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We use simplified methods to investigate how uncertainty in geological models affects practical CO 2 storage capacities in large-scale saline aquifers. Our focus is on uncertainties in top-surface elevation, rock properties (porosity, permeability), fault transmissibility, and aquifer conditions (pressure and temperature). To quantify the statistical characteristics of static trapping capacity and dynamic estimates of plume migration, we create hundreds of possible realizations of the geomodel by applying Gaussian-type perturbations to the spatially correlated properties. Two different simplified methods are introduced to reduce the computational cost of simulating migration over thousands of years in all the model realizations, which each spans hundreds of kilometers. First, we use vertical-equilibrium (VE) modelling, which is orders of magnitude faster than solving the 3D flow equations. Second, we introduce a fast look-ahead algorithm that enables us to exit the VE simulation once a pseudo-steady state is reached. This algorithm uses a spill-point analysis of the top-surface's trapping structure to forecast how much CO 2 will eventually become trapped and how much will leak through open boundaries of the formation. This reduces the computational cost significantly, since we seldom need to simulate long-term migration past a few hundred or thousand years. [ABSTRACT FROM AUTHOR]

Temperature is a key variable for the modeling of geological CO 2 storage, and any simulation model must take it explicitly or implicitly into account. At the large spatial scales and low flow rates associated with CO 2 migration studies, temperature can be reasonably considered as an constant and imposed external field, with CO 2 and brine assumed to be in thermal equilibrium with the surrounding rock. Closer to an injection well, the picture is different. CO 2 may be injected at a temperature significantly different from that of the aquifer, leading to an expanding thermal front around the injection well. The local change in temperature not only affects fluid properties, but also geomechanical stresses and the rate of geochemical reactions. In this article, we examine whether certain simplified approaches used to simulate CO 2 storage at the large scale may be adapted and applied to model the regions affected by the thermal front. We do this by comparing the results from upscaled (vertically integrated) flow models extended with heat transport and different choices of overburden representations against highly resolved 3D models. The considered test cases have been constructed to minimize or maximize specific characteristics of the coupled flow-thermal system: the Peclet number, the gravity number and the amount of thermal bleed. Our results suggest that for several practical cases the thermal front can be reasonably well modeled using a vertically integrated flow model with constant vertical temperature. The results also suggest that a simplified overburden representation may give a reasonable approximation, particularly for scenarios with low thermal bleed. We point out that the impact of a simplified overburden representation can be very similar to the use of linear heat transfer coefficients. On the other hand, while models that completely neglect thermal bleed may perform acceptably in some low-bleed settings, they often lead to very large errors. [ABSTRACT FROM AUTHOR]

The process of selecting a CO 2 storage site involves evaluating many potentially suitable sites in terms of their storage potentials as well as their associated technical and economic limitations. As such, it is useful to apply a ranking scheme that makes use of several different criteria and weights each criterion based on its relative importance in the overall evaluation. In this study, we demonstrate one such possible ranking workflow using real formation datasets from CO 2 Storage Atlas of the Norwegian Continental Shelf. The workflow involves computing practical storage potentials using a generic well placement scheme, mathematical optimization and vertical-equilibrium modeling, and is general in the sense that it can be applied to other formation datasets. Economic factors related to the transportation and injection of CO 2 are represented by the number of injection wells required, depth of injection, and distance from a CO 2 point source. The purpose of this study is not to provide formation-specific capacity estimates or efficiency factors for engineering purposes, due to the simplifying assumptions used in this work, and the fact that our specific datasets come with their own limitations (i.e., homogeneous rock properties, lack of fault data). Rather, the purpose is to demonstrate a general ranking scheme that reflects operational limitations and the economic factors likely to be involved in any commercial or demonstration CCUS project. [ABSTRACT FROM AUTHOR]

