Analysis of CH_(4) and H_(2) Adsorption on Heterogeneous Shale Surfaces Using aMolecular Dynamics Approach

Determining the adsorption of shale gas on complex surfaces remains a challenge in molecular simulation studies.Difficulties essentially stem from the need to create a realistic shale structure model in terms of mineral heterogeneityand multiplicity.Moreover,precise characterization of the competitive adsorption of hydrogen andmethane in shale generally requires the experimental determination of the related adsorptive capacity.In thisstudy,the adsorption of adsorbates,methane(CH_(4)),and hydrogen(H_(2))on heterogeneous shale surface modelsof Kaolinite,Orthoclase,Muscovite,Mica,C_(60),and Butane has been simulated in the frame of a moleculardynamic’s numerical technique.The results show that these behaviors are influenced by pressure and potentialenergy.On increasing the pressure from 500 to 2000 psi,the sorption effect for CH_(4)significantly increasesbut shows a decline at a certain stage(if compared to H_(2)).The research findings also indicate that raw shalehas a higher capacity to adsorb CH_(4)compared to hydrogen.However,in shale,this difference is negligible.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Exploratory and Descriptive Study of the Kimberlite Massif of Boya-02 at Eastern Kasai in the Democratic Republic of Congo

The Boya-02 kimberlite was identified at depth by geophysical survey work (a single-probe AM survey in 1997 and a gravity survey in 2006) that De Beers DRC Exploration carried out around anomaly 193/172/0019. This anomaly located approximately 50 km southwest of the town of Mbuji-Mayi in the Kasaï-Oriental Province in the DRC should therefore be the subject of detailed exploration with the aim of better identifying and describing this kimberlite. Thus, through exploratory work and cross-checking of geophysical and geological data, the discovery of this Massif was made by drilling on the aeromagnetic anomaly 193/172/X298. Based on drilling, sampling and laboratory petrographic analysis reports, the Boya-02 kimberlite was classified among highly diluted re-sedimented volcaniclastic kimberlites (KVR), rich in olivine and incidentally in quartz and poor in juvenile substances. This kimberlite represents a deposit of very low economic interest following extremely high dilution. The Boya-02 kimberlite was modeled using ground magnetism data. It is a complex anomaly comprising 2 components with variable amplitude appearing on a subtly magnetized linear detail. The modeled dimensions of two components of this anomaly are 0.32 Ha and 0.2 Ha at depths of 32 m & 14 m for the deposits to the West and the East respectively. Garnet data for the Boya-02 occurrence reports a maximum Pmin value of 49.7 kbar (207 garnets). These data demonstrate the high diamond potential which assumes a conductive cratonic geotherm of 40 mWm2.

An Assessment of Saltwater Intrusion in Coastal Regions of Lagos, Nigeria

This paper explains various factors that contribute to saltwater intrusion, including overexploitation of freshwater resources and climate change as well as the different techniques essential for effective saltwater intrusion management. The impact of saltwater intrusion along coastal regions and its impact on the environment, hydrogeology and groundwater contamination. It suggests potential solutions to mitigate the impact of saltwater intrusion, including effective water management and techniques for managing SWI. The application of A.I (assessment index) serves as a guideline to correctly identify wells with SWI ranging from no intrusion, slight intrusion and strong intrusion. The challenges of saltwater intrusion in Lagos and the salinization of wells were investigated using the hydro-chemical parameters. The study identifies four wells (“AA”, “CMS”, “OBA” and “VIL”) as having high electric conductivities, indicating saline water intrusion, while other wells (“EBM”, “IKJ, and “IKO”) with lower electric conductivities, indicate little or no salt-water intrusion, and “AJ” well shows slight intrusion. The elevation of the wells also played a vital role in the SWI across coastal regions of Lagos. The study recommends continuous monitoring of coastal wells to help sustain and reduce saline intrusion. The findings of the study are important for policymakers, researchers, and practitioners who are interested in addressing the challenges of saltwater intrusion along coastal regions. We assessed the SWI across the eight (8) wells using the Assessment Index to identify wells with SWI. Wells in “CMS” and “VIL” has strong intrusions. A proposed classification system based on specific ion ratios categorizes water quality from good (+) to highly (-) contaminated (refer to Table 4). These findings underscore the need for attention and effective management strategies to address groundwater unsuitability for various purposes.

Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors

To perform landslide susceptibility prediction(LSP),it is important to select appropriate mapping unit and landslide-related conditioning factors.The efficient and automatic multi-scale segmentation(MSS)method proposed by the authors promotes the application of slope units.However,LSP modeling based on these slope units has not been performed.Moreover,the heterogeneity of conditioning factors in slope units is neglected,leading to incomplete input variables of LSP modeling.In this study,the slope units extracted by the MSS method are used to construct LSP modeling,and the heterogeneity of conditioning factors is represented by the internal variations of conditioning factors within slope unit using the descriptive statistics features of mean,standard deviation and range.Thus,slope units-based machine learning models considering internal variations of conditioning factors(variant slope-machine learning)are proposed.The Chongyi County is selected as the case study and is divided into 53,055 slope units.Fifteen original slope unit-based conditioning factors are expanded to 38 slope unit-based conditioning factors through considering their internal variations.Random forest(RF)and multi-layer perceptron(MLP)machine learning models are used to construct variant Slope-RF and Slope-MLP models.Meanwhile,the Slope-RF and Slope-MLP models without considering the internal variations of conditioning factors,and conventional grid units-based machine learning(Grid-RF and MLP)models are built for comparisons through the LSP performance assessments.Results show that the variant Slopemachine learning models have higher LSP performances than Slope-machine learning models;LSP results of variant Slope-machine learning models have stronger directivity and practical application than Grid-machine learning models.It is concluded that slope units extracted by MSS method can be appropriate for LSP modeling,and the heterogeneity of conditioning factors within slope units can more comprehensively reflect the relationships between conditioning factors and landslides.The research results have important reference significance for land use and landslide prevention.

Tectonic and climatic controls for fluvial terraces of the Yellow River over the past 2.6 Ma at Northeast Tibetan Plateau and Ordos Block

The Yellow River is usually assumed to record tectonic activities and climatic changes;however,a systematic study was lack in the sedimentology,stratigraphy,geomorphology and geochronology for the entire Yellow River though various geologic scholars have conducted numerous works in individual basins.This review focused on well-preserved fluvial terrace sequences that formed along this river on northeastern(NE)Tibetan Plateau and Ordos Block over the past 2.6 Ma.After comparing numerous initial incision ages at different segments along the Yellow River,we found out that the youngest initial incision may occur at ca.150 ka at the Longyang Gorge.The Yellow River may transit from multiple separated endorheic drainages to an entire external drainage after 150 ka,which may cause differentiations in the apparent incision rates before and after 150 ka;thus apparent net incision rates were calculated respectively for the Yellow River before 150 ka and the drainage network post 150 ka.Apparent net incision rates prior to 0.15 Ma were calculated as 0.15,0.29,0.10,0.12 and 0.03 mm/a respectively in Tongde-Xunhua,Lanzhou-Linxia basins,Heishan,Jinshan and Fenwei-Sanmen Gorges in this review,which mainly reflected Kunhuang-Gonghe Tectonic Event,generated by the Indo-Asian collision and diminishing as the NE Tibetan Plateau eastward extruding at ca.1.8-0.15 Ma.Apparent net incision rates post 0.15 Ma were calculated respectively for NE Tibetan Plateau and Ordos Block,considering their different base level.On NE Tibetan Plateau,four fluvial degradational phases were identified between ca.105~70,53~40,25~16 and 12~6 ka associated with terrace levels respectively,at average elevations of 96,40,20 and 10.5 meters above the current river level(m arl)within a range of 5~96 m arl;and four broad periods in the last 150 ka on Ordos Block:possibly marine oxygen isotope stage(MIS)5,ca.118 to 72 ka,most of MIS 3,ca.44~28 ka,transition from LGM to last deglacial ca.20 to 16 ka,and 4~3 ka at average elevations of 67.5,26,19 and 11.5 m arl.These degradational phases post 0.15 Ma were associated with multiple processes including enhanced fluvial discharge with an increase in monsoonal precipitation and/or melt water in deglaciation.

