Short-term displacement prediction for newly established monitoring slopes based on transfer learning

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.

Runout prediction of potential landslides based on the multi-source data collaboration analysis on historical cases

Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.

Forming Condition and Geology Prediction Techniques of Deep Clastic Reservoirs

1 Introduction As new exploration domain for oil and gas,reservoirs with low porosity and low permeability have become a hotspot in recent years(Li Daopin,1997).With the improvement of technology,low porosity and low

Tunnel seismic tomography method for geological prediction and its application

Typical existing methods of tunnel geological prediction include negative apparent velocity, horizontal seismic profile, and the Tunnel Seismic Prediction （TSP） method as this technology is under development at home and abroad. Considering simpler observational methods and data processing, it is hard to accurately determine the seismic velocity of the wall rock in the front of the tunnel face. Therefore, applying these defective methods may result in inaccurate geological inferences which will not provide sufficient evidence for classifying the wall rock characteristics. This paper proposes the Tunnel Seismic Tomography （TST） method using a spatial observation arrangement and migration and travel time inversion image processing to solve the problem of analyzing the velocity structure of wall rock in the front of the tunnel face and realize accurate imaging of the geological framework of the tunnel wall rock. This method is very appropriate for geological prediction under complex geological conditions.

Quantitative analysis of geological ore-controlling factors and stereoscopic quantitative prediction of concealed ore bodies

To address the issues for assessing and prospecting the replaceable resource of crisis mines, a geological ore-controlling field model and a mineralization distribution field model were proposed from the viewpoint of field analysis. By dint of solving the field models through transferring the continuous models into the discrete ones, the relationship between the geological ore-controlling effect field and the mineralization distribution field was analyzed, and the quantitative and located parameters were extracted for describing the geological factors controlling mineralization enrichment. The method was applied to the 3-dimensional localization and quantitative prediction for concealed ore bodies in the depths and margins of the Daehang mine in Guangxi, China, and the 3-dimensional distribution models of mineralization indexes and ore-controlling factors such as magmatic rocks, strata, faults, lithology and folds were built. With the methods of statistical analysis and the non-linear programming, the quantitative index set of the geological ore-controlling factors was obtained. In addition, the stereoscopic located and quantitative prediction models were set up by exploring the relationship between the mineralization indexes and the geological ore-controlling factors. So far, some concealed ore bodies with the resource volume of a medium-sized mineral deposit are found in the deep parts of the Dachang Mine by means of the deep prospecting drills following the prediction results, from which the effectiveness of the predication models and results is proved.

Applications of Pre-Geological Prediction in Tunnel Construction

Pre-geological prediction (PGP) is defined as the prediction of engineering geologic condition and hy-drogeological condition certain distance ahead of the working face. The purpose of this paper is to introduce mainlygeologic survey before and in excavation, to clarify their emphasis on PGP. At the same time, the technique is appliedto an engineering case, the longest highway tunnel in Gansu province. Data of geological survey of outside tunnels,sound wave detection, and geologic sketch for both tunnel face and sidewalls within the tunnel are analyzed. Afteranalyzing these data, long-term pre-geological prediction forecasting basic geological conditions of fault 4 such aslithology, scope, location, etc., and short-term and more accurate pre-geological prediction are reported.

Application of Integrated Geological Prediction Technologies in Sub-river Tunnel of Liuyang

Because of the frequent serious geo-hazards met in constructing sub-river tunnels,the application of geological prediction is necessary to reduce the risk. Taking the Liuyang River Tunnel(10.1 km,with 362 m of the sub-river part) which is one of the key projects of the dedicated-passenger railway from Wuhan to Guangzhou as an example,the application of integrated geological prediction technologies is expounded in detail.The effects of TSP(tunnel seismic prediction) and infrared water detectors are analyzed as key points in order to summarize the advantages and disadvantages of these devices.The results of this research which can be adopted to improve the effects of the

Analysis and Prediction of Foundation Settlement of High-Rise Buildings under Complex Geological Conditions

Based on an example of a project in Tangshan, the high-rise buildings are built in karst area and mined out affected area which is treated by high pressure grouting, and foundation is adopted the form of pile raft foundation. By long-term measured settlement of high-rise buildings, It is found that foundation settlement is linear increase with the increase of load before the building is roof-sealed, and the settlement increases slowly after the building is roof-sealed, and the curve tends to converge, and the foundation consolidation is completed. The settlement of the foundation is about 80% - 84% of the total settlement before the building is roof-sealed.Three layer BP neural network model is used to predict the settlement in the karst area and mined affected area.Compared with the measured data, the relative difference of the prediction is 0.91% - 2.08% in the karst area, and is 0.95% - 2.11% in mined affected area. The prediction results of high precision can meet the engineering requirements.

