利用瞬变电磁和多频电磁方法监测地下水位及其对Hawara遗址的影响

利用瞬变电磁（TEM）和地面电磁（GEM）方法,本文研究了埃及Hawara遗址区的地下水对遗址的影响.这个遗址包括Hawara金字塔、北区墓地、以及被称作“迷宫”的南区墓葬场所.现今Hawara遗址已经完全荒废,被耕作区和Bahr Wahba运河包围.地表水和地下水会破坏Hawara金字塔和“迷宫”遗址的地基,现在金字塔入口已被淹没至地面下约6 m深处.本文在耕作区、金字塔以及“迷宫”等三个地区进行了TEM勘察;在“迷宫”地区进行了GEM勘察.综合分析以上两种勘察数据,我们发现,农业灌溉是浸入到地下的水的主要来源;本地区地下水位随着观测点及海拔的不同,在地面以下2~7 m之间变化.     

Groundwater budget for the upper and middle parts of the River Gash Basin, eastern Sudan

The River Gash Basin is filled by the Quaternary alluvial deposits, unconformably overlying the basement rocks. The alluvial deposits are composed mainly of unconsolidated layers of gravel, sand, silt, and clays. The aquifer is unconfined and is laterally bounded by the impermeable Neogene clays. The methods used in this study include the carry out of pumping tests and the analysis of well inventory data in addition to the river discharge rates and other meteorological data. The average annual discharge of the River Gash is estimated to be 1,056?×?10⁶ m³ at El Gera gage station (upstream) and 587?×?10⁶ m³ at Salam-Alikum gage station (downstream). The annual loss mounts up to 40% of the total discharge. The water loss is attributed to infiltration and evapotranspiration. The present study proofs that the hydraulic conductivity ranges from 36 to 105 m/day, whereas the transmissivity ranges from 328 to 1,677 m²/day. The monitoring of groundwater level measurements indicates that the water table rises during the rainy season by 9 m in the upstream and 6 m in the midstream areas. The storage capacity of the upper and middle parts of the River Gash Basin is calculated as 502?×?10⁶ m³. The groundwater input reach 386.11?×?10⁶ m³/year, while the groundwater output is calculated as 365.98?×?10⁶ m³/year. The estimated difference between the input and output water quantities in the upper and middle parts of the River Gash Basin demonstrates a positive groundwater budget by about 20?×?10⁶ m³/year     

The application of remote sensing and structural analysis in groundwater exploration in basement terrains, Darfur region, Western Sudan

Darfur region is one of the most vulnerable areas in Sudan that suffer from shortage in water supply. The objective of the current study is to utilize remote sensing techniques combined with the structural analysis to recognize the most potential fracture zones for groundwater occurrences in the hard rock terrains of Darfur region. The old ductile deformation features in Darfur region delineated from Landsat imageries are used for the structural analysis to determine and classify the fractures in the hard rock terrains of the region. Based on the structural analysis conducted in this study, Darfur region was divided into two domains—the western domain of the pre-Pan-African age that is affected by the two deformational phases (D1 and D2), and the eastern domain represented by the basement related to the Pan-African orogeny. The most potential fractures in the western domain are in the NW–SE and NE–SW trends that classified as extensional and release open fractures for the deformations D1 and D2. In the eastern domain, the main potential fractures for groundwater occurrence are in E–W and N–S directions that are classified as extensional and release open fractures of the deformation D3. From the results of the structural analysis, the main potential fracture systems in Darfur region trend are NW–SE, NE–SW, and E–W directions. The intersections of these fracture systems are the most promising targets for drilling, with consideration of the topography, the rates of recharge, and the underlying geology. The geophysical data and boreholes information in Zalingei and north of El Geneina areas in West Darfur confirm the results obtained from remote sensing data and structural analysis, in which the NW–SE, NE–SW, and E–W fractures trends are the most potential fractures in Darfur region.     

Bayesian Reservoir History Matching Considering Model and Parameter Uncertainties

This paper presents a consistent Bayesian solution for data integration and history matching for oil reservoirs while accounting for both model and parameter uncertainties. The developed method uses Gaussian Process Regression to build a permeability map conforming to collected data at well bores. Following that, an augmented Markov Chain Monte Carlo sampler is used to condition the permeability map to dynamic production data. The selected proposal distribution for the Markov Chain Monte Carlo conforms to the Gaussian process regression output. The augmented Markov Chain Monte Carlo sampler allows transition steps between different models of the covariance function, and hence both the parameter and model space are effectively explored. In contrast to single model Markov Chain Monte Carlo samplers, the proposed augmented Markov Chain Monte Carlo sampler eliminates the selection bias of certain covariance structures of the inferred permeability field. The proposed algorithm can be used to account for general model and parameter uncertainties.     

