Composition, porosity, and reservoir potential of the Middle Jurassic Kashafrud Formation, northeast Iran

In the Kopet-Dagh Basin of Iran, deep-sea sandstones and shales of the Middle Jurassic Kashafrud Formation are disconformably overlain by hydrocarbon-bearing carbonates of Upper Jurassic and Cretaceous age. To explore the reservoir potential of the sandstones, we studied their burial history using more than 500 thin sections, supplemented by heavy mineral analysis, microprobe analysis, porosity and permeability determination, and vitrinite reflectance.The sandstones are arkosic and lithic arenites, rich in sedimentary and volcanic rock fragments. Quartz overgrowths and pore-filling carbonate cements (calcite, dolomite, siderite and ankerite) occluded most of the porosity during early to deep burial, assisted by early compaction that improved packing and fractured quartz grains. Iron oxides are prominent as alteration products of framework grains, probably reflecting source-area weathering prior to deposition, and locally as pore fills. Minor cements include pore-filling clays, pyrite, authigenic albite and K-feldspar, and barite. Existing porosity is secondary, resulting largely from dissolution of feldspars, micas, and rock fragments, with some fracture porosity. Porosity and permeability of six samples averages 3.2% and 0.0023 mD, respectively, and 150 thin-section point counts averaged 2.7% porosity. Reflectance of vitrinite in eight sandstone samples yielded values of 0.64-0.83%, in the early mature to mature stage of hydrocarbon generation, within the oil window.Kashafrud Formation petrographic trends were compared with trends from first-cycle basins elsewhere in the world. Inferred burial conditions accord with the maturation data, suggesting only a moderate thermal regime during burial. Some fractures, iron oxide cements, and dissolution may reflect Cenozoic tectonism and uplift that created the Kopet-Dagh Mountains. The low porosity and permeability levels of Kashafrud Formation sandstones suggest only a modest reservoir potential. For such tight sandstones, fractures may enhance the reservoir potential.     

Factor and cluster analysis of water quality data of the groundwater wells of Kushtia, Bangladesh: Implication for arsenic enrichment and mobilization

The study area is located in the southwestern part of Bangladesh. Twenty-six groundwater samples were collected from both shallow and deep tube wells ranging in depth from 20 to 60 m. Multivariate statistical analyses including factor analysis, cluster analysis and multidimensional scaling were applied to the hydrogeochemical data. The results show that a few factors adequately represent the traits that define water chemistry. The first factor of Fe and HCO₃ is strongly influenced by bacterial Fe (III) reduction which would raise both Fe and HCO₃ concentrations in water. Na, Cl, Ca, Mg and PO₄ are grouped under the second factor representing the salinity sources of waters. The third factor, represented by As, Mn, SO₄ and K is related to As mobilization processes. Cluster analysis has been applied for the interpretation of the groundwater quality data. Initially Piper methods have been employed to obtain a first idea on the water types in the study area. Hierarchical cluster analysis was carried out for further classification of water types in the study area. Twelve components, namely, pH, Fe, Mn, As, Ca, Mg, Na, K, HCO₃, Cl, SO₄ and NO₃ have been used for this purpose. With hierarchical clustering analysis the water samples have been classified into 3 clusters. They are very high, high and moderately As-enriched groundwater as well as groundwater with elevated SO₄.     

Landslide susceptibility assessment along the southern coast of the Caspian Sea,Iran

China is a disaster-prone country, and these disasters have diverse characteristics, a wide scope of distribution, high frequency, and large losses. China has advanced community-based disaster management (CBDM) capacity. Community is the bottom unit of the society, and CBDM is the foundation of the entire society’s disaster management system. A series of domestic major emergency incidents and disasters and international disaster reduction activities have promoted the formation of the CBDM concept, the implementation of capacity building activities, and the improvement of policy and laws. Thus far, the CBDM system has been preliminarily formed in China, and relevant rules and regulations have been promulgated and implemented. Furthermore, disaster reduction activities, such as the construction of the national comprehensive disaster reduction community and national safe community, have been promoted nationwide. As a result, China’s disaster-resistance capacity has largely improved. However, it is only in the initial phase of CBDM implementation, which remains plagued by several challenges and problems, such as the deficiency of community resident participation, management organizations, disaster risk assessment methods, NGO development, and safety culture cultivation.     