Multi-source data integration and multi-scale modeling framework for progressive prediction of complex geological interfaces in tunneling

A reliable geological model plays a fundamental role in the efficiency and safety of mountain tunnel construction.However,regional models based on limited survey data represent macroscopic geological environments but not detailed internal geological characteristics,especially at tunnel portals with complex geological conditions.This paper presents a comprehensive methodological framework for refined modeling of the tunnel surrounding rock and subsequent mechanics analysis,with a particular focus on natural space distortion of hard-soft rock interfaces at tunnel portals.The progressive prediction of geological structures is developed considering multi-source data derived from the tunnel survey and excavation stages.To improve the accuracy of the models,a novel modeling method is proposed to integrate multi-source and multi-scale data based on data extraction and potential field interpolation.Finally,a regional-scale model and an engineering-scale model are built,providing a clear insight into geological phenomena and supporting numerical calculation.In addition,the proposed framework is applied to a case study,the Long-tou mountain tunnel project in Guangzhou,China,where the dominant rock type is granite.The results show that the data integration and modeling methods effectively improve model structure refinement.The improved model’s calculation deviation is reduced by about 10%to 20%in the mechanical analysis.This study contributes to revealing the complex geological environment with singular interfaces and promoting the safety and performance of mountain tunneling.

Predicting geological hazards during tunnel construction

The complicated geological conditions and geological hazards are challenging problems during tunnel construction,which will cause great losses of life and property.Therefore,reliable prediction of geological defective features,such as faults,karst caves and groundwater,has important practical significances and theoretical values.In this paper,we presented the criteria for detecting typical geological anomalies using the tunnel seismic prediction（TSP） method.The ground penetrating radar（GPR） signal response to water-bearing structures was used for theoretical derivations.And the 3D tomography of the transient electromagnetic method（TEM） was used to develop an equivalent conductance method.Based on the improvement of a single prediction technique,we developed a technical system for reliable prediction of geological defective features by analyzing the advantages and disadvantages of all prediction methods.The procedure of the application of this system was introduced in detail.For prediction,the selection of prediction methods is an important and challenging work.The analytic hierarchy process（AHP） was developed for prediction optimization.We applied the newly developed prediction system to several important projects in China,including Hurongxi highway,Jinping II hydropower station,and Kiaochow Bay subsea tunnel.The case studies show that the geological defective features can be successfully detected with good precision and efficiency,and the prediction system is proved to be an effective means to minimize the risks of geological hazards during tunnel construction.

Expert System for Statistical Prediction of Mineral Deposits on Middle and Large Scales

The expert system for statistical prediction of mineral deposits on middle and large scales takes the system of scientific exploration theories, criteria and methods proposed by Professor Zhao Pengda as the field expert knowledge. At present the developed system focuses on two aspects: synthetic exploration and quantitative exploration. Among the three basic theories for the prediction of deposits, it highlights the applications of seeking anomaly theory. This system is characteristic in the determination of geological background, the study of geological anomalies and the delineation of geological background, the study of geological anomalies and the delineation of mineralization anomalies. The system combines closely the knowledge base, method base and database .integrates the input and output information of multi - sources and mul-ti - variables , data , graphs and imagine processing system and inquiring system as a whole . So the system can meet in general all kinds of demands in statistical prediction of mineral deposits . Since the statistical prediction of mineral resources is a kind of systematic engineering pro ject , a further study should be carried out on the fields of theoretical exploration and ster eo - exploration on the basis of unceasingly perfecting the above-mentioned fields in order to establish a comprehensive intelligent system for scientific exploration , to provide new methods , new techniques and new ideas for fast prospecting appraisal of mineral resources .

Tectonic evolution and the analysis of unfavorable geology in a tunnel

Based on the theory of geomechanics and using geologic analytical methods,analyed the fault characteristics, mechanical properties, displacement mode, tectonic system, structural pattern, activity mode of stress, tectonic activity, and tectonic evolution ofthe area of the Xiamen submarine tunnel, the strike NWW 295^(。), which is the main unfavorable geological structure that affects the safety of the tunnel construction; the macrogeological prediction concludes that weathered troughs and groundwater-rich zonesformed by its larger-scale fault fracture zones are the main unfavorable geological bodiesprovides a basis for preventing the geo-logical hazards in the tunnel construction.

Prediction of Favorable Gas Accumulation Zones in the Western Part of Southern Margin in Junggar Basin

ＰｒｅｄｉｃｔｉｏｎｏｆＦａｖｏｒａｂｌｅＧａｓＡｃｃｕｍｕｌａｔｉｏｎＺｏｎｅｓｉｎｔｈｅＷｅｓｔｅｒｎＰａｒｔｏｆＳｏｕｔｈｅｒｎＭａｒｇｉｎｉｎＪｕｎｇｇａｒＢａｓｉｎ￥ＳｏｎｇＹａｎ，ＤａｉＪｉｎｘｉｎｇ，ＷａｎｇＤａｒｕｉ，ＳｕｎＹｏｎｇｘ...

