The effects of carbon dioxide leakage on fractures, and water quality of potable aquifers during geological sequestration of CO2

Since industrial revolution, the ＂greenhouse effect＂ is one of the most important global environmental issues. Of all the greenhouse gases, CO2 is responsible for about 64% of the enhanced ＂greenhouse effect＂, making it the target for mitigation, so reducing anthropogenic discharge of carbon dioxide attracts more and more attention. Geological sequestration of CO2 in deep saline aquifers is one of the most promising options. But because unknown fractures and faults may exist in the caprock layers which can prevent the leakage of CO2, CO2 will leak upward into upper potable aquifers, and lead to adverse impacts on the shallow potable aquifers. In order to assess the potential effect of CO2 leakage from underground storage reservoirs on fractures and water quality of potable aquifers, this study used the non-isothermal reactive geochemical transport code TOUGHREACT developed by Xu et al to establish a simplified 2-D model of CO2 underground sequestration system, which includes deep saline aquifers, caprock layers, and shallow potable aquifers, and study and analyze the changes of mineral and aqueous components. The simulation results indicated that the minerals of deep saline aquifers and fractures should be mainly composed of aluminosilicate and silicate minerals, which not only enhance the mass of CO2 sequestrated by mineral trapping, but also decrease the porosity and permeability of caprock layers and fractures to prevent and reduce CO2 leakage. The results from deep saline aquifers showed that the mass of carbon dioxide trapped by minerals and solution phases is limited, the rest remained as a supercritical phase, and so once the caprock aquifers have some unknown fractures, the free carbon dioxide phase may leak from CO2 geologic sequestration reservoirs by buoyancy.     

Reservoir description using dynamic parameterisation selection with a combined stochastic and gradient search

There is a correspondence between flow in a reservoir and large scale permeability trends. This correspondence can be derived by constraining reservoir models using observed production data. One of the challenges in deriving the permeability distribution of a field using production data involves determination of the scale of resolution of the permeability. The Adaptive Multiscale Estimation (AME) seeks to overcome the problems related to choosing the resolution of the permeability field by a dynamic parameterisation selection. The standard AME uses a gradient algorithm in solving several optimisation problems with increasing permeability resolution. This paper presents a hybrid algorithm which combines a gradient search and a stochastic algorithm to improve the robustness of the dynamic parameterisation selection. At low dimension, we use the stochastic algorithm to generate several optimised models. We use information from all these produced models to find new optimal refinements, and start out new optimisations with several unequally suggested parameterisations. At higher dimensions we change to a gradient-type optimiser, where the initial solution is chosen from the ensemble of models suggested by the stochastic algorithm. The selection is based on a predefined criterion. We demonstrate the robustness of the hybrid algorithm on sample synthetic cases, which most of them were considered insolvable using the standard AME algorithm.     

Modeling of the classification behavior of the diaphragms used in multi-chamber cement mills

A new approach has been developed for describing the classification that arises at the diaphragm in multi-chamber ball mills. Fourteen industrial scale cement mills have been sampled in this study and after mass balancing, model fits of the equipment were done. Successive mill product predictions for the sampled conditions were achieved, and requirements to build up an optimization capable model are discussed.     

Mais comment s'écoule donc un glacier ? Aperçu historique

Ice and snow have often helped physicists understand the world. On the contrary it has taken them a very long time to understand the flow of the glaciers. Naturalists only began to take an interest in glaciers at the beginning of the 19th century during the last phase of glacier advances. When the glacier flow from the upslope direction became obvious, it was then necessary to understand how it flowed. It was only in 1840, the year of the Antarctica ice sheet discovery by Dumont d'Urville, that two books laid the basis for the future field of glaciology: one by Agassiz on the ice age and glaciers, the other one by canon Rendu on glacier theory. During the 19th century, ice flow theories, adopted by most of the leading scientists, were based on melting/refreezing processes. Even though the word ‘fluid’ was first used in 1773 to describe ice, more the 130 years would have to go by before the laws of fluid mechanics were applied to ice. Even now, the parameter of Glen's law, which is used by glaciologists to model ice deformation, can take a very wide range of values, so that no unique ice flow law has yet been defined. To cite this article: F. Rémy, L. Testut, C. R. Geoscience 338 (2006).     

爆破夯实技术在水下地基处理中的应用

以某杂货码头和集装箱重力式码头水下地基处理工程为例，介绍了其地基处理的爆夯试验过程，得出了一次性爆破夯实厚层块石抛石基床的爆夯参数，并对其施工过程进行了监测。总结了类似工程施工的经验与教训。     

虚拟样机技术在地质工程机械领域的应用研究

基于对国内地质工程机械的研发现状的考虑，根据虚拟样机技术的特点，讨论了在地质工程机械领域实施虚拟样机技术的必要件，并提出了建立地质工程机械虚拟样机的策略。联合PRO／E、ANSYS及ADAMS建立了气动潜孔锤的虚拟样机模型，对气动潜孔锤虚拟样机进行了仿真，阐明了虚拟样机技术在地质工程机械领域的应用前景。     

