证据权重法在黑龙江省三合屯地区三维金矿远景区建模中的应用

矿床的分布具有明显的群聚性,成矿过程是由多方面因素共同作用的结果,因此从三维地学模型中准确地识别具有成矿前景的信息是一项重要且具有挑战性的任务。证据权重法引入成矿有利度量化矿床与三维证据因子之间的空间关系,并确定最优正负权重;以单元格成矿后验概率值为基础进行成矿远景建模,并结合约登指数确定成矿概率临界值以圈定成矿靶区。本文利用三维地质和地球物理模型对黑龙江省三合屯地区的热液型金矿进行了成矿远景建模,圈定出3个找矿靶区。研究表明,证据权重法用于三维成矿预测中具有预测可靠性高、简单易实现等特点,并为探测地下隐伏矿体提供可靠的支持。

Geometry and 3D seismic characterisation of post-rift normal faults in the Pearl River Mouth Basin,northern South China Sea

Based on high-resolution 3D seismic data acquired in the Pearl(Zhujiang)River Mouth Basin of the northern South China Sea,this study investigated the geometry,spatial extension,and throw distribution of the post-rift normal fault through detailed seismic interpretation and fault modeling.A total of 289 post-rift normal faults were identified in the study area and can be classified into four types:(1)isolated normal faults above the carbonate platform;(2)isolated normal faults cutting through the carbonate platform;(3)conjugate normal faults,and(4)connecting normal faults.Throw distribution analysis on the fault planes show that the vertical throw profiles of most normal fault exhibit flat-topped profiles.Isolated normal faults above the carbonate platform exhibit roughly concentric ellipses with maximum throw zones in the central section whereas the normal faults cutting through the carbonate platform miss the lowermost section due to the chaotic seismic reflections in the interior of the carbonate platform.The vertical throws of conjugate normal faults anomalously decrease toward their intersection region on the fault plane whereas the connecting normal faults present two maximum throw zones in the central section of the fault plane.According to the symmetric elliptical distribution model of fault throw,an estimation was made indicating that normal faults cutting through the carbonate platform extended downward between-1308 s and-1780 s(two-way travel time)in depth and may not penetrate the entire Liuhua carbonate platform.Moreover,it is observed that the distribution of karst caves on the top of the carbonate platform disaccord with those of hydrocarbon reservoirs and the post-rift normal faults cutting through the carbonate platform in the study area.We propose that these karst caves formed most probably by corrosive fluids derived from magmatic activities during the Dongsha event,rather than pore waters or hydrocarbons.

基于水系沉积物地球化学采样的地形加权图卷积网络基岩填图方法

为了探索高效的第四系覆盖及露头较少区域的基岩智能填图方法,应用图卷积网络(GCN)对青海省察汗乌苏河地区水系沉积物地球化学采样的下伏基岩进行分类。基于Delaunay三角化采样点被组织为一个地形加权的有向图来表达水系沉积物地球化学采样点之间的河流上下游关系。实验结果表明:半监督的GCN模型仅使用了20%的采样点标签,分类精度达到68.20%(10类基岩)和78.31%(5类基岩)。该方法能有效利用水系沉积物地球化学采样中的元素含量进行基岩填图,且能提高基岩填图的效率并能进行大面积应用。

Stability Scrutinization of Agrawal Axisymmetric Flow of Nanofluid through a Permeable Moving Disk Due to Renewable Solar Radiation with Smoluchowski Temperature and Maxwell Velocity Slip Boundary Conditions

The utilization of solar energy is essential to all living things since the beginning of time.In addition to being a constant source of energy,solar energy(SE)can also be used to generate heat and electricity.Recent technology enables to convert the solar energy into electricity by using thermal solar heat.Solar energy is perhaps the most easily accessible and plentiful source of sustainable energy.Copper-based nanofluid has been considered as a method to improve solar collector performance by absorbing incoming solar energy directly.The goal of this research is to explore theoretically the Agrawal axisymmetric flow induced by Cu-water nanofluid over a moving permeable disk caused by solar energy.Moreover,the impacts of Maxwell velocity and Smoluchowski temperature slip are incorporated to discuss the fine points of nanofluid flow and characteristics of heat transfer.The primary partial differential equations are transformed to similarity equations by employing similarity variables and then utilizing bvp4c to resolve the set of equations numerically.The current numerical approach can produce double solutions by providing suitable initial guesses.In addition,the results revealed that the impact of solar collector efficiency enhances significantly due to nanoparticle volume fraction.The suction parameter delays the boundary layer separation.Moreover,stability analysis is performed and is found that the upper solution is stable and physically trustworthy while the lower one is unstable.

Machine learning strategies for lithostratigraphic classification based on geochemical sampling data: A case study in area of Chahanwusu River, Qinghai Province, China

Based on the complex correlation between the geochemical element distribution patterns at the surface and the types of bedrock and the powerful capabilities in capturing subtle of machine learning algorithms,four machine learning algorithms,namely,decision tree(DT),random forest(RF),XGBoost(XGB),and LightGBM(LGBM),were implemented for the lithostratigraphic classification and lithostratigraphic prediction of a quaternary coverage area based on stream sediment geochemical sampling data in the Chahanwusu River of Dulan County,Qinghai Province,China.The local Moran’s I to represent the features of spatial autocorrelations,and terrain factors to represent the features of surface geological processes,were calculated as additional features.The accuracy,precision,recall,and F1 scores were chosen as the evaluation indices and Voronoi diagrams were applied for visualization.The results indicate that XGB and LGBM models both performed well.They not only obtained relatively satisfactory classification performance but also predicted lithostratigraphic types of the Quaternary coverage area that are essentially consistent with their neighborhoods which have the known types.It is feasible to classify the lithostratigraphic types through the concentrations of geochemical elements in the sediments,and the XGB and LGBM algorithms are recommended for lithostratigraphic classification.

