Holger Class

Numerical simulation of non-isothermal multiphase multicomponent processes in porous media. 1. An efficient solution technique

Modeling non-isothermal multiphase multicomponent flow and transport processes in the subsurface requires the consideration of the transfer of mass and energy between the phases in addition to the flow processes such as advection and diffusion. We developed a multidimensional numerical simulator, in which we implemented new efficient solution techniques. The description of the physical and thermodynamical state yields a system of four strongly coupled partial differential equations. The set of phases (phase state) present in the porous medium is variable in space and time. In order to take this into account, we implemented an algorithm that allows an adaptive switching of the primary variables according to each phase state. We apply a Newton algorithm for the linearization of the equations. For the solution of the arising linear equations, we extended a multigrid method and adapted it to the problem of variable phase states. First results of this new solution technique are given in the paper.

Hydraulic fracturing in unconventional gas reservoirs: risks in the geological system part 1

Hydraulic fracturing is a method used for the production of unconventional gas resources. Huge amounts of so-called fracturing fluid (10,000–20,000 m3) are injected into a gas reservoir to create fractures in solid rock formations, upon which mobilised methane fills the pore space and the fracturing fluid is withdrawn. Hydraulic fracturing may pose a threat to groundwater resources if fracturing fluid or brine can migrate through fault zones into shallow aquifers. Diffuse methane emissions from the gas reservoir may not only contaminate shallow groundwater aquifers, but also escape into the atmosphere where methane acts as a greenhouse gas. The working group “Risks in the Geological System” as part of ExxonMobil’s hydrofracking dialogue and information dissemination processes was tasked with the assessment of possible hazards posed by migrating fluids as a result of hydraulic fracturing activities. In this work, several flow paths for fracturing fluid, brine and methane are identified and scenarios are set up to qualitatively estimate under what circumstances these fluids would leak into shallower layers. The parametrisation for potential hydraulic fracturing sites in North Rhine-Westphalia and Lower Saxony (both in Germany) is derived from literature using upper and lower bounds of hydraulic parameters. The results show that a significant fluid migration is only possible if a combination of several conservative assumptions is met by a scenario.

Modeling, parameterization and evaluation of monitoring methods for CO2 storage in deep saline formations: the CO2-MoPa project

Capture and geological sequestration of CO2 from large industrial sources is considered a measure for reducing anthropogenic emissions of CO2 and thus mitigating climate change. One of the main storage options proposed are deep saline formations, as they provide the largest potential storage capacities among the geologic options. A thorough assessment of this type of storage site therefore is required. The CO2-MoPa project aims at contributing to the dimensioning of CO2 storage projects and to evaluating monitoring methods for CO2 injection by an integrated approach. For this, virtual, but realistic test sites are designed geometrically and fully parameterized. Numerical process models are developed and then used to simulate the effects of a CO2 injection into the virtual test sites. Because the parameterization of the virtual sites is known completely, investigation as well as monitoring methods can be closely examined and evaluated by comparing the virtual monitoring result with the simulation. To this end, the monitoring or investigation method is also simulated, and the (virtual) measurements are recorded and evaluated like real data. Application to a synthetic site typical for the north German basin showed that pressure response has to be evaluated taking into account the layered structure of the storage system. Microgravimetric measurements are found to be promising for detecting the CO2 phase distribution. A combination of seismic and geoelectric measurements can be used to constrain the CO2 phase distribution for the anticline system used in the synthetic site.

Multiphase Processes in Porous Media

Models for multiphase flow in porous media are widespread today and can be found in many places in science and engineering. More complex multiphase-multicomponent models that even allow phase changes to occur need sophisticated numerical algorithms. Research in this area has been very successful with a versatile result.