Optimization of nonconventional wells under uncertainty using statistical proxies

The determination of the optimal type and placement of a nonconventional well in a heterogeneous reservoir represents a challenging optimization problem. This determination is significantly more complicated if uncertainty in the reservoir geology is included in the optimization. In this study, a genetic algorithm is applied to optimize the deployment of nonconventional wells. Geological uncertainty is accounted for by optimizing over multiple reservoir models (realizations) subject to a prescribed risk attitude. To reduce the excessive computational requirements of the base method, a new statistical proxy (which provides fast estimates of the objective function) based on cluster analysis is introduced into the optimization process. This proxy provides an estimate of the cumulative distribution function (CDF) of the scenario performance, which enables the quantification of proxy uncertainty. Knowledge of the proxy-based performance estimate in conjunction with the proxy CDF enables the systematic selection of the most appropriate scenarios for full simulation. Application of the overall method for the optimization of monobore and dual-lateral well placement demonstrates the performance of the hybrid optimization procedure. Specifically, it is shown that by simulating only 10% or 20% of the scenarios (as determined by application of the proxy), optimization results very close to those achieved by simulating all cases are obtained.     

Atomistic calculations of structural and elastic properties of serpentine minerals: the case of lizardite

The physical properties of the hydrous phyllosilicate lizardite have been investigated by atomistic simulation using the GULP code based on transferable semi-empirical interatomic potentials. Lizardite behavior was first investigated during structure relaxation at room temperature. The Helmholtz free energy is minimum for an equilibrium structure that is in agreement with experiment. The bulk, shear, and Young modulii for lizardite were calculated along with the Poisson ratio. From the shear and bulk modulii, we also calculated translational and longitudinal acoustic wave velocities that are important quantities for tectonophysics models. As expected, lizardite is stiffer in the a direction parallel to the layers than in the c perpendicular direction; the variation of the unit cell parameters with pressure is in good agreement with experiment. The cohesive energy between two successive layers along c direction was calculated at 0.33 eV (i.e., 0.11 eV per OH bond) in good agreement with recent ab initio calculations. Upon pressure and temperature variations, we evidenced that structural changes are mainly pressure induced; pressure being accommodated by a decrease of the c parameter up to 10 GPa. We also found that the change of slope in the derivative of the c cell parameter with respect to pressure occurring around 2 GPa originates from the bending of the interlayer hydroxyl groups with respect to the layer normal direction.     

New Generation of Probabilistic Seismic Hazard Assessment for the Area Cologne/Aachen Considering the Uncertainties of the Input Data

A new earthquake catalogue for central, northern and northwestern Europe with unified M_w magnitudes, in part derived from chi-square maximum likelihood regressions, forms the basis for seismic hazard calculations for the Lower Rhine Embayment. Uncertainties in the various input parameters are introduced, a detailed seismic zonation is performed and a recently developed technique for maximum expected magnitude estimation is adopted and quantified. Applying the logic tree algorithm, resulting hazard values with error estimates are obtained as fractile curves (median, 16% and 84% fractiles and mean) plotted for pga (peak ground acceleration; median values for Cologne 0.7 and 1.2 m/s² for probabilities of exceedence of 10% and 2%, respectively, in 50 years), 0.4 s (0.8 and 1.5 m/s²) and 1.0 s (0.3 and 0.5 m/s²) pseudoacclerations, and intensity (I₀ = 6.5 and 7.2). For the ground motion parameters, rock foundation is assumed. For the area near Cologne and Aachen, maps show the median and 84% fractile hazard for 2% probability of exceedence in 50 years based on pga (maximum median value about 1.5 m/s²), and 0.4 s (>2 m/s²) and 1.0 s (about 0.8 m/s²) pseudoaccelerations, all for rock. The pga 84% fractile map also has a maximum value above 2 m/s² and shows similarities with the median map for 0.4 s. In all maps, the maximum values fall within the area 6.2–6.3° E and 50.8–50.9° N, i.e., east of Aachen.     

T -distributed Random Fields: A Parametric Model for Heavy-tailedWell-log Data1

Histograms of observations from spatial phenomena are often found to be more heavy-tailed than Gaussian distributions, which makes the Gaussian random field model unsuited. A T-distributed random field model with heavy-tailed marginal probability density functions is defined. The model is a generalization of the familiar Student-T distribution, and it may be given a Bayesian interpretation. The increased variability appears cross-realizations, contrary to in-realizations, since all realizations are Gaussian-like with varying variance between realizations. The T-distributed random field model is analytically tractable and the conditional model is developed, which provides algorithms for conditional simulation and prediction, so-called T-kriging. The model compares favourably with most previously defined random field models. The Gaussian random field model appears as a special, limiting case of the T-distributed random field model. The model is particularly useful whenever multiple, sparsely sampled realizations of the random field are available, and is clearly favourable to the Gaussian model in this case. The properties of the T-distributed random field model is demonstrated on well log observations from the Gullfaks field in the North Sea. The predictions correspond to traditional kriging predictions, while the associated prediction variances are more representative, as they are layer specific and include uncertainty caused by using variance estimates.