Erosion wear at the bend of pipe during tailings slurry transportation:Numerical study considering inlet velocity,particle size and bend angle

Pipeline hydraulic transport is a highly efficient and low energy-consumption method for transporting solids and is commonly used for tailing slurry transport in the mining industry.Erosion wear(EW)remains the main cause of failure in tailings slurry pipeline systems,particularly at bends.EW is a complex phenomenon influenced by numerous factors,but research in this area has been limited.This study performs numerical simulations of slurry transport at the bend by combining computational fluid dynamics and fluid particle tracking using a wear model.Based on the validation of the feasibility of the model,this work focuses on the effects of coupled inlet velocity(IV)ranging from 1.5 to 3.0 m·s^(-1),particle size(PS)ranging from 50 to 650μm,and bend angle(BA)ranging from 45°to 90°on EW at the bend in terms of particle kinetic energy and incidence angle.The results show that the maximum EW rate of the slurry at the bend increases exponentially with IV and PS and first increases and then decreases with the increase in BA with the inflection point at 60°within these parameter ranges.Further comprehensive analysis reveals that the sensitivity level of the three factors to the maximum EW rate is PS>IV>BA,and when IV is 3.0 m/s,PS is 650μm,and BA is 60°,the bend EW is the most severe,and the maximum EW rate is 5.68×10^(-6)kg·m^(-2)·s^(-1).In addition,When PS is below or equal to 450μm,the maximum EW position is mainly at the outlet of the bend.When PS is greater than 450μm,the maximum EW position shifts toward the center of the bend with the increase in BA.Therefore,EW at the bend can be reduced in practice by reducing IV as much as possible and using small particles.

Uncertainties of landslide susceptibility prediction considering different landslide types

Most literature related to landslide susceptibility prediction only considers a single type of landslide,such as colluvial landslide,rock fall or debris flow,rather than different landslide types,which greatly affects susceptibility prediction performance.To construct efficient susceptibility prediction considering different landslide types,Huichang County in China is taken as example.Firstly,105 rock falls,350 colluvial landslides and 11 related environmental factors are identified.Then four machine learning models,namely logistic regression,multi-layer perception,support vector machine and C5.0 decision tree are applied for susceptibility modeling of rock fall and colluvial landslide.Thirdly,three different landslide susceptibility prediction(LSP)models considering landslide types based on C5.0 decision tree with excellent performance are constructed to generate final landslide susceptibility:(i)united method,which combines all landslide types directly;(ii)probability statistical method,which couples analyses of susceptibility indices under different landslide types based on probability formula;and(iii)maximum comparison method,which selects the maximum susceptibility index through comparing the predicted susceptibility indices under different types of landslides.Finally,uncertainties of landslide susceptibility are assessed by prediction accuracy,mean value and standard deviation.It is concluded that LSP results of the three coupled models considering landslide types basically conform to the spatial occurrence patterns of landslides in Huichang County.The united method has the best susceptibility prediction performance,followed by the probability method and maximum susceptibility method.More cases are needed to verify this result in-depth.LSP considering different landslide types is superior to that taking only a single type of landslide into account.

