Cluster Analysis of Petrophysical and Geological Parameters for Separating the Electrofacies of a Gas Carbonate Reservoir Sequence

Natural Resources Research - Assessing reservoir properties and knowing the relationship between different reservoir parameters can significantly help to plan for production from a reservoir. In...     

Scaling property of regional floods in New South Wales Australia

Regional flood frequency analysis (RFFA) is often used in hydrology to estimate flood quantiles when there is a limitation of at-site recorded flood data. One of the commonly used RFFA methods is the index flood method, which is based on the assumptions that a region satisfies criterion of simple scaling and it can be treated homogeneous. Another RFFA method is quantile regression technique where prediction equations are developed for flood quantiles of interest as function of catchment characteristics. In this paper, the scaling property of regional floods in New South Wales (NSW) State in Australia is investigated. The results indicate that the annual maximum floods in NSW satisfy a simple scaling assumption. The application of a heterogeneity test, however, reveals that NSW flood data set does not satisfy the criteria for a homogeneous region. Finally, a set of prediction equations are developed for NSW using quantile regression technique; an independent test shows that these equations can provide reasonably accurate design flood estimates with a median relative error of about 27%.     

Applying an optimized proxy-based workflow for fast history matching

History matching is still one of the main challenging parts of reservoir study especially in giant brown oil fields with lots of wells. In these cases, history matching with conventional manual technique needs many runs and takes months to get a match. In this work, an innovative approach was suggested for fast history matching in a real brown field. The workflow was employed based on an optimized proxy model for history matching of a field consisting of 14 active wells with multiple responses (which are production rate and pressure data) in the south part of Iran. The main important features of the proposed algorithm were defining a proxy model which is response surface method in which 21 model parameters were incorporated based on cubic centered face method. The proxy model was then optimized by one of the most famous algorithms which is genetic algorithm. Proxy model was successfully performed using 256 samples leading into p- value of 0.531 and R ² of 0.91 dataset. As a result, the proposed workflow and algorithm showed good and acceptable results for history matching of studied real model.     

Socio-political and ecological stresses on traditional pastoral systems: A review

Journal of Geographical Sciences - Pastoralism is a viable socio-economic system-shaped by landless and agro-pastoral communities in many pastoral regions of the world. This system is mainly based...     

Analysis of stochastic characteristics of the Benue River flow process

Stochastic characteristics of the Benue River streamflow process are examined under conditions of data austerity. The streamflow process is investigated for trend, non-stationarity and seasonality for a time period of 26 years. Results of trend analyses with Mann-Kendall test show that there is no trend in the annual mean discharges. Monthly flow series examined with seasonal Kendall test indicate the presence of positive change in the trend for some months, especially the months of August, January, and February. For the stationarity test, daily and monthly flow series appear to be stationary whereas at 1%, 5%, and 10% significant levels, the stationarity alternative hypothesis is rejected for the annual flow series. Though monthly flow appears to be stationary going by this test, because of high seasonality, it could be said to exhibit periodic stationarity based on the seasonality analysis. The following conclusions are drawn： （1） There is seasonality in both the mean and variance with unimodal distribution. （2） Days with high mean also have high variance. （3） Skewness coefficients for the months within the dry season period are greater than those of the wet season period, and seasonal autocorrelations for streamflow during dry season are generally larger than those of the wet season. Precisely, they are significantly different for most of the months. （4） The autocorrelation functions estimated ＂over time＂ are greater in the absolute value for data that have not been deseasonalised but were initially normalised by logarithmic transformation only, while autocorrelation functions for i = 1, 2 365 estimated ＂over realisations＂ have their coefficients significantly different from other coefficients.     

Indices based assessment of built-up density and urban expansion of fast growing Surat city using multi-temporal Landsat data sets

GeoJournal - The population growth in urban areas leads to the expansion of built-up area which leads to a number of serious problems like environmental pollution, destruction of urban ecology,...     

