IORSim - A Simulator for Fast and Accurate Simulation of Multi-phase Geochemical Interactions at the Field Scale

Hiorth, A.; Sagen, Jan; Lohne, Arild; Nossen, Jan; Vinningland, Jan Ludvig; Jettestuen, Espen; Sira, Terje

doi:10.3997/2214-4609.201601882

Cited by 3 publications

(3 citation statements)

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“…For further details of the implementation the reader is referred to Trujillo et al (2018). Trujillo et al (2018) adapted and validated the Hiorth et al (2016) porosity-permeability model and the 4-component silica gelation reaction suggested by Icopini et al (2005) for in-depth divergence simulation. These models were implemented in the Automatic Differentiation General Purpose Research Simulator (AG-GPRS) developed at Stanford University (Voskov and Tchelepi, 2012;Zaydullin et al, 2014;Garipov et al, 2018).…”

Section: In-depth Water Diversion Simulationmentioning

confidence: 99%

“…where N solids is the amount of moles of solids deposited, M v solid is the molecular volume of the solid, V cell the cell volume, and C rock the fraction of rock. Finally, the Hiorth et al (2016) 5) approximates permeability as function of initial permeability k 0 and porosity ϕ 0 , the mass fraction of deposited silica over water Y and the water saturation S w ,…”

Section: In-depth Water Diversion Simulationmentioning

confidence: 99%

“…Combined with these pilots, experimental laboratory work has given insight on activation conditions, core-scale behaviour, and chemistry of the poorly understood polymerization process (Icopini et al (2005); Stavland et al (2011)). Several numerical simulation studies, based on a weak coupling of a reservoir flow modeling and a separate software module for chemical reactions, have been able to replicate the main characteristics of the observed behaviour (Hiorth et al (2016); Skrettingland et al (2014)). Since the development of silicate gels and the accompanying permeability reduction is essentially a coupled process, Trujillo et al (2018) recently proposed a fully implicit coupled chemical-compositionalflow implementation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimization Of In-Depth Water Diversion Using A Fully Implicit Thermal-Compositional Approach

Sangers¹,

Romano-Trujillo²,

Voskov³

et al. 2018

Proceedings

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We investigate the potential for improved recovery of subsurface energy resources (hydrocarbons or heat) through in-depth diversion technology. A number of pilot studies in the North Sea have demonstrated in recent years that sodium silicate can be used to block preferential flow paths and divert water to previously unswept areas of a reservoir. Accompanying simulation studies based on an explicit weak coupling of a reservoir flow simulator and an external chemical module have attempted to replicate the observed behaviour. Since the development of silicate gels and the accompanying permeability reduction is essentially a coupled flowchemical process, we first will present a fully implicit compositional-reactive flow and transport implementation and investigate the impact of the grid and time-stepping resolution on simulation performance in 2D subsurface reservoirs mimicking petroleum and geothermal applications. We proceed to investigate the sensitivity of the recovery to design parameters of the in-depth diversion strategy. Since adjoint gradients are not typically available for these parameters and uncertainties associated with an application of in-depth divergence are large, we use an ensemble-based methodology to perform an optimization study. This study aims to find optimal strategies for combined waterflooding and design of in-depth diversion under geological uncertainty. It is demonstrated that in-depth diversion can significantly extend the life-time of hydrocarbon or geothermal fields when the timing of injection and the size of the sodium silicate batch is optimized. Finally, we discuss methods that help to address an issue of computational cost associated with the high resolution required for accurate simulation of the coupled process.

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Section: In-depth Water Diversion Simulationmentioning

confidence: 99%

Section: In-depth Water Diversion Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimization Of In-Depth Water Diversion Using A Fully Implicit Thermal-Compositional Approach

Sangers¹,

Romano-Trujillo²,

Voskov³

et al. 2018

Proceedings

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IORSim: A Mathematical Workflow for Field-Scale Geochemistry Simulations in Porous Media

Feldmann,

Nødland,

Sagen

et al. 2024

Transp Porous Med

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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.

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Porosity Evolution during Chemo-Mechanical Compaction

Nermoen¹

2018

Porosity - Process, Technologies and Applications

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This chapter presents the constitutive equations necessary to interpret laboratory and field data when both solid and pore volume evolve through time due to chemical and mechanical processes. The equations for the porosity evolution that are developed are generic, but the examples presented are acquired from chalk core studies. The processes at play when porosity is subject to change due to volumetric compaction and fluid-rock interactions when porous chalks are continuously flooded are presented here. As the overall solid mass is a conserved quantity, the void space is not. Constitutive equations are therefore required to estimate the time-evolution of the porosity. Laboratory triaxial tests were performed on highporosity outcrop chalks from Obourg, Liegè, and Mons (Belgium). These tests are being compacted and continuously flooded with MgCl 2 brine at elevated temperature and at high stresses. As calcite is replaced by magnesite, the overall mass and solid density change, thereby changing the volume of the solid. At the same time, the bulk volume is changing. Taking both effects into consideration, the pore volume evolution can be determined. We find that the porosity changes in nonintuitive ways as the relative importance of bulk compaction and chemical interaction may vary over time.

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IORSim - A Simulator for Fast and Accurate Simulation of Multi-phase Geochemical Interactions at the Field Scale

Cited by 3 publications

References 0 publications

Optimization Of In-Depth Water Diversion Using A Fully Implicit Thermal-Compositional Approach

Optimization Of In-Depth Water Diversion Using A Fully Implicit Thermal-Compositional Approach

IORSim: A Mathematical Workflow for Field-Scale Geochemistry Simulations in Porous Media

Porosity Evolution during Chemo-Mechanical Compaction

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