Assessment of trace metals contamination in stream sediments and soils in Abuja leather mining,southwestern Nigeria

This study is aimed at determining the level of environmental degradation as well as the concentration of trace elements in soil and stream sediments in order to evaluate the environmental impact of the mining operation. Twenty-five (25) soils and ten (10) stream sediment samples were collected from the study area. The physicochemical parameters were determined using appropriate instrumentation with the aid of a digital pH meter (Milwaukee meter) to measure the pH and electrical conductivity, total dissolved solids, moisture content and loss on ignition of the soil and stream sediment samples. The pH of the soil sample ranged from (6.10 to 7.19); Electrical conductivity ranged from (21.3 to 279.4 µS/cm), moisture content varied from (0.60% to 7.20%), and the LOI ranged from (2.03% to 18.62%). The results of the analysis showed that the concentrations of the trace elements in the soils and stream sediment samples were slightly higher than the background values. Plots of the trace elements in stream sediment samples show moderate, consistent decrease downstream except at points where there was mine water discharge into the main river. The pollution levels of heavy metals were examined in stream sediment and soil samples using different assessable indices, such as the enrichment factor, which showed significant-moderate enrichment for Cr, Th, Nb, Zn, Pb, Y and Zr and the geo-accumulation index, which showed practically moderate contamination with Cr, Ni and Sr based on regional background reference values. Geo-accumulation index and contamination index for soils and stream sediment revealed uncontaminated to moderate contamination. Likewise, elements with moderate contamination were Cr, Ni and Sr. The Pearson correlation showed that there were significant positive associations among selected metals in soil and stream sediment samples.     

Geochemistry and geochronology of Late Jurassic and Early Cretaceous intrusions related to some Au (Sb) deposits in southern Anhui: a case study and review

Some Au deposits in southern Anhui Province have recently been found to be closely associated with Late Mesozoic intrusions. Typical examples include the Huashan Au (Sb) deposit and Au deposits at Zhaojialing, Wuxi, and Liaojia. In order to understand the mechanisms that led the formation of these Au deposits, we make detailed reviews on the geological characteristics of these Au deposits. Specifically, we present new LA-ICP-MS zircon U–Pb dating, along with elemental and Hf isotopic data from the Huashan Au (Sb) deposit. Our data suggests that the Huashan ore-related intrusions were emplaced during the Late Jurassic and Early Cretaceous periods (144–148 Ma). They are characterized by arc-magma features and high oxygen fugacity and are rich in inherited zircons. Zircon U–Pb ages and Lu–Hf isotopes from intrusions suggest that Proterozoic juvenile lithosphere is the main source of these intrusions. The regional geological history implies that lithosphere beneath southern Anhui was produced during a Proterozoic subduction and was fertilized with Au (Cu) in the process. Integrated with the results of previous studies, we inferred that Late Mesozoic intrusions formed by the remelting of the lithosphere could provide the metal endowment for the Au-rich deposits in southern Anhui.     

Geoscience Frontiers 2017 Annual Convention

正The 2017 Geoscience Frontiers Annual Convention was held in Beijing,China during October 19-21,2017 hosted by China University of Geosciences,Beijing(Fig.1).This convention assembled earth scientists from seven countries,including Australia(Dr.Christopher Spencer and Dr.Stijn Glorie),Korea(Dr.S.Kwon),India(Dr.Shaji Erath),Japan(Dr.Toshiaki Tsunogae and Dr.Masaki Yoshida),Russia(Dr.Inna Safonova),UK(Dr.Nick Roberts),China,and also     

The Fragmentation in a Protoplanetary Disk and the Properties of the Resultant Self-Gravitating Clumps

We study the fragmentation properties in the protoplanetary disk and properties of the resultant self-gravitating clumps using our newly constructed disk model. Our disk model includes the mass inflall term from a molecular cloud core and the photoevaporation winds effect. We adopt the conventional fragmentation criterion to judge whether a protoplanetary disk can fragment. In this work, we follow our previous work to investigate the properties of the resultant self-gravitating clumps. In our calculation, the initial masses of the resultant self-gravitating clumps lie in the range of tens of M_J to more than one hundred of M_J, where M_J is the Jupiter mass. These initial masses can seemingly account for the masses of extrasolar planets in magnitude. We also calculate the subsequent gas accretion of clumps in 1.27 × 10⁴ yr after the formation of self-gravitating clumps. We find that the subsequent gas accretion of self-gravitating clumps is very efficient, and the clump masses grow to hundreds of M_J and the physical radii R_c of clumps increase to about 10 AU. Additionally, we also calculate the orbital migration of clumps. We find that most clumps have short migration timescale to be accreted onto the protostar, and only a small fraction of clumps have long migration timescale (>10⁶ yr) to successfully become gas giant planets. These results are consistent with previous studies.     