In the present study, we use data published alongside the Norwegian Petroleum Directorate (NPD) storage atlases to further investigate the storage capacity of 23 formations found in the Norwegian Continental Shelf. Our goal is to categorize the formations according to the main limiting factors for long-term geologic storage of CO2. We conduct the study by defining reasonable injection scenarios and running simulations on grids constructed from the NPD data, which also include the associated averaged rock properties. The use of vertical-equilibrium models allows us to rapidly run a large number of long-term simulations of injection and migration scenarios. The ability to run rapid simulations allows us to optimize injection rates using an adjoint-based nonlinear optimization algorithm. For a given number of wells and set of boundary conditions, we aim to optimize the amount of CO2 injected, subject to limits on long-term leakage and maximum allowed pressures. The outcome allows us to determine whether an aquifer is restricted mainly by long-time leakage across open boundaries, or global pressure buildup. We also provide figures for how much CO2 can be injected before the limitation is reached, subject to the working assumptions and demonstrate how changing these assumptions may influence the result. In particular, the assumed injection time and cost of leakage is discussed. We emphasize that through this study we wish to demonstrate a practical approach to the estimation of realizable storage capacity and illustrate how site-specific operational limitations influence the exploitable storage volume as compared with the initial storage estimates provided by NPD. As the study is based on large-scale averaged data under several simplifying assumptions, the realized storage capacity for each formation may well change if more detailed information, in particular on heterogeneity or more complex fluid-rock interactions, were to be taken into account. However, the use of simplified models to identify realizable storage capacity on the large scale allows us to quickly identify which formations may be best suited for a particular injection scenario. [ABSTRACT FROM AUTHOR]

A key part of planning CO 2 storage sites is to devise a monitoring strategy with proper modelling support. Herein, we show how a simulation framework that incorporates adjoint-based sensitivities can be combined with time-lapse seismics to update forecast models of the migrating plume, investigate the measurability of model parameters, and assess the effect of acquiring new measurements (value of information). In particular, we show how the sensitivities in measured quantities with respect to parameters can guide the choice of whether additional data should be obtained or not. To this end, we us singular value decomposition to find determine the model parameters that are best constrained with respect to the measured data, or, viewed alternatively, the parameters that has the largest influence on the mismatch between measured and simulated quantities. Other measurements like uplift data and gravitational data can also be used in our inversion algorithm. We apply the methodology to the Sleipner benchmark model. A large number of researchers have used plume data to better understand the flow physics and challenge assumptions made previously regarding the model properties. In particular, the parameters for the flow model are uncertain and have been topic of discussion in the literature. Using a vertical-equilibrium simulator, we show that Darcy flow adequately describes the physics of the CO 2 injection and migration. Adjoint-based sensitivities are used to efficiently minimize the mismatch between observations and simulations in an optimization loop giving plausible changes in topography, permeability, CO 2 density, porosity, and injection rates. However, since the minimization of the misfit is not unique, we investigate the Hessian of the misfit function for a reduced set of parameters. By considering the eigenvalue decomposition of this Hessian, we are able to identify its (approximate) null space, i.e., the combinations of parameter perturbations that do not affect plume migration. Similarly, by considering the complementary subspace, we identify the reduced set of parameter combinations that are sufficient to obtain a match. As a result, we obtain a parametrized family of (locally) optimal solutions to the minimization problem, i.e., a family of models that all match the observed data. We also investigate the effect of observation frequency on our model matching methodology, and conclude that for the model considered, frequent seismic measurements are not required to obtain adequate matched models however it give more accurate estimates of the top surface. [ABSTRACT FROM AUTHOR]

Environmental monitoring requires cost-effective and efficient methods for detecting potential effects of pollution, and valve gape behaviour has been used with this purpose for a range of contaminants in freshwater and marine bivalves. The current study investigated the use of a new method for measuring valve behaviour responses in mussels ( Mytilus edulis ) exposed to dispersed crude oil (DCO). Results confirmed that valve gape is a sensitive parameter; at the high DCO concentration (0.25 mg L − 1 ) the mean valve gape was reduced from 49 to 31%, and mussels increased shell movement (measured as distance travelled) or spent more time closed to avoid contact with the oil. At the low DCO concentration (0.015 mg L − 1 ) the distance travelled parameter was the most sensitive endpoint. Results also demonstrated that valve gape behaviour is a valid endpoint when monitoring mussels for exposure to DCO. [ABSTRACT FROM AUTHOR]

