页岩气基础地质调查皖南地1井钻探施工技术

皖南地1井是部署在安徽省南陵县烟墩镇的一口页岩气基础地质调查井。文章详细介绍了该井的钻探施工工艺技术以及遇到复杂问题的处理方法,并对钻效进行了分析,提出了实现优质高效钻探的措施。项目的顺利实施,梳理了皖南地区地层层序,为页岩气储层理论推测提供了有力的实物数据支撑和验证。     

Geometric-constrained multi-view image matching method based on semi-global optimization

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.     

A geometric-based approach for road matching on multi-scale datasets using a genetic algorithm

Object matching is used in various applications including conflation, data quality assessment, updating, and multi-scale analysis. The objective of matching is to identify objects referring to the same entity. This article aims to present an optimization-based linear object-matching approach in multi-scale, multi-source datasets. By taking into account geometric criteria, the proposed approach uses real coded genetic algorithm (RCGA) and sensitivity analysis to identify corresponding objects. Moreover, in this approach, any initial dependency on empirical parameters such as buffer distance, threshold of spatial similarity degree, and weights of criteria is eliminated and, instead, the optimal values for these parameters are calculated for each dataset. Volunteered geographical information (VGI) and authoritative data with different scales and sources were used to assess the efficiency of the proposed approach. According to the results, in addition to an efficient performance in various datasets, the proposed approach was able to appropriately identify the corresponding objects in these datasets by achieving higher F-Score.     

基于优化经验模态分解和聚类分析的滑坡位移智能预测研究

针对三峡库区"阶跃式"滑坡的变形特征,提出了一种新的滑坡位移预测方法。以白水河滑坡ZG118和XD-01监测点位移数据为例,采用基于软筛分停止准则的经验模态分解(SSSC-EMD)将累计位移-时间曲线和影响因子时间序列自适应地分解为多个固有模态函数(IMF),并采用K均值(K-Means)聚类法对其进行聚类累加,得到有物理含义的位移分量(趋势性位移、周期性位移以及随机性位移)和影响因子分量(高频影响因子和低频影响因子)。使用最小二乘法对趋势性位移进行拟合预测;采用果蝇优化-最小二乘支持向量机(FOA-LSSVM)模型对周期性位移和随机性位移进行预测。将各位移分量预测值进行叠加处理,实现滑坡累计位移的预测。研究结果表明,所提出的(SSSC-EMD)-K-Means-(FOA-LSSVM)模型能够预测"阶跃式"滑坡的位移变化规律,且预测精度高于传统的支持向量机回归(SVR)、最小二乘支持向量机(LSSVM)模型;并通过改变训练集长度,进行单因素分析,发现其与预测精度之间呈正相关关系。     

PARAMETER AND VARIANCE ESTIMATION IN GEOTECHNICAL BACKANALYSIS USING PRIOR INFORMATION

A probabilistic framework to perform inverse analysis of geotechnical problems is presented. The formulation allows the incorporation of existing prior information on the parameters in a consistent way. The method is based on the maximum likelihood approach that allows a straightforward introduction of the error structure of field measurements and prior information. The difficulty of ascribing definite values to the uncertainties associated with the various types of observations is overcome by including the corresponding variances in the set of parameters to be identified. The inverse analysis results in a minimization problem that is solved by coupling the optimization technique to the finite element method. Two examples are presented to illustrate the performance of the method. The first one corresponds to a synthetic case simulating the excavation of a tunnel. Young's modulus, K₀ value and measurements variances are identified. The second case concerns the excavation of a large underground cavern in which again Young's modulus and K₀ are identified. It is shown that introduction of prior information permits the estimation of parameters more consistent with all available informations that include not only monitored displacements but also results from in situ tests carried out during the site investigation stage.     

关于井炮激发参数优化设计的思考

利用正演模拟的手段进行分析,对影响井炮激发的不同影响因素展开分析,结合对炸药特征阻抗与围岩的阻抗匹配系数、炸药几何耦合系数、激发药量、井深等方面进行分析,对井炮激发参数进行优化设计.通过优化设计,寻求有效提高地震子波品质的方法.结合实际的地震地质条件和地震勘探目标,设计最佳的井炮激发参数,提高地震勘探的效益.     

应用最优化模型分析活断层与地震的关系

文中应用基于“多态”前兆模式及效能评价的最优效能单项模型参数选择方法,分析了3个地震带活断层(Qp3—Qh)与地震(M≥6)空间分布之间的关系。结果表明,河套地震带地震较集中分布在距断层20km的范围内,用其对6级以上地震进行地点预测有较高的准确性,R值达0.5,而对祁连山地震带30km范围内地震的发生地点进行预测,R值却仅为0.14     

Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer

As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.     

粘质沙雷氏菌(Serratia marcescens)发酵培养基优化的研究

采用单因素试验和正交试验,对从山东东营海岸湿地盐碱滩地土壤中筛选出的一株海洋菌种———粘质沙雷氏菌(Serratia marcescens)的发酵培养基进行优化,并进行100 L发酵罐中试放大试验的研究。确定粘质沙雷氏菌的最佳培养基配方为葡萄糖10 g/L,硫酸铵5 g/L,麸皮50 g/L,柠檬酸三钠1.0 g/L,K2HPO4.3H2O 0.3 g/L,FeSO4.7H2O 0.05 g/L,MgSO4.7H2O 0.5 g/L,pH 7.2~7.7。发酵最适温度为30℃。通过测定粘质沙雷氏菌在发酵罐中培养的生长曲线,确定发酵时间以28~30 h为宜,发酵结束后发酵液中的活菌数约为50×108个/mL。将所筛选到的粘质沙雷氏菌应用于农作物的病害防治,效果非常显著,表明是一株高活性的生物防治拮抗菌。此研究结果为高效率、低成本和工业化生产具有生物防治作用的海洋菌种制剂提供了科学依据,也为海岸湿地盐碱土的可持续开发利用提供了技术支撑。     

极化SAR目标相对最优极化研究

目标相对最优极化就是选取一种极化状态,使得研究目标和背景地物的接收功率对比达到最大。通过讨论了目标相对最优极化问题,提出了改进的模型和解算方法,利用实际数据对其模型和方法进行了实验,验证了其有效性和正确性。