The gravity field and gravity data reduction across the continental area of Nigeria

This research presents the variation of the gravity field and associated gravity field components over the continental area of Nigeria to provide data for geoscience research,geodetic and engineering works,aerodynamic studies and deep crustal inferences.Accurate positions and elevations were observed at 58 of the 59 base stations of the Primary Gravity Network of Nigeria(PGNN),whose absolute gravity values had been accurately determined.The absolute gravity values were plotted against their respective positions to reveal the distribution pattern and strength of the gravity field within the study area.Theoretical gravity values at each base station were generated using the Somigliana's equation.The free-air gravity and free-air anomaly gravity values were generated with respect to the World Geodetic System 1984(WGS84)ellipsoid using GPS-derived elevation data.Then,the perturbing potential,free-air gravity with respect to the geoid,and the indirect effects were evaluated.The average of the indirect effects was used to adjust the WGS84 gravity formula to produce a gravity formula that better approximates the geoid across the continental area of Nigeria,compatible with the heights measured relative to the geoid,which can serve as a reference for establishing a vertical height control.The Bouguer gravity and Bouguer gravity anomalies across Nigeria revealed a“trans-southern gravity high strip”interpreted to be associated with mantle upwelling.Two new major mega-lineaments related to mantle upwelling were mapped.A batholith province trending NWeSE was delineated,occurring from north central Nigeria to the north western region and containing closures of“Bouguer gravity lows”interpreted as batholiths.A separate closure of“Bouguer gravity low”was detected at Azare,north eastern Nigeria,which may be due to the presence of intrusive granitic body.It is recommended that the mantle structure beneath“the trans-southern gravity high strip”,“delineated batholith province”and“isolated gravity closures”around the northeast of Nigeria should be studied from seismic shear wave splitting analysis for better understanding of the deep lithospheric structures and moho relief.

Soft ground tunnel lithology classification using clustering-guided light gradient boosting machine

During tunnel boring machine(TBM)excavation,lithology identification is an important issue to understand tunnelling performance and avoid time-consuming excavation.However,site investigation generally lacks ground samples and the information is subjective,heterogeneous,and imbalanced due to mixed ground conditions.In this study,an unsupervised(K-means)and synthetic minority oversampling technique(SMOTE)-guided light-gradient boosting machine(LightGBM)classifier is proposed to identify the soft ground tunnel classification and determine the imbalanced issue of tunnelling data.During the tunnel excavation,an earth pressure balance(EPB)TBM recorded 18 different operational parameters along with the three main tunnel lithologies.The proposed model is applied using Python low-code PyCaret library.Next,four decision tree-based classifiers were obtained in a short time period with automatic hyperparameter tuning to determine the best model for clustering-guided SMOTE application.In addition,the Shapley additive explanation(SHAP)was implemented to avoid the model black box problem.The proposed model was evaluated using different metrics such as accuracy,F1 score,precision,recall,and receiver operating characteristics(ROC)curve to obtain a reasonable outcome for the minority class.It shows that the proposed model can provide significant tunnel lithology identification based on the operational parameters of EPB-TBM.The proposed method can be applied to heterogeneous tunnel formations with several TBM operational parameters to describe the tunnel lithologies for efficient tunnelling.

Reservoir characteristics of Datta Formation (Early Jurassic), Marwat-Khisor Ranges, sub-Himalayas, Pakistan