Groundwater balance in the Khor Arbaat basin, Red Sea State, eastern Sudan

The Khor Arbaat basin is the main source of potable water supply for the more than 750,000 inhabitants of Port Sudan, eastern Sudan. The variation in hydraulic conductivity and storage capacity is due to the heterogeneity of the sediments, which range from clay and silt to gravely sand and boulders. The water table rises during the summer and winter rainy seasons; it reaches its lowest level in the dry season. The storage capacity of the Khor Arbaat aquifer is estimated to be 21.75?×?10⁶ m³. The annual recharge through the infiltration of flood water is about 1.93?×?10⁶ m³. The groundwater recharge, calculated as underground inflow at the ‘upper gate’, is 1.33?×?10⁵ m³/year. The total annual groundwater recharge is 2.06?×?10⁶ m³. The annual discharge through underground outflow at the ‘lower gate’ (through which groundwater flows onto the coastal plain) is 3.29?×?10⁵ m³/year. Groundwater discharge due to pumping from Khor Arbaat basin is 4.38?×?10⁶ m³/year on average. The total annual groundwater discharge is about 4.7?×?10⁶ m³. A deficit of 2.6?×?10⁶ m³/year is calculated. Although the total annual discharge is twice the estimated annual recharge, additional groundwater flow from the fractured basement probably balances the annual groundwater budget since no decline is observed in the piezometric levels.     

The geometric configuration of the newly discovered Abu Deleig sedimentary sub-basin,Central Sudan,using remote sensing,structural analysis,and geophysical survey

Abu Deleig area is a transitional area between the Butana basement terrain to the east; and the Khartoum and Shendi sedimentary basins to the west and northwest directions, respectively. The existence of sedimentary basins within this region of Sudan was previously unknown. Landsat images have been used for delineation of lineaments and drainage system, followed by a structural analysis and geophysical investigations including gravity and resistivity methods. The interpretation of the remotely sensed data revealed that the drainage pattern is structurally controlled. The structural analysis defined the trends of the shear and tensional fractures. The structural analysis revealed that Wadi Al Hawad is the southern continuation of the Keraf Shear Zone. The related minor fractures in a NE–SW direction exhibit normal faults governing the geometry of the Abu Deleig sub-basin. The geophysical investigations confirmed the findings of structural analysis and portrayed the subsurface geometry of the sub-basin. The newly discovered sub-basin has a prism-like shape with its apex occurring at Abu Deleig town and extends to 40 km in NW direction. The depth to the basement increases from 20 m at Abu Deleig in step form to more than 300 m, where it is linked with the Shendi Basin in the northwestern part. The results of this study, however, did not confirm any link of Abu Deleig sub-basin with Atbara Basin to the NE or Khartoum Basin to the west as have been previously suggested.     

Robust optimisation of CO2 sequestration strategies under geological uncertainty using adaptive sparse grid surrogates

Geologic CO₂ sequestration in deep saline aquifers is a promising technique to mitigate the effect of greenhouse gas emissions. Designing optimal CO₂ injection strategy becomes a challenging problem in the presence of geological uncertainty. We propose a surrogate assisted optimisation technique for robust optimisation of CO₂ injection strategies. The surrogate is built using Adaptive Sparse Grid Interpolation (ASGI) to accelerate the optimisation of CO₂ injection rates. The surrogate model is adaptively built with different numbers of evaluation points (simulation runs) in different dimensions to allow automatic refinement in the dimension where added resolution is needed. This technique is referred to as dimensional adaptivity and provides a good balance between the accuracy of the surrogate model and the number of simulation runs to save computational costs. For a robust design, we propose a utility function which comprises the statistical moment of the objective function. Numerical testing of the proposed approach applied to benchmark functions and reservoir models shows the efficiency of the method for the robust optimisation of CO₂ injection strategies under geological uncertainty.     

Extraction of High Purity Bischofite (MgCl2.6H2O) from Left Over-Resiudal Bittren, Lake Quroun, Egypt

正1 Introduction The left-over(residual)brines often in industrial facilities is disposed back to the sea or in dump areas e.g.abundant salt mines in other cases.Dumping into the sea