Seasonal influence of freshwater discharge on spatio-temporal variations in primary productivity, sea surface temperature, and euphotic zone depth in the northern Bay of Bengal

Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on land.Spatio-temporal variability of net primary productivity(NPP),sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(MLD),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three monsoon seasons were examined in this study based on remote sensing data for the period 2005 to 2020.To compare the NPP distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that most productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sediment and nutrient loads.Across Z1-Z5,the NPP ranges from 5 315.38 mg/(m^(2)·d) to 346.7 mg/(m^(2)·d)(carbon,since then the same).The highest monthly average NPP of 5 315.38 mg/(m^(2)·d) in February and 5 039.36 mg/(m^(2)·d) in June were observed from Z2,while the lowest monthly average of 346.72 mg/(m^(2)·d) was observed in March from Z4,which is an oceanic zone.EZD values vary from 6-154 m for the study area,and it has an inverse correlation with NPP concentration.EZD is deeper during the summer season and shallower during the wintertime,with a corresponding increase in productivity.Throughout the year,monthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation among NPP,and EZD,overall positive between NPP and MLD,whereas no significant correlation among SSS,and SST for the northern BoB.Long-term trends in SST and productivity were significantly po sitive in head bay zones but negatively productive in the open ocean.The findings in this study on the distribution of NPP,SST,SSS,MLD,and EZD and their seasonal variability in five different zones of BoB can be used to further improve the management of marine resources and overall environmental condition in response to climate changes in BoB as they are of utmost relevance to the fisheries for the three bordering countries.

3D reservoir characterization of the Mangahewa Formation,Mangahewa Field,Taranaki Basin,New Zealand

The Mangahewa Formation is the primary reservoir target in the Mangahewa Field in the Taranaki Basin,New Zealand.This formation is distinguished by its marginal marine substantial tight-sand reservoir,having thickness exceeding 800 m.The aim of this study is to assess the reservoir properties of the Mangahewa Formation through 3D reservoir modeling,employing 3D seismic data,core data,and well data from the Mangahewa Field.Utilizing variance attributes,the faults and horizons have been identified successfully within the field.The majority of the interpreted faults exhibit dip angles exceeding 60°,with a maximum displacement of 118 m.To detect direct hydrocarbon indicators,root-mean-square amplitude seismic attribute,envelope,and generalized spectral decomposition techniques have been employed.Subsequently,four lithofacies,comprising 78.3%sandstone,9.2%siltstone,9.5%claystone,and 3.0%coal have been established by utilizing the Sequential Indicator Simulation(SIS)algorithm to create a lithofacies model.A property model has been generated using the Sequential Gaussian Simulation(SGS)algorithm.Petrophysical evaluation indicates that the Mangahewa Formation exhibits reservoir qualities ranging from fair to good,with porosity levels between 8%and 11%,permeability averaging up to 10 mD,variable shale volumes,and hydrocarbon saturation in the range of 40%-50%.This study's methodologies and findings can serve as a valuable foundation for similar investigations in other tightsand gas fields located in different regions.

Reservoir quality of the Late Cretaceous Volador Formation of the Latrobe group,Gippsland Basin,Australia:Implications from integrated analytical techniques

Increasing demand for energy due to the populous Eastern Australia has driven oil and gas industries to find new sources of hydrocarbons as they are the primary energy suppliers.Intensive study has been done on the Volador Formation in the Gippsland Basin by means of core-based petrophysical,sedimentological,and petrographic analyses as well as well log-based interpretation and capillary pressure test.Five wells from Kipper,Basker and Tuna fields with available dataset were investigated in this study:Kipper-1,Basker-1,Basker-2,Basker-5 and Tuna-4.Overall,the formation has good reservoir quality based on the high porosity and permeability values obtained through core and well log petrophysical analyses.The formation made up of mostly moderate to coarse quartz grains that has experienced strong anti-compaction and is poorly cemented.Montmorillonite and illite clays are seen dispersed in the rock formation,with the minority being mixed clays.These clays and diagenetic features including kaolinite cement and quartz overgrowth that can lead to porosity reduction only have insignificant impact on the overall reservoir quality.In addition,capillary pressure data shows that most samples are found in the transition to good reservoir zones(<50%saturation).The results obtained from this study have shown that the Volador Formation in the Gippsland Basin is worth for hydrocarbon exploration.