Planning and execution of large-scale, aquifer-wide CO 2 storage operations will require extensive use of computer modelling and simulations. The required computational tools will vary depending on the physical characteristics of the targeted aquifer, the stage of the project, and the questions asked, which may not always be anticipated in advance. In this paper, we argue that a one-size-fits-all simulation tool for the modelling CO 2 storage does not exist. Instead, we propose an integrated toolchain of computational methods that can be used in a flexible way to set up adaptive workflows. Although a complete toolchain will require computational methods at all levels of complexity, we further argue that lightweight methods play a particularly important role in addressing many of the relevant questions. We have implemented a number of such simplified methods in MRST-co2lab, a separate module to the open-source MATLAB Reservoir Simulation Toolbox (MRST). In particular, MRST-co2lab contains percolation-type methods that within seconds can identify structural traps and their catchment areas and compute spill paths and rough estimates of trapping capacity. The software also offers two-phase simulators based on vertical-equilibrium assumptions that can forecast structural, residual, and solubility trapping in a thousand-year perspective and are orders of magnitude faster than traditional 3D simulators. Herein, we apply these methods on realistic, large-scale datasets to demonstrate their capabilities and show how they can be used in combination to address optimal use of open aquifers for large-scale storage. [ABSTRACT FROM AUTHOR]

Abstract: Proteomics is a new and promising approach to evaluate potential effects of pollution. In order to investigate if there is a direct link between the protein expression profiles obtained by the SELDI–TOF MS technology and effects observed at the organism level in fish, plasma samples from unexposed and 20ppb alkylphenol exposed female Atlantic cod (Gadus morhua) with high phenotypic variation in gonadosomatic index (GSI) were analyzed by SELDI–TOF MS. Principle component analysis (PCA) showed that the major proteomic variation present in the dataset (i.e. 23.6%) could be significantly correlated to the individual variation in GSI, which indicates that SELDI–TOF MS data can reflect effects observed at higher levels of organization in fish. Further exploration of the other principal components revealed an additional proteomic pattern specific for the alkylphenol exposed females. Hence, this study supports the usefulness of SELDI–TOF MS as a proteomic tool in ecotoxicological research. [Copyright &y& Elsevier]

Compound-specific protein expression signatures (PESs) can be revealed by proteomic techniques. The SELDI-TOF MS approach is advantageous due to its simplicity and high-throughput capacity, however, there are concerns regarding the reproducibility of this method. The aim of this study was to define an estrogen-responsive PES in plasma of Atlantic cod (Gadus morhua) using the SELDI-TOF MS technique. Protein expression analysis of male cod exposed to 17β-estradiol (E2) showed that 27 plasma peaks were differentially expressed following exposure. The reproducibility of this result was evaluated by reanalyzing the samples six months later, and a significant change in expression was confirmed for 13 of the 27 peaks detected in the first analysis. The performance of the reproducible E2-responsive PES, constituting these 13 peaks, was then tested on samples from juvenile cod exposed to 4-nonylphenol, North Sea oil, or North Sea oil spiked with alkylphenols. Principal component analysis revealed that nonylphenol-exposed cod could be separated from unexposed cod based on the E2-responsive PES, indicating that the PES can be used to assess estrogenic exposure of both juvenile and adult specimens of cod. A targeted antibody-assisted SELDI-TOF MS approach was carried out in an attempt to identify the E2-responsive peaks. Results indicated that 2 peaks were fragments of the well-known biomarkers VTG and/or ZRP. In this study, the SELDI-TOF MS technology has shown its potential for defining compound-specific PESs in fish. Nevertheless, thorough validation of reproducibility, specificity and sensitivity of a PES is required before it can be applied in environmental monitoring. [Copyright &y& Elsevier]