A study of differentiation pattern and rare earth elements migration in geochemical and hydrogeochemical environments of Airekan and Cheshmeh Shotori areas (Central Iran)

The Airekan and Cheshmeh Shotori areas are located about 60 km northeast of Khour, in Isfahan province from Central Iran. Research on characteristics and rare earth elements (REE) pattern in hydrogeochemical environments of these areas suggests the same origin for the elements dissolved in groundwater in these areas. Investigation of migration pattern of REE in hydrogeochemical environments shows that the migration and transportation of REE has occurred through chloride complexes. REEs, leached by water/rock interaction from the Airekan granite, are transported by groundwater and then precipitated in the Cheshmeh Shotori area. Study of the Cheshmeh Shotori sediments shows the presence of a sequence of red oxidized and dark layers. Geochemical characteristics of these sediments reveal that their REE characteristics are mainly inherited from the Airekan granite. Changes in the REE pattern of these sediments with depth show that changes in oxidation and reduction process have not played a significant role in controlling their behavior. It is crucial to note that adsorption of REEs dissolved in water by hydrosilicate increases these elements in depth. The REE behavior shows water/rock interaction between the granitic rocks and groundwater as the main factor of solution, migration and precipitation of REEs in the Cheshmeh Shotori area.     

Vertical geochemical variations and arsenic mobilization in the shallow alluvial aquifers of the Chapai-Nawabganj District, northwestern Bangladesh: implication of siderite precipitation

Core sediments from three disturbed boreholes (JOR, GHAT, and RAJ) and two undisturbed boreholes (DW1 and DW2) were collected in the study area of the Chapai-Nawabganj district of northwestern Bangladesh for geochemical analyses. In the study area, groundwater samples from fourteen As-contained private wells and five nested piezometers at both the DW1 and DW2 boreholes were also collected and analyzed. The groundwater arsenic concentrations in the uppermost aquifer (10–40 m of depth) range from 3 to 315 μg/L (mean 47.73 ± 73.41 μg/L), while the arsenic content in sediments range from 2 to 14 mg/kg (mean 4.36 ± 3.34 mg/kg). An environmental scanning electron microscope (ESEM) with an energy dispersive X-ray spectrometer was used to investigate the presence of major and trace elements in the sediments. Groundwaters in the study area are generally the Ca–HCO₃ type with high concentrations of As, but low levels of Fe, Mn, NO₃ ^? and SO ₄ ^?2 . The concentrations of As, Fe, Mn decrease with depth in the groundwater, showing vertical geochemical variations in the study area. Statistical analysis clearly shows that As is closely associated with Fe and Mn in the sediments of the JOR core (r = 0.87, p < 0.05 for Fe and r = 0.78, p < 0.05 for Mn) and GHAT core (r = 0.95, p < 0.05 for Fe and r = 0.93, p < 0.05 for Mn), while As is not correlated with Fe and Mn in groundwater. The comparatively low Fe and Mn concentrations in some groundwater and the ESEM image revealed that siderite precipitated as a secondary mineral on the surface of the sediment particles. The correlations along with results of sequential extraction experiments indicated that reductive dissolution of FeOOH and MnOOH represents a mechanism for releasing arsenic into the groundwater.     

Simple formulas for the dynamic stiffness of pile groups

Simple formulas are derived for the dynamic stiffness of pile group foundations subjected to horizontal and rocking dynamic loads. The formulations are based on the construction of a general model of impedance matrices as the condensation of matrices of mass, damping, and stiffness, and on the identification of the values of these matrices on an extensive database of numerical experiments computed using coupled finite element–boundary element models. The formulations obtained can be readily used for the design of both floating piles on homogeneous half‐space and end‐bearing piles and are applicable for a wide range of mechanical and geometrical parameters of the soil and piles, in particular for large pile groups. For the seismic design of a building, the use of the simple formulas rather than a full computational model is shown to induce little error on the evaluation of the response spectra and time histories. Copyright © 2009 John Wiley & Sons, Ltd.     

Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

A reliable and accurate prediction of the tunnel boring machine(TBM) performance can assist in minimizing the relevant risks of high capital costs and in scheduling tunneling projects.This research aims to develop six hybrid models of extreme gradient boosting(XGB) which are optimized by gray wolf optimization(GWO), particle swarm optimization(PSO), social spider optimization(SSO), sine cosine algorithm(SCA), multi verse optimization(MVO) and moth flame optimization(MFO), for estimation of the TBM penetration rate(PR).To do this, a comprehensive database with 1286 data samples was established where seven parameters including the rock quality designation, the rock mass rating, Brazilian tensile strength(BTS), rock mass weathering, the uniaxial compressive strength(UCS), revolution per minute and trust force per cutter(TFC), were set as inputs and TBM PR was selected as model output.Together with the mentioned six hybrid models, four single models i.e., artificial neural network, random forest regression, XGB and support vector regression were also built to estimate TBM PR for comparison purposes.These models were designed conducting several parametric studies on their most important parameters and then, their performance capacities were assessed through the use of root mean square error, coefficient of determination, mean absolute percentage error, and a10-index.Results of this study confirmed that the best predictive model of PR goes to the PSO-XGB technique with system error of(0.1453, and 0.1325), R~2 of(0.951, and 0.951), mean absolute percentage error(4.0689, and 3.8115), and a10-index of(0.9348, and 0.9496) in training and testing phases, respectively.The developed hybrid PSO-XGB can be introduced as an accurate, powerful and applicable technique in the field of TBM performance prediction.By conducting sensitivity analysis, it was found that UCS, BTS and TFC have the deepest impacts on the TBM PR.     

