IORSim computation efficiency. After validating the geochemical solver against reference software, IORSim is used to investigate the impact of seawater injection on the NCS Ekofisk reservoir chemistry. Article Highlights The IORSim sorting algorithm decouples the nonlinear geochemical reaction calculations into recurring one-dimensional problems to assure numerical stability and computation efficiency. To the best of our knowledge, this work presents the mathematical concept, implementation, and application of topological sorting for the first time on (industry) field-scale problems. IORSim combines topological sorting with basis swapping and splay trees to significantly reduce computation times. Moreover, a high-speed forward simulation mode was developed to allow the post-advection of chemical components to visualize species distribution, water chemistry, and mineral interactions. If the geochemical reactions interfere with the fluid flow, the IORSim backward mode uses relative permeability curves to update the global fluid flow at each time step. We validate the implemented topological scheme on a reservoir grid, show the computation efficiency, and compare the impact of explicit, implicit, and grid refinement on numerical dispersion. The decoupled flow simulator and geochemical reaction calculations allow seamless integration of full-field reservoir models that contain complex geological structures, a large number of wells, and long production histories. The computation capabilities of IORSim are demonstrated by simulating and reproducing the impact of seawater injection in the southern segment of the giant Ekofisk field (more than 50 years of injection and production history). IORSim shows that seawater injection changed the Ekofisk mineralogy and impacted the produced water chemistry. In the investigated Ekofisk case, seawater promoted calcite dissolution and led to the precipitation of magnesite and anhydrite. Moreover, surface complexation modeling revealed that sulfate is adsorbed on the calcite surface.
To study the ore mineralization at the outcrop scale we merge an advection–diffusion simulation with the geochemical software iphreeqc to model the mixing of two realistic fluids. We simulate the infiltration of a metal-rich fluid into a rock that is saturated with pore fluid. We test the feedback effects with a number of scenarios based on an outcrop-scale 5 × 5 m model consisting of two high-permeable vertical faults within a low-permeable host rock that lead into a permeable layer. The hot metal-rich fluid enters the model through the faults from below. We solve the advection–diffusion equation for 12 chemical species and temperature, and use iphreeqc to determine the resulting properties of local fluid domains as well as related saturation indices for minerals. The faults in the model act as pathways for the metal-rich fluid, with the infiltrating fluid displacing the pore fluid. Mixing in the model takes place as a function of advection along permeable faults coupled with diffusion of chemical species at the interface between two fluids, while heat diffusion is fast enough (103 times faster) to equilibrate temperature. Simulations show a high saturation index of mixing-derived minerals such as barite at the interface between the two fluids as a result of fluid mixing. Fast fluid pathways (i.e. faults) show travelling waves of high saturation indices of barite, while low-permeability zones such as fault walls and areas below less permeable layers experience stationary waves of high saturation indices. Our results show that, depending on the dominant transport process (advection or diffusion), mineralization will localize next to permeability contrasts in zones where local diffusion dominates.
Abstract. Reactive transport processes in natural environments often involve many ionic species. The diffusivities of ionic species vary. Since assigning different diffusivities in the advection–diffusion equation leads to charge imbalance, a single diffusivity is usually used for all species. In this work, we apply the Nernst–Planck equation, which resolves unequal diffusivities of the species in an electroneutral manner, to model reactive transport. To demonstrate the advantages of the Nernst–Planck model, we compare the simulation results of transport under reaction-driven flow conditions using the Nernst–Planck model with those of the commonly used single-diffusivity model. All simulations are also compared to well-defined experiments on the scale of centimeters. Our results show that the Nernst–Planck model is valid and particularly relevant for modeling reactive transport processes with an intricate interplay among diffusion, reaction, electromigration, and density-driven convection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.