• Joint effect of uncertain parameters affecting the overall CO 2 migration and trapping in the model is studied. • To make the study computationally feasible the simulations are performed using the VE approach. • Uncertain parameters include porosity and permeability heterogeneity, reservoir temperature, pressure and caprock elevation. • Caprock elevation was shown to be the most important parameter in controlling the plume migration. Several researchers have studied the Sleipner model to understand the inherent flow physics better, to find a satisfactory match of the CO 2 plume migration. Various sources of uncertainty in the geological model and the fluid have been investigated. Most of the work undertaken on the Sleipner model employed the one factor at a time (OFAT) method and analysed the impact of uncertain parameters on plume match individually. In this study, we have investigated the impact of some of the most cited sources of uncertainties including porosity, permeability, caprock elevation, reservoir temperature, reservoir pressure and injection rate on CO 2 plume migration and structural tapping in the Sleipner. We tried to fully span the uncertainty space on Sleipner 2019 Benchmark (Layer 9) using a vertical-equilibrium based simulator. To the best of our knowledge, this is the first time that a study has focused on the joint effect of six uncertain parameters using data-driven models. This work would raise our scientific understanding of the complexity of the impact of the reservoir uncertainty on CO 2 plume migration in a real field model. The caprock elevation was shown to be the most important parameter in controlling the plume migration (overall importance of 26 %) followed by injection rate (24 %), temperature (22 %), heterogeneity in permeability (13 %), pressure (9 %) and porosity (6 %). [ABSTRACT FROM AUTHOR]

• This work is the first benchmark study on the impact of caprock morphology on CO 2 storage migration. • A number of modelling approaches including MRST-co2lab, ECLIPSE-black-oil, ECLIPSE-compositional and ECLIPSE-VE are used. • In 3D simulators, the dissolution was seen to decrease by increasing the tilt angle. • Concerning the computation costs, MRST-co2lab significantly outperformed other models. Saline aquifers constitute the most abundant geological storage option for Carbon Capture and Storage (CCS) projects. When injected in the aquifer, due to its lower density in comparison to the in-situ brine, the free phase CO 2 tends to migrate upwards. This vertical migration is generally tens of metres depending on the reservoir thickness, despite the plume migration distance in the horizontal direction which could be over hundreds of kilometres (depending on the time horizon, reservoir characteristics, trapping mechanisms involved, etc.). In many situations, the plume ends up as a separate region below a sealing barrier. This large aspect ratio between the plume migration in the horizontal and vertical directions would potentially validate the use of vertical equilibrium (VE) models in CO 2 storage studies. In other words, when phase segregation occurs rapidly compared to the time scale studied, vertical equilibrium can be assumed, allowing for the use of specially adapted models. In the VE model, the equilibrium between brine and CO 2 is pre-assumed at all times. Under this assumption, the injected CO 2 plume flow in 3D can be approximated in terms of its thickness in order to obtain a 2D simulation model, which consequently decreases the computational costs. The time by which phase segregation occurs depends on the aquifer thickness, aquifer permeability, fluid properties, etc. However, the CO 2 and in-situ brine are separated considerably fast and form two separate layers, in comparison to the time period for lateral migration. The CO2lab module of the Matlab Reservoir Simulation Toolbox (MRST) used in this work, is a set of open source simulation and workflow tools to study the long-term, large-scale storage of CO 2. We employed the VE tool in MRST−CO2lab (MVE) to study the effect of caprock morphology on the CO 2 migration. The results have been compared with a number of simulators including ECLIPSE-black-oil (E100), ECLIPSE-compositional (E300) and ECLIPSE-VE (EVE) models and the differences between the approaches are analysed and discussed in detail. In particular, we focused on the impact of caprock morphology and aquifer top-surface slope on the CO 2 structural and dissolution trapping mechanisms and plume migration. The results indicated a good agreement for the ultimate plume shapes in all the models. However, the amount of dissolved CO 2 in the brine was different. [ABSTRACT FROM AUTHOR]