Numerical simulation of non-isothermal multiphase multicomponent processes in porous media.: 2. Applications for the injection of steam and air

In part 1 [Class et al., this issue], we presented a numerical simulator for non-isothermal multiphase systems. A module of this simulator that considers the phases water, an organic non-aqueous-phase liquid (NAPL), and the gas phase is used here for two applications. The aim of the numerical simulations is to show and to interpret the behavior of the non-isothermal multiphase processes. The first example deals with an experiment in which an air-dry, NAPL-contaminated column is remediated by a steam injection. The typical front behavior is investigated and the coupled physical processes are identified by a comparison with experimental temperature data. The second application is a two-dimensional case study, where the influence of different strategies for the remediation by injection of steam and/or air in a heterogeneous, NAPL-contaminated sand can be shown.

Anthropogenic Trace Compounds (ATCs) in aquatic habitats - research needs on sources, fate, detection and toxicity to ensure timely elimination strategies and risk management.

Anthropogenic Trace Compounds (ATCs) that continuously grow in numbers and concentrations are an emerging issue for water quality in both natural and technical environments. The complex web of exposure pathways as well as the variety in the chemical structure and potency of ATCs represents immense challenges for future research and policy initiatives. This review summarizes current trends and identifies knowledge gaps in innovative, effective monitoring and management strategies while addressing the research questions concerning ATC occurrence, fate, detection and toxicity. We highlight the progressing sensitivity of chemical analytics and the challenges in harmonization of sampling protocols and methods, as well as the need for ATC indicator substances to enable cross-national valid monitoring routine. Secondly, the status quo in ecotoxicology is described to advocate for a better implementation of long-term tests, to address toxicity on community and environmental as well as on human-health levels, and to adapt various test levels and endpoints. Moreover, we discuss potential sources of ATCs and the current removal efficiency of wastewater treatment plants (WWTPs) to indicate the most effective places and elimination strategies. Knowledge gaps in transport and/or detainment of ATCs through their passage in surface waters and groundwaters are further emphasized in relation to their physico-chemical properties, abiotic conditions and biological interactions in order to highlight fundamental research needs. Finally, we demonstrate the importance and remaining challenges of an appropriate ATC risk assessment since this will greatly assist in identifying the most urgent calls for action, in selecting the most promising measures, and in evaluating the success of implemented management strategies.

Bayesian updating via bootstrap filtering combined with data-driven polynomial chaos expansions: methodology and application to history matching for carbon dioxide storage in geological formations

Model calibration and history matching are important techniques to adapt simulation tools to real-world systems. When prediction uncertainty needs to be quantified, one has to use the respective statistical counterparts, e.g., Bayesian updating of model parameters and data assimilation. For complex and large-scale systems, however, even single forward deterministic simulations may require parallel high-performance computing. This often makes accurate brute-force and nonlinear statistical approaches infeasible. We propose an advanced framework for parameter inference or history matching based on the arbitrary polynomial chaos expansion (aPC) and strict Bayesian principles. Our framework consists of two main steps. In step 1, the original model is projected onto a mathematically optimal response surface via the aPC technique. The resulting response surface can be viewed as a reduced (surrogate) model. It captures the model’s dependence on all parameters relevant for history matching at high-order accuracy. Step 2 consists of matching the reduced model from step 1 to observation data via bootstrap filtering. Bootstrap filtering is a fully nonlinear and Bayesian statistical approach to the inverse problem in history matching. It allows to quantify post-calibration parameter and prediction uncertainty and is more accurate than ensemble Kalman filtering or linearized methods. Through this combination, we obtain a statistical method for history matching that is accurate, yet has a computational speed that is more than sufficient to be developed towards real-time application. We motivate and demonstrate our method on the problem of CO2 storage in geological formations, using a low-parametric homogeneous 3D benchmark problem. In a synthetic case study, we update the parameters of a CO2/brine multiphase model on monitored pressure data during CO2 injection.