Is Social Distancing, and Quarantine Effective in Restricting COVID-19 Outbreak? Statistical Evidences from Wuhan, China

The flow of novel coronavirus(COVID-19)has affected almost every aspect of human life around the globe.Being the emerging ground and early sufferer of the virus,Wuhan city-data remains a case of multifold significance.Further,it is of notable importance to explore the impact of unique and unprecedented public health response of Chinese authorities—the extreme lockdown of the city.In this research,we investigate the statistical nature of the viral transmission concerning social distancing,extreme quarantine,and robust lockdown interventions.We observed highly convincing and statistically significant evidences in favor of quarantine and social distancing approaches.These findings might help countries,now facing,or likely to face the wave of the virus.We analyzed Wuhan-based data of“number of deaths”and“confirmed cases,”extracted from China CDC weekly database,dated from February 13,2020,to March 24,2020.To estimate the underlying group structure,the assembled data is further subdivided into three blocks,each consists of two weeks.Thus,the complete data set is studied in three phases,such as,phase 1(Ph 1)=February 13,2020,to February 26,2020;phase 2(Ph 2)=February 27,2020 to March 11,2020;and phase 3(Ph 3)=March 12,2020 to March 24,2020.We observed the overall median proportion of deaths in those six weeks remained 0.0127.This estimate is highly influenced by Ph1,when the early flaws of weak health response were still prevalent.Over the time,we witnessed a median decline of 92.12%in the death proportions.Moreover,a non-parametric version of the variability analysis of death data,estimated that the average rank of reported proportions in Ph 3 remained 7,which was 20.5 in Ph 2,and stayed 34.5 in the first phase.Similar patterns were observed,when studying the confirmed cases data.We estimated the overall median of the proportion of confirmed cases in Wuhan as 0.0041,which again,is highly inclined towards Ph 1 and Ph 2.We also witnessed minimum average rank proportions for Ph 3,such as 7,which was noticeably lower than Ph 2,21.71,and Ph 1, 32.29. Moreover, the varying degree of clustering indicates that the effectivenessof quarantine based policies is time-dependent. In general, the declinein coronavirus transmission in Wuhan significantly coincides with the lockdown.

Multi-material Bio-inspired Soft Octopus Robot for Underwater Synchronous Swimming

Inspired by the simple yet amazing morphology of the Octopus, we propose the design, fabrication, and characterization of multi-material bio-inspired soft Octopus robot (Octobot). 3D printed molds for tentacles and head were used. The tentacles of the Octobot were casted using Ecoflex-0030 while head was fabricated using relatively flexible material, i.e., OOMOO-25. The head is attached to the functionally responsive tentacles (each tentacle is of 79.12 mm length and 7 void space diameter), whereas Shape Memory Alloy (SMA) muscle wires of 0.5 mm thickness are used in Octobot tentacles for dual thrust generation and actuation of Octobot. The tentacles were separated in two groups and were synchronously actuated. Each tentacle of the developed Octobot contains a pair of SMA muscles (SMA-α and SMA-β). SMA-α muscles being the main actuator, was powered by 9 V, 350 mA power supply, whereas SMA-β was used to provide back thrust and thus helps to increase the actuation frequency. Simulation work of the proposed model was performed in the SolidWorks environment to verify the vertical velocity using the octopus tentacle actuation. The design morphology of Octobot was optimized using simulation and TRACKER software by analyzing the experimental data of angle, displacement, and velocity of real octopus. The as-developed Octobot can swim at variable frequencies (0.5–2 Hz) with the average speed of 25 mm/s (0.5 BLS). Therefore, the proposed soft Octopus robot showed an excellent capability of mimicking the gait pattern of its natural counterpart.

3D structural modeling integrated with seismic attribute and petrophysical evaluation for hydrocarbon prospecting at the Dhulian Oilfield,Pakistan

Surface and deep subsurface geological structural trends,stratigraphic features,and reservoir characteristics play important roles in assessment of hydrocarbon potential.Here,an approach that integrates digital elevation modelling,seismic interpretation,seismic attributes,three-dimensional(3D)geological structural modeling predicated on seismic data interpretation,and petrophysical analysis is presented to visualize and analyze reservoir structural trends and determine residual hydrocarbon potential.The digital elevation model is utilized to provide verifiable predictions of the Dhulian surface structure.Seismic interpretation of synthetic seismograms use two-way time and depth contour models to perform a representative 3D reservoir geological structure evaluation.Based on Petrel structural modeling efficiency,reservoir development indexes,such as the true 3D structural trends,slope,geometry type,depth,and possibility of hydrocarbon prospects,were calculated for the Eocene limestone Chorgali,upper Paleocene limestone Lockhart,early Permian arkosic sandstone Warcha,and Precambrian Salt Range formations.Trace envelope,instantaneous frequency,and average energy attribute analyses were utilized to resolve the spatial predictions of the subsurface structure,formation extrusion,and reflector continuity.We evaluated the average porosity,permeability,net to gross ratio,water saturation,and hydrocarbon saturation of early Eocene limestone and upper Paleocene limestone based on the qualitative interpretation of well log data.In summary,this integrated study validates 3D stratigraphic structural trends and fault networks,facilitates the residual hydrocarbon potential estimates,and reveals that the Dhulian area has a NE to SW(fold axis)thrust-bounded salt cored anticline structure,which substantiates the presence of tectonic compression.The thrust faults have fold axes trending from ENE to WSW,and the petrophysical analysis shows that the mapped reservoir is of good quality and has essential hydrocarbon potential,which can be exploited economically.