The present work has been accomplished to carry out a detailed study of the characteristics of the Early Jurassic Datta Formation of Trans-Indus Ranges, Pakistan. The discovery of Saib well-1 (Gas and condensate discovery from Jurassic limestone) in the study basin takes an active interest in carrying out extensive exploration activities in the same basin. Jurassic rocks especially Datta Sandstone and Samana Suk Limestone are acting as good reservoirs. The study unit consists of variegated sandstone interbedded with siltstone, carbonaceous clay, and shale and coal stringer. For the current work, two stratigraphic sections (Pezu and Abbo Wanda) have been measured. To examine its sedimentology, depositional environment, diagenetic settings, and reservoir characteristics, a detailed study was conducted and various laboratory techniques have been utilized. About 95 rock samples from the bottom to the top of both sections were collected, and 50 rock samples have been selected for thin section analysis and were examined under a polarizing microscope to show their mineralogical composition, diagenesis, and their reservoir characteristics. XRD (X-ray diffraction), Cathodoluminescence (CL), SEM (Scanning electron microscope) with EDS (Energy-dispersive spectroscope), and Core plug porosity and permeability analysis have been used to interpret its chemical and mineralogical composition and its reservoir characteristics, respectively. Based on field observations and thin section analysis, four depositional facies and six lithofacies have been established. The sedimentary structures, depositional facies, and lithofacies indicate that Datta Formation was deposited in a deltaic environment. Compactions, cementation, fracturing and dissolution can greatly affect the quality of reservoir rock. Based on thin section and SEM analysis, large numbers of primary pores, fracture and secondary pores were observed and connectivity between the pores is good, and at some places, these pores were filled through the authigenic clay minerals like kaolinite, mixed layers illite/smectite and chlorite that influences the reservoir characteristics. Primary pores (thin section) and secondary pores (dissolution pores) and core plug porosity and permeability data (porosity 13.23%-26.89% and permeability 0.12 to 149 mD) shows that Datta Formation has a good reservoir quality.

Challenges in the Detection and Attribution of Northern Hemisphere Surface Temperature Trends Since 1850

Since 2007,the Intergovernmental Panel on Climate Change(IPCC)has heavily relied on the comparison between global climate model hindcasts and global surface temperature(ST)estimates for concluding that post-1950s global warming is mostly human-caused.In Connolly et al.,we cautioned that this approach to the detection and attribution of climate change was highly dependent on the choice of Total Solar Irradiance(TSI)and ST data sets.We compiled 16 TSI and five ST data sets and found by altering the choice of TSI or ST,one could(prematurely)conclude anything from the warming being“mostly human-caused”to“mostly natural.”Richardson and Benestad suggested our analysis was“erroneous”and“flawed”because we did not use a multilinear regression.They argued that applying a multilinear regression to one of the five ST series re-affirmed the IPCC's attribution statement.They also objected that many of the published TSI data sets were out-of-date.However,here we show that when applying multilinear regression analysis to an expanded and updated data set of 27 TSI series,the original conclusions of Connolly et al.are confirmed for all five ST data sets.Therefore,it is still unclear whether the observed warming is mostly human-caused,mostly natural or some combination of both.

A Five-stage Evolution of Earth's Phosphorus Cycle

Phosphorus(P)is a key biological nutrient and probably the ultimate limiter of marine productivity during Earth history.In recent years,a wealth of new knowledge has revolutionized our understanding of the global P cycle,yet its longterm evolution remains incompletely documented.In this paper,we review the effects of three major controlling factors on the long-term evolution of the global P cycle,i.e.,tectonics,marine redox conditions,and bio-evolution,on the basis of which a five-stage model is proposed:StageⅠ(>~2.4 Ga),tectonic-lithogenic-controlled P cycling;StageⅡ(~2.4 Ga to 635Ma),low-efficiency biotic P cycling;StageⅢ(~635 Ma to 380 Ma),transitional biotic P cycling;StageⅣ(~380 Ma to near-modern),high-efficiency biotic P cycling;and Stage V(Anthropocene),human-influenced P cycling.This model implies that the earlier-proposed Ediacaran reorganization of the marine P cycle may represent only the start of a-250-Myr-long transition of the Earth's P cycle(StageⅢ)between the low-efficiency biotic mode of the Proterozoic(StageⅡ)and the high-efficiency biotic mode of the Phanerozoic(StageⅣ).The development of biologically-driven,high-efficiency P cycling may have been a key factor for the increasing frequency and volume of phosphorite deposits since the late Neoproterozoic.