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

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.

Seismic attribute and well-log analysis for channel characterization in the upper San Andres and Grayburg formations of the Midland Basin,Texas

The Permian Basin is one of the most prolific,and currently one of the most active,oil and gas basins in the USA.The Lower Permian strata in the Permian Basin have produced more than 14 billion barrels of oil(BBO),making it the largest volume of hydrocarbon in the basin.Sedimentation in the Midland Basin during late Leonardian through early Guadalupian(ca.272-269 Ma)resulted in progradation of shelf edge and ultimately closure of the basin by Middle Permian time.We analyzed a merged seismic survey covering parts of the Permian Basin(i.e.,Central Basin Platform and Midland Basin)in Andrews,Ector,and Midland Counties,Texas.The seismic survey and well logs show the presence of gently dipping(ca.1°)clinoforms in the Upper San Andres and Grayburg Formations on the eastern edge of the Central Basin Platform and western Midland Basin.The seismic attributes,curvature,and spectral decomposition identify low sinuosity slope channels oriented north-south,but such channels do not appear beyond the slope.The shelf edge shifts from north to south during deposition of the Upper San Andres and Grayburg Formations.We identify five basinward shifts noted by the migration of the shelf edge toward the basin center and the presence of channel features along the depositional slope.The petrophysical analysis indicates that channels cut into carbonate rocks and are filled by siliciclastic sediments;this interpretation is supported by the most negative curvature anomalies along the channel axes caused by the differential compaction between the carbonate and siliciclastic rocks.There are a few channels with a northwest-southeast strike,which matches the direction of the Concho Lineament observed by satellite data.Such observations are consistent with previous interpretations of the northern Midland Basin closure during Middle-Late Permian time.

Characterization of Aquifers in Crystalline and Crystallophyll Basement Zones Using the Electrical Resistivity Method (Trails and Electrical Soundings) in the Gagnoa Region, (Central-Western Côte d’Ivoire)

Introduction: Located in the central-western part of Côte d’Ivoire, the subsoil of the Gagnoa region is made up of sedimentary volcano formations and granitoids with developed fracturing. This complex Precambrian basement contains most of the region’s water resources. This is at the origin of the high failure rate during the various hydrogeological prospecting campaigns. Methodology: The database consists of resistivities from 42 holes and 51 trails drilled as part of the implementation of high-throughput drilling in the study area. The objective of this study is to deepen the knowledge of the fissured basement by interpreting profile curves and electrical soundings. It will be a question of classifying the different types of anomalies obtained on the profiles and their shapes. The orientation of the lineaments observed on the profiles was determined. Results: The interpretation of the geophysical data revealed various anomalies, the main ones being of the CC (Conductor Compartment) and CEDP (Contact between two bearings) types. These types of anomalies are mainly expressed in various forms: the “V”, “W” and “U” shapes. From these anomalies and the appearance of the electrical profiles, lineaments and their orientations were identified with N90-100, N130-140, N170-180 as major orientations. Conclusion: These results could contribute to a better understanding of the fractured environment of the Gagnoa region.

Application of the Electrical Resistivity Method in Precision Agriculture of Coffee Cultivation, in the Kabiri Area, Ícolo e Bengo Township, Luanda, Angola

The electrical resistivity method is a geophysical tool used to characterize the subsoil and can provide an important information for precision agriculture. The lack of knowledge about agronomic properties of the soil tends to affect the agricultural coffee production system. Therefore, research related to geoelectrical properties of soil such as resistivity for characterization the region of the study for coffee cultivation purposes can improve and optimize the production. This resistivity method allows to investigate the subsurface through different techniques: 1D vertical electrical sounding and electrical imaging. The acquisition of data using these techniques permitted the creation of 2D resistivity cross section from the study area. The geoelectrical data was acquired by using a resistivity meter equipment and was processed in different softwares. The results of the geoelectrical characterization from 1D resistivity model and 2D resistivity electrical sections show that in the study area of Kabiri, there are 8 varieties of geoelectrical layers with different resistivity or conductivity. Near survey in the study area, the lowest resistivity is around 0.322 Ω·m, while the highest is about 92.1 Ω·m. These values illustrated where is possible to plant coffee for suggestion of specific fertilization plan for some area to improve the cultivation.