High-dimensional geostatistical history matching

Hydrocarbon reservoir modelling and characterisation is a challenging subject within the oil and gas industry due to the lack of well data and the natural heterogeneities of the Earth’s subsurface. Integrating historical production data into the geo-modelling workflow, commonly designated by history matching, allows better reservoir characterisation and the possibility of predicting the reservoir behaviour. We present herein a geostatistical-based multi-objective history matching methodology. It starts with the generation of an initial ensemble of the subsurface petrophysical property of interest through stochastic sequential simulation. Each model is then ranked according the match between its dynamic response, after fluid flow simulation, and the observed available historical production data. This enables building regionalised Pareto fronts and the definition of a large ensemble of optimal subsurface Earth models that fit all the observed production data without compromising the exploration of the uncertainty space. The proposed geostatistical multi-objective history matching technique is successfully implemented in a benchmark synthetic reservoir dataset, the PUNQ-S3, where 12 objectives are targeted.     

Constraint energy minimizing generalized multiscale finite element method in the mixed formulation

This paper presents a novel mass-conservative mixed multiscale method for solving flow equations in heterogeneous porous media. The media properties (the permeability) contain multiple scales and high contrast. The proposed method solves the flow equation in a mixed formulation on a coarse grid by constructing multiscale basis functions. The resulting velocity field is mass-conservative on the fine grid. Our main goal is to obtain first-order convergence in terms of the mesh size which is independent of local contrast. This is achieved, first, by constructing some auxiliary spaces, which contain global information that cannot be localized, in general. This is built on our previous work on the generalized multiscale finite element method (GMsFEM). In the auxiliary space, multiscale basis functions corresponding to small (contrast-dependent) eigenvalues are selected. These basis functions represent the high-conductivity channels (which connect the boundaries of a coarse block). Next, we solve local problems to construct multiscale basis functions for the velocity field. These local problems are formulated in the oversampled domain, taking into account some constraints with respect to auxiliary spaces. The latter allows fast spatial decay of local solutions and, thus, allows taking smaller oversampled regions. The number of basis functions depends on small eigenvalues of the local spectral problems. Moreover, multiscale pressure basis functions are needed in constructing the velocity space. Our multiscale spaces have a minimal dimension, which is needed to avoid contrast dependence in the convergence. The method’s convergence requires an oversampling of several layers. We present an analysis of our approach. Our numerical results confirm that the convergence rate is first order with respect to the mesh size and independent of the contrast.     

Interior boundary-aligned unstructured grid generation and cell-centered versus vertex-centered CVD-MPFA performance

Grid generation for reservoir simulation must honor classical key constraints and be boundary aligned such that control-volume boundaries are aligned with geological features such as layers, shale barriers, fractures, faults, pinch-outs, and multilateral wells. An unstructured grid generation procedure is proposed that automates control-volume and/or control point boundary alignment and yields a PEBI-mesh both with respect to primal and dual (essentially PEBI) cells. In order to honor geological features in the primal configuration, we introduce the idea of protection circles, and to generate a dual-cell feature based grid, we construct halos around key geological features. The grids generated are employed to study comparative performance of cell-centred versus cell-vertex control-volume distributed multi-point flux approximation (CVD-MPFA) finite-volume formulations using equivalent degrees of freedom. The formulation of CVD-MPFA schemes in cell-centred and cell-vertex modes is analogous and requires switching control volume from primal to dual or vice versa together with appropriate data structures and boundary conditions. The relative benefits of both types of approximation, i.e., cell-centred versus vertex-centred, are made clear in terms of flow resolution and degrees of freedom required.     

Ensemble clustering for efficient robust optimization of naturally fractured reservoirs

In the development of naturally fractured reservoirs (NFRs), the existence of natural fractures induces severe fingering and breakthrough. To manage the flooding process and improve the ultimate recovery, we propose a numerical workflow to generate optimal production schedules for smart wells, in which the inflow control valve (ICV) settings can be controlled individually. To properly consider the uncertainty introduced by randomly distributed natural fractures, the robust optimization would require a large ensemble size and it would be computationally demanding. In this work, a hierarchical clustering method is proposed to select representative models for the robust optimization in order to avoid redundant simulation runs and improve the efficiency of the robust optimization. By reducing the full ensemble of models into a small subset ensemble, the efficiency of the robust optimization algorithm is significantly improved. The robust optimization is performed using the StoSAG scheme to find the optimal well controls that maximize the net-present-value (NPV) of the NFR’s development. Due to the discrete property of a natural fracture field, traditional feature extraction methods such as model-parameter-based clustering may not be directly applicable. Therefore, two different kinds of clustering-based optimization methods, a state-based (e.g., s _w profiles) clustering and a response-based (e.g., production rates) clustering, are proposed and compared. The computational results show that the robust clustering optimization could increase the computational efficiency significantly without sacrificing much expected NPV of the robust optimization. Moreover, the performance of different clustering algorithms varies widely in correspondence to different selections of clustering features. By properly extracting model features, the clustered subset could adequately represent the uncertainty of the full ensemble.