Magmatic Evolution of the Western Branch of the East African Rift System Melts: Evidence by Silicate Melt Inclusions, Rock Petrography and Geochemistry of the Nyiragongo 1977 and 2002 Lavas in DRC

Nyiragongo volcanic eruptions of 1977 and 2002 emitted silica-undersaturated lavas named melilite-nephelinites with microlithic to sub-porphyritic textures, and consisted of olivine, clinopyroxene (augite), phlogopite, melilite, magnetite, and rare plagioclases. This melilite-nephelinite as an evolved rock, shows low SiO2 (38.40 - 39.52 wt%) and MgO (3.10 - 4.01 wt%), and relatively high FeOt (13.76 - 14.10 wt%), Al2O3 (15.01 - 16.48 wt%), CaO (11.00 - 12.29 wt%) and Na2O + K2O (10.34 - 11.85 wt%). Unlike LA-ICP-MS on silicate melt inclusions (SMIs) hosted in augite show a pristine melt of picrobasaltic (low Ti-picrite) rock poor in SiO2 (31.14 - 32.26 wt%), FeOt (2.19 - 2.79 wt%), Al2O3 (8.01 - 9.57 wt%), and Na2O + K2O (2.34 - 3.05 wt%), while enriched in MgO (20.27 - 28.63 wt%), and CaO (24.95 - 33.17 wt%). The sums (∑REEs) for lavas and SMIs are ranging 712 - 799 and 43 - 119 ppm respectively. REE contracted multi-element patterns showed a W-feature for most lavas except for SMIs. High Rb/Sr, and low Ba/Rb, Zr/Nb, and Sm/Hf ratios of lavas suggest a phlogopite-rich source of materials. .

Geochemistry and Petrogenesis of Basic and Ultrabasic Rocks Elogo Complex in Ivindo Archean Block (Congo Craton): Geodynamic Implications

The Elogo complex is a greenstone belt portion located on the Eastern edge of the Archean Congo craton at the junction with the Paleoproterozoic to Neoproterozoic Sembe Ouesso basin. This study was carried out on this complex to determine the context of the placement of basaltic rocks. Metaluminous tholeiitic basalts (basic and ultrabasic), calc-alkaline basalts, andesitic basalts, and peraluminous calc-alkaline dacites represent greenstones. Tholeiitic and calc-alkaline basalts come from deep enriched and depleted mantle sources, including garnet in fusion residues [Al2O3/TiO2 > 16 (16.5 to 35.12) and in some samples between 12.45 to 14.48;CaO/Al2O3 1 (1.04 to 1.35) in ten samples and (Gb/Yb)PM > 1]. The calc-alkaline dacites come from a shallow depleted mantle source [Al2O3/TiO2 > 16;CaO/Al2O3 1]. Tholeiitic and calc-alkaline basalts have a negative Rb, Ba, Ce, and Nb anomaly without negative Ti anomaly, positive Ta, Pb anomalies, and a lack of significant REE [(La/Yb)n = 0.36 to 0.97 and 1 to 2.15;(Ce/Yb)n = 0.27 to 0.96 and 1.04 to 1.72, respectively] fractionation. High Nb/Th (2 to 10) and Nb/U (1.82 to 26) ratios and low La/Ta (5 to 27) ratios are characteristic of divergent margin magmatic sources. Tholeiitic and calc-alkaline basalts correspond to an extensive back-arc basin-type tectonic setting. Calc-alkaline andesitic basalts and dacites show positive Ba, U, Th, K, La, Ce, Pb, and Li anomalies and negative Nb, Ta, and Ti anomalies reflecting crustal contamination and hydrothermal alteration in a compressive tectonic context as a volcanic arc in a subduction regime marking the interruption of the meso-neoarchean Elogo’s opening. Elogo’s opening and closing are probably associated with the emplacement of the greenstone of the meso-neoarchean Gabon Belinga group and the relics of the Mesoarchean greenstones of the Cameroun Ntem complex.