The regional pressure impact of CO2 storage: a showcase study from the North German Basin

A regional scale, showcase saline aquifer CO2 storage model from the North German Basin is presented, predicting the regional pressure impact of a small industrial scale CO2 storage operation on its surroundings. The intention of the model is to bridge the gap between generic and site-specific, studying the role of fluid flow boundary conditions and petrophysical parameters typically found in the North German Basin. The numerical simulation has been carried out using two different numerical simulators, whose results matched well. The most important system parameters proved to be the model’s hydrological boundary conditions, rock compressibility, and permeability. In open boundary aquifers, injection-induced overpressures dissipate back to hydrostatic level within a few years. If a geological flow barrier is present on at least one side of the aquifer, pressure dissipation is seriously retarded. In fully closed compartments, overpressures can never fully dissipate, but equilibrate to a compartment-wide remnant overpressure. At greater distances to the injection well, maximum fluid pressures are in the range of a few bar only, and reached several years to decades after the end of the actual injection period. This is important in terms of long-term safety and monitoring considerations. Regional pressure increase impacts the storage capacities of neighbouring sites within hydraulically connected units. It can be concluded that storage capacities may be seriously over- or underestimated when the focus is on a single individual storage site. It is thus necessary to assess the joint storage capacities and pressure limitations of potential sites within the same hydraulic unit.

Estimation of effective parameters for a two-phase flow problem in non-Gaussian heterogeneous porous media

In this paper we discuss estimates of effective parameters for an upscaled model for buoyant counter flow of DNAPL and water in a closed box filled with heterogeneous porous material. The upscaling procedure is based on the assumption that the flow is dominated by capillary forces on the small scale and that the fluids are segregated. The upscaled model has the same form as the usual two-phase flow model with an effective capillary pressure function and an effective mobility function Λ. Effective parameters are then estimated in two different ways. Stochastic theory can be applied to calculate the effective parameters to first order in the parameter fluctuations. This approach does not take into account that different parameter ranges of the heterogeneous field may be connected or isolated, yielding very different macroscopic residual saturations. Therefore, the second estimate of effective parameters takes connectivity of parameter ranges into account. In this case, the univariate parameter distribution of the heterogeneous field and the values that mark connected materials are the only information about heterogeneity that is used. Effective parameters are then estimated using mean field theory (the Maxwell approach). The upscaled model and the estimation of effective parameters are applied to a numerical test case. Buoyant counter flow in heterogeneous parameter fields with different structures is simulated numerically and compared to the solutions of the quasi-1d upscaled model with differently estimated parameters. It is demonstrated that connectivity of the different parameter ranges is an important information that determines typical time scales for the flow process and the macroscopic residual saturation. Even simple estimates of effective parameters based on little information may capture the typical time scales, provided that information about connected parameter ranges is taken into account.

A revised model for microbially induced calcite precipitation: Improvements and new insights based on recent experiments

The model for microbially induced calcite precipitation (MICP) published by Ebigbo et al. (2012) has been improved based on new insights obtained from experiments and model calibration. The challenge in constructing a predictive model for permeability reduction in the underground with MICP is the quantification of the complex interaction between flow, transport, biofilm growth, and reaction kinetics. New data from Lauchnor et al. (2015) on whole-cell ureolysis kinetics from batch experiments were incorporated into the model, which has allowed for a more precise quantification of the relevant parameters as well as a simplification of the reaction kinetics in the equations of the model. Further, the model has been calibrated objectively by inverse modeling using quasi-1D column experiments and a radial flow experiment. From the postprocessing of the inverse modeling, a comprehensive sensitivity analysis has been performed with focus on the model input parameters that were fitted in the course of the model calibration. It reveals that calcite precipitation and concentrations of NH4+ and Ca2+ are particularly sensitive to parameters associated with the ureolysis rate and the attachment behavior of biomass. Based on the determined sensitivities and the ranges of values for the estimated parameters in the inversion, it is possible to identify focal areas where further research can have a high impact toward improving the understanding and engineering of MICP.