Granulometric and Mineralogical Characterization of the Sands of the Middle Course of the Kasai River (Territory of Ilebo, Province of Kasai/DR Congo)

The sand bars, in perpetual transformation, observable in the middle course of the Kasai river on the section between the city of Ilebo (pk605) to the confluence of the Loange river (pk525), pose enormous navigability problems. This may be dependent on hydrosedimentological characteristics of the Kasai River. This abundance of sand thus conditions the morphology of the middle course of the Kasai River in the section under our study. It therefore constitutes sedimentary navigation obstacles. The objective of this study is the granulometric and mineralogical characterization of the bar sands of the Kasai River in this study section. Particle size analyzes reveal these are moderately well classified to well classified unimodal sands (Classification coefficient between 1.29 to 1.742) largely presenting grain size symmetry and rarely fine asymmetry (Asymmetry coefficient—Skewness between −0.197 to 0.069) with mesorkurtic and rarely leptokurtic and platykurtic acuity (Angulosity coefficient—Kurtosis between 0.814 to 1.323). All these parameters evolve in sawtooth patterns from upstream to downstream. And then, an automated mineralogical analysis of the sands of the Kasaï River using a Qemscan FEG Quanta 650 made it possible to determine a very varied mineralogical procession with a sawtooth evolution. It is largely dominated by quartz (between 93.73% and 99.07%), followed by calcite (0.01% - 2.66%), iron oxides (0.01% - 1.88%), orthoclase (0.04% - 0.99%), plagioclase (0.01% - 0.75%) and Kaolinite (0.18% - 0.71%). Finally, this mineralogical procession is characterized by a group of minerals which do not reach the threshold of 0.55% such as: illite, apatite, ilmenite, muscovite, chlorite, biotite, montmorillonite, rutile, pyrophyllite, siderite, zircon and dolomite. The evolution of the mineralogical procession of the sands of the bars is not as clear as in the case of particle size parameters.

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.

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.

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.

Reservoir quality evaluation using sedimentological and petrophysical characterization of deep-water turbidites:A case study of Tariki Sandstone Member,Taranaki Basin,New Zealand

The current study aims to ascertain the reservoir characteristics of the Tariki Sandstone Member of the Otaraoa Formation,Taranaki Basin,New Zealand.This study was carried out by integrating the comprehensive petrophysical evaluation,sedimentological and petrographic studies,as well as well log analysis by using data from six wells.The porosity-permeability relationship is used to divide the samples of the Tariki Sandstone Member into reservoir and non-reservoir facies.A thorough petrophysical analysis shows that the maximum porosity values fluctuate between 16.6%and 22.1%,while permeability ranges from 102 mD to 574 mD,which indicates fair to good reservoir quality.Moreover,the Tariki sandstone represents six hydraulic flow units with a high reservoir quality index and flow zone indicator representing good reservoir characteristics.The pore size varies between nano and megapores with dominant macropores.Based on the sedimentological and petrographic analysis,the Tariki Sandstone Member is classified as a combination of subarkose,arkose,and lithic arkose with fine to medium and moderately to moderately well-sorted grains.The main diagenetic factor affecting the reservoir quality is cementation,which occupied all the pores with calcite.On the bright side,the secondary pores are developed due to the dissolution of calcite cement and few grains.The well log analysis demonstrates the presence of low clay volume ranging from 0.3%to 3.1%,fair to good effective porosity values between 13.6%and 15.9%,net pay thickness from 18.29 m to 91.44 m,and hydrocarbon saturation from 56%to 77.9%.The findings from this study revealed that the Tariki Sandstone Member possesses fair to good reservoir quality and hydrocarbon potential,which indicate submarine fans as appealing hydrocarbon reservoirs.This study can be used in similar depositional environments elsewhere in the world.

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.