Integrating Aster Images Processing and Fieldwork for Identification of Hydrothermal Alteration Zones at the Oumjrane-Boukerzia District, Moroccan Anti-Atlas

Mapping from remote sensing has become more effective in the field of geology, mainly in lithological discrimination and identification of hydrothermal alteration zones. The use of this technique consists in obtaining information about the rock mass and the main ones existing in the inaccessible areas. Satellite data from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) sensor represent a favorable potential for detecting the spectral signatures of mineral zones and identifying their nature. These data are more reliable in places where the climate is arid with less abundant vegetation, as at the Oumjrane-Boukerzia mining district. This region which is part of the Eastern Anti-Atlas, is composed of several mineralized veins which still require detailed studies and exploration by the technique of remote sensing. In this work we applied several processing techniques on ASTER imagery such as Colored Composition, Principal Component Analysis and Ratio Bands. The use of the reports of the specialized Bands makes it possible to identify some hydrothermal alteration minerals within the mining district of Oumjrane Boukerzia. These minerals are represented mainly by iron oxides and hydroxides (Hematite, jarosite, limonite and goethite), carbonate minerals (dolomite, calcite), clay minerals (Illite, kaolinite and chlorite) and quartz minerals. This work allows us to produce a map of hydrothermal alteration zones which can be used as a valuable reference in the strategy of mining exploration for the base metals (Cu, Pb, Zn and Ba), in the mining district of Oumjrane-Boukerzia and in the entire Eastern Anti-Atlas.

Effects of the Produced Water from a Sour Oilfield in South Kuwait on the Production Tubing

Kuwaiti oil production faces a growing challenge in the increasing quantities of produced water generated in the production of oil. The high water cut of the produced fluid from the wells and the high salinity of the produced water lead to significant degradation of subsurface equipment, specifically the production tubing. Debris generated through the degradation of the inner part of the tubing becomes a constituent of the scaling that deposits in the tubing and blocks the flow of the production fluid, inducing higher maintenance costs. This paper looks at the characteristics of the scaling in regard to the produced water and outlines the economic impact of the produced water induced degradation of the tubing structure.

Estimation of the Actual Evapotranspiration by the SEBAL Method in the Irrigated Rice Perimeter of Zatta (Yamoussoukro—Côte d’Ivoire)

In this study, the SEBAL (Surface Energy Balance Algorithm for Land) model was used to map the spatio-temporal distribution of actual evapotranspiration in the Yamoussoukro department (Côte d’Ivoire). Like other regions of the country, the Yamoussoukro district is confronted with the phenomenon of evapotranspiration (ET). This is a very important component that comes into play in the water balance but also in the calculation of the water needs of agricultural crops. Consequently, its estimation is of paramount importance in research related to the rational management of water resources, particularly agricultural water. The objective of this study was to analyze the spatio-temporal distribution of actual evapotranspiration (AET) as a function of land cover and land use. The methodology used is based on the SEBAL model which uses remote sensing (Landsat 8_OLI/TIRS) and climatic data to estimate actual evapotranspiration and analyze the spatio-temporal distribution of AET. The results reveal that the AET varied from 0 to 5.44 mm/day over the period from December 2019 to February 2020 with an average value of 4.92 mm/day. The highest average values occurred for water bodies (4.90 mm/day) and flooded vegetation (4.88 mm/day) while the lowest values occurred in residential areas (2.04 mm/day). Furthermore, the results show that the difference between the SEBAL model and the FAO-Penman-Monteith method is minimal with an average RMSE of 0.36 mm/day for all the satellite images. This study demonstrates the considerable potential of remote sensing for the characterization and estimation of spatial evapotranspiration in the Zatta irrigated rice-growing area.