Application of multivariate statistical methods to indicate the origin and geochemical behavior of potentially hazardous elements in sediment around the Sarcheshmeh copper mine,SE Iran

Multivariate statistical techniques, i.e., correlation coefficient analysis, principal components analysis (PCA), and hierarchical cluster analysis (CA), were applied to the total and water-soluble concentrations of potentially hazardous metals in sediments associated with the Sarcheshmeh mine, one of the largest Oligo-Miocene porphyry copper deposits in the world. The samples were analyzed for hazardous metal concentration levels by inductively coupled plasma mass spectrometry method. Results indicate that the contaminant metals As, Cd, Cu, Mo, S, Sb, Sn, Se, Pb, and Zn were positively correlated with the total concentrations. These hazardous metals also have strong association in the PCA and CA results. Different anthropic versus natural sources of contaminant metals were distinguished by using CA method. Water-soluble fraction of hazardous metals showed that the hydro-geochemical behavior of these metals in sediments is different considerably. Elements such as Cd, Co, Cr, Cu, Fe, Mn, Ni, S, and Zn are readily water soluble from contaminated samples, especially from evaporative mineral phases, while the release of As, Mo, Sb, and Pb into the water is limited by adsorption processes. Results obtained from the application of multivariate techniques on the water-soluble fraction data set show that the hazardous metals are categorized into three groups including (1) Ni, S, Co, Cu, Cr, and Fe; (2) Se, Mn, Cd, and Zn; and (3) Sb, As, Mo, and Sn. This classification describes the hydro-geochemical behavior of hazardous metals in water–sediment environments of the Sarcheshmeh porphyry copper mine and can be used as a basis in remedial and treatment strategies.     

Estimation of sediment load and erosion of different geological units: A case study from a basin of north-eastern Iran

Erosion of geological units and sediment load in rivers can be considered as the serious problems in recent decades.Increasing sediment loads generate major hazards for water resources development,particularly in terms of loss of reservoir storage due to sedimentation and siltation of water distribution systems.In this paper,the performance of four sediment rating curve (SRC) development methods was evaluated for the Shirin Darreh River(SDR) basin (1750 km2),located in North Khorasan Province,Iran.Data of flow discharge (Q) and suspended sediment flux (SSF)(Q-SSF pairs,N=957)and daily flow discharge,recorded by the Regional Water Company of North Khorasan (RWCNK) at the Qaleh-Barbar (QB) gauging site during 1989-2018were used.The flow discharge classification method performed best by meeting the desired criteria of most statistical indices,including normalized root mean square error (NRMSE),mean bias error (MBE),mean absolute error (MAE),index of agreement (d),and coefficient of determination (R~2).Based on the optimized method,the rate of suspended sediment transportation at the study site was estimated about2.7×10~6 ton year~(-1).Erodibility of the exposed formations in the study area was estimated based on a factorial scoring model (FSM).Three indices,focused on the outcrop and erodibility,were calculated for the geological units at sub-basin and total scales.Marl deposits are the most extensive geological unit in the three sub-basins and the maximum formation outcrop ratio (FOR) and participation in erosion (PCE)were obtained for these rocks at total scale.In fact,marl unit can be regarded as the main source to supply the suspended sediments in the study basin.     

A GIS‐based multi‐criteria seismic vulnerability assessment using the integration of granular computing rule extraction and artificial neural networks

This study proposes multi‐criteria group decision‐making to address seismic physical vulnerability assessment. Granular computing rule extraction is combined with a feed forward artificial neural network to form a classifier capable of training a neural network on the basis of the rules provided by granular computing. It provides a transparent structure despite the traditional multi‐layer neural networks. It also allows the classifier to be applied on a set of rules for each incoming pattern. Drawbacks of original granular computing (GrC) are covered, where some input patterns remained unclassified. The study was applied to classify seismic vulnerability of the statistical units of the city of Tehran, Iran. Slope, seismic intensity, height and age of the buildings were effective parameters. Experts ranked 150 randomly selected sample statistical units with respect to their degree of seismic physical vulnerability. Inconsistency of the experts' judgments was investigated using the induced ordered weighted averaging (IOWA) operator. Fifty‐five classification rules were extracted on which a neural network was based. An overall accuracy of 88%, κ = 0.85 and R² = 0.89 was achieved. A comparison with previously implemented methodologies proved the proposed method to be the most accurate solution to the seismic physical vulnerability of Tehran.