Wrench tectonics of Abu Gharadig Basin,Western Desert,Egypt: a structural analysis for hydrocarbon prospects

Mapping based on the interpreted seismic data covering the Abu Gharadig Basin in the northern Western Desert has revealed that the deposition of the Upper Cretaceous succession was controlled by dextral wrench tectonics. This dextral shear accompanied NW movement of the African Plate relative to Laurasian Plate. Structural depth maps of the Cenomanian Bahariya Formation and the Turonian-Coniacian D and A members of Abu Roash Formation display a clear NE-SW anticline dissected by NW-SE normal faults. This anticline represents one of the en echelon folds characterizing the wrench compressional component. The interpreted normal faults reflect the extensional T-fractures associated with the wrenching tectonics. The interaction between the aforementioned NE-SW anticline with the NW-SE extensional faults further confirms the effect of the Upper Cretaceous dextral wrench tectonic. However, the influence of this wrench tectonics was gradually diminishing from the Cenomanian up to the Coniacian times. The NW-SE compressional stress of the dextral wrench compressional component during the Cenomanian up to Coniacian age was greater in NW direction than the SE direction. Three mapped structural closures which are predicted to be potential hydrocarbon traps belonging to the Bahariya Formation and Abu Roash D Member, and are recommended to be drilled in the study area, with potential reservoirs. The regularity of the en echelon array of both anticlines and normal faults within the wrench zones suggests additional closures may be located elsewhere beside the study area.     

Missing basics: a study on sanitation and women’s health in urban slums in Lucknow,India

GeoJournal - Sanitation is a multidimensional concept alluding primarily to provision of services for safe disposal of human excreta, provision of clean potable water as well as maintenance of...     

Integration of aquifer geology,groundwater flow and arsenic distribution in deltaic aquifers – A unifying concept

Groundwater arsenic (As) presents a public health risk of great magnitude in densely populated Asian delta regions, most acutely in the Bengal Basin (West Bengal, India and Bangladesh). Research has focused on the sources, mobilisation, and heterogeneity of groundwater As, but a consistent explanation of As distribution from local to basin scale remains elusive. We show for the Bengal Aquifer System that the numerous, discontinuous silt‐clay layers together with surface topography impose a hierarchical pattern of groundwater flow, which constrains As penetration into the aquifer and controls its redistribution towards discharge zones, where it is re‐sequestered to solid phases. This is particularly so for the discrete periods of As release to groundwater in the shallow subsurface associated with sea level high‐stand conditions of Quaternary inter‐glacial periods. We propose a hypothesis concerning groundwater flow ( S ilt‐clay layers I mpose H ierarchical groundwater flow patterns constraining A rsenic progression [SIHA]), which links consensus views on the As source and history of sedimentation in the basin to the variety of spatial and depth distributions of groundwater As reported in the literature. SIHA reconciles apparent inconsistencies between independent, in some cases contrasting, field observations. We infer that lithological and topographic controls on groundwater flow, inherent to SIHA, apply more generally to deltaic aquifers elsewhere. The analysis suggests that groundwater As may persist in the aquifers of Asian deltas over thousands of years, but in certain regions, particularly at deeper levels, As will not exceed low background concentrations unless groundwater flow systems are short‐circuited by excessive pumping.     

Burden prediction in blasting operation using rock geomechanical properties

Burden prediction is a vital task in the production blasting. Both the excessive and insufficient burden can significantly affect the result of blasting operation. The burden which is determined by empirical models is often inaccurate and needs to be adjusted experimentally. In this paper, an attempt was made to develop an artificial neural network (ANN) in order to predict burden in the blasting operation of the Mouteh gold mine, using considering geomechanical properties of rocks as input parameters. As such here, network inputs consist of blastability index (BI), rock quality designation (RQD), unconfined compressive strength (UCS), density, and cohesive strength. To make a database (including 95 datasets), rock samples are used from Iran’s Mouteh goldmine. Trying various types of the networks, a neural network, with architecture 5-15-10-1, was found to be optimum. Superiority of ANN over regression model is proved by calculating. To compare the performance of the ANN modeling with that of multivariable regression analysis (MVRA), mean absolute error (E _a), mean relative error (E _r), and determination coefficient (R ²) between predicted and real values were calculated for both the models. It was observed that the ANN prediction capability is better than that of MVRA. The absolute and relative errors for the ANN model were calculated 0.05 m and 3.85%, respectively, whereas for the regression analysis, these errors were computed 0.11 m and 5.63%, respectively. Moreover, determination coefficient of the ANN model and MVRA were determined 0.987 and 0.924, respectively. Further, a sensitivity analysis shows that while BI and RQD were recognized as the most sensitive and effective parameters, cohesive strength is considered as the least sensitive input parameters on the ANN model output effective on the proposed (burden).