Pre-rig mobilization hazard evaluation in offshore oil and gas prospect drilling:A case study of TM field,offshore Niger Delta

TM Field,located offshore Niger Delta in the Gulf of Guinea(Nigeria),has been evaluated for potential drilling hazards prior to the drilling of a proposed oil well.This is in a region where potential hazards that could inhibit successful drilling exercise have not been adequately studied.The study adopted the modern technique of offshore geohazard evaluation that relies mainly on suites of geophysical and shallow geological investigations which include ocean bathymetry using multi-beam echo sounder,sidescan sonar,sub-bottom profiler,magnetic,and 2D-high resolution seismic reflection surveys.The results were integrated to draw inferences about the risk potential of the field.From the bathymetric survey,water depths were found to range from 345 m to 650 m LAT,with seabed relief being 305 m.Water depth at the proposed well location was found to be approximately 450 m and the seabed was found to slope in the northwestern direction.Seafloor gradient was computed as 0.05 across the whole area.Two shallow sub-surface stratigraphic units,labelled A and B,were delineated.Unit A was directly beneath the seafloor and seemed to be composed mainly of clayey/silty sand.Its thickness ranged from 6 m to 70 m across the study area.Unit B appeared to be a layer of sand and its total thickness was not fully delineated.Observable kinks and displacements at the flanks of seabed undulations/depressions on subbottom profiler sections suggested that the depressions may be fault-controlled.On the map generated from the marine magnetic data,a magnetic fault was delineated and this appeared to be coincident with the shallower of the two buried faults on the cross-line seismic section cutting through the proposed well-head location.Interpreted seismic reflection data presented this fault as being inactive.Most of the faults mapped,especially the buried ones,appeared to be inactive except a few.Regions with mapped amplitude anomalies are to be avoided during rig-mobilization operations.Though engineering conditions are expected to vary vertically since layers occur as intercalation,significant lateral variation is not expected within uniform layers of bed.Risk of punch-through associated with clayey formation is expected to be low because the geologic layers are not uniformly and entirely clay.The proposed wellhead location was found to be free of potential hazard sources.

Cu-Bearing Mokama Granite Prospect of the Kibara Belt in the Maniema Province, DRC: A Preliminary Petrography, Geochemistry, and Fluid Inclusion Study

The Mokama granites are located in the Kibara belt (KIB) and hosts tin oxide group minerals (TOGM: Sn-W), and sulfide group minerals (SGM: Cu-Zn-Fe-As). The essential of Cu mineralization (non-economic deposit) is disseminated inside the rock and consists of minerals (Raman, EPMA and metallographic microscopy) including chalcopyrite and bornite that are replaced by chalcocite and covellite, and the last also replaced later by malachite. The chemistry (XRF, LA-ICP-MS) of these peraluminous S-type leucogranites show SiO2 (71 wt% - 79 wt%), ASI (1.4 - 3.1 molar), and are enriched in Rb (681 - 1000 ppm), Ta (12–151 ppm), Sn (43 - 142 ppm), Cu (10 - 4300 ppm), Zn (60 - 740 ppm), U (2.2 - 20.7 ppm) while depleted in Zr (20 - 31 ppm), Sr (20 - 69 ppm), Hf (1.3 - 2.0 ppm), Th (2.2 - 18.9 ppm), W (9 - 113 ppm), Pb (5 - 50 ppm), Ge (5 - 10 ppm), Cs (21 - 53 ppm) and Bi (0.6 - 17.4 ppm) and low ratios of (La/Yb) N, (Gd/Yb) N, (La/Sm) N). Fluid inclusion assemblages (FIAs) hosted in quartz in the Mokama granites show ranges of salinities of 4 - 23 wt% (NaCl equivalent) and homogenization temperatures (Th) of 190°C - 550°C. A boiling assemblage in the granite suggests a fluid phase separation occurred at about 380 - 610 bars, and this corresponds to apparent paleodepths of approximately 1 - 2 km (lithostatic model) or 3 - 5 km (hydrostatic model). FIAs hosted in TOGM such as cassiterite (salinities of 2 wt% - 10 wt% and Th of 220°C - 340°C) helped set up the possible temperature limit of SGM (Cu sulfide) precipitations that are estimated below 200°C.