Interlayer Prediction Method for Braid River Reservoirs in Offshore Oil Field

The interlayer structure of braid river reservoirs is complex and the interwell prediction is difficult in offshore oil field. Taking CFD11-1 oilfield of NgⅢ sand as an example, based on layer contrasting, the interlayer is divided into muddy interlayer, clay boulder interlayer, and physical interlayer according to lithology. Under the guidance of sedimentary model, we use the geology statistical inversion method to predict the clay boulder interlayer, consistent with the dynamic characteristics of oil production which is used for the prior quality control. The results of this study can objectively reveal the characteristics of interlayer space distribution. Compared with the traditional multi-well comparison and stochastic simulation model, this method is applied to the offshore oil field which is character with wide well space, sparse well network, which has very high application value in predicting the interlayer and deploying of inter-well encryption in the similar oilfield.

The Validity of the Thermohydrogravidynamic Theory Concerning the Predicted Dates of the Maximal Temporal Intensifications of the Global Seismotectonic Processes of the Earth during the Range 2020 - 2023 AD

We present (on the 13th International Conference on Geology and Geophysics) the convincing evidence that the strongest earthquakes (according to the U.S. Geological Survey) of the Earth (during the range 2020 - 2023 AD) occurred near the predicted (calculated in advance based on the global prediction thermohydrogravidynamic principles determining the maximal temporal intensifications of the global seismotectonic, volcanic, climatic and magnetic processes of the Earth) dates 2020.016666667 AD (Simonenko, 2020), 2021.1 AD (Simonenko, 2019, 2020), 2022.18333333 AD (Simonenko, 2021), 2023.26666666 AD (Simonenko, 2022) and 2020.55 AD, 2021.65 AD (Simonenko, 2019, 2021), 2022.716666666 AD (Simonenko, 2022), respectively, corresponding to the local maximal and to the local minimal, respectively, combined planetary and solar integral energy gravitational influences on the internal rigid core of the Earth. We present the short-term thermohydrogravidynamic technology (based on the generalized differential formulation of the first law of thermodynamics and the first global prediction thermohydrogravidynamic principle) for evaluation of the maximal magnitude of the strongest (during the March, 2023 AD) earthquake of the Earth occurred on March 16, 2023 AD (according to the U.S. Geological Survey). .

新世纪以来我国铀矿地质科技创新重要进展及展望

新世纪以来,我国铀矿地质勘查领域重大理论和技术创新成果,极大地改变了我国砂岩型、热液型铀矿的找矿思路、找矿方向,引领、支撑了系列找矿重大突破,重塑了铀矿勘查新格局。文章首先分析了我国20余年来铀矿地质科研布局的总体思路与演进方向;然后总结了铀矿重大基础地质与成矿理论研究进展,系统凝练了地质、物化探、遥感、钻探工艺、分析测试等领域的技术创新及核心勘查装备研制成果,梳理了铀资源预测评价技术研究进展及应用成效;最后,在重大基础前沿和成矿理论、先进铀矿勘查技术研发、非常规核能裂变资源勘查技术研究、数字铀矿勘查技术开发等方面提出了未来10~15年主要发展趋势和方向,指出在“双碳”目标和核能大发展对铀资源保障需求背景下,必须继续坚持并加强铀矿地质科技创新,高质量引领和推动“新区、新层位、新类型、新深度”找矿突破。

基于地质三维建模的矿床蚀变带深部资源预测方法

随着矿产资源需求的持续增加,加之浅表矿产资源的逐渐匮乏,如何有效开发深部矿产资源成为国家重点研究课题之一。以往二维矿床信息无法确定精准的深部资源储量,阻碍矿产资源的开发进度,本文提出基于地质三维建模的矿床蚀变带深部资源预测方法研究。应用地质三维建模软件(GOCAD)与计算机技术,构建矿床蚀变带深部地质三维模型,以此为基础,确定最佳单元尺度,划分矿床蚀变带深部地质统计单元,提取矿床蚀变带深部地质变量,计算地质变量权重数值,探究深部地质统计单元之间的联系度,基于三维证据权法预测矿床蚀变带深部资源。实验数据显示:应用该方法获得的矿床蚀变带深部资源预测误差最小值为1.01%,充分证实了该方法的深部资源预测精度更高。

钻爆法机械化施工隧道随钻地震波超前地质探测技术研究

为适应我国隧道建设机械化、智能化、无人化发展趋势,围绕钻爆法机械化施工隧道,提出以凿岩台车破岩振动为震源的钻爆法机械化施工隧道随钻地震波超前地质探测技术。针对凿岩台车多震源连续激发带来的地震数据波场混叠、有效信息难以识别问题开展相关研究,提出VMD-SVD-RobustICA三臂混合先导信号分离方法与脉冲反褶积-小波域互相关地震记录重构方法,可实现三臂混合先导信号的分离与有效反射信号的提取。工程实践证明,利用凿岩台车搭载式无线高精度探测装备,该技术可初步实现“边钻边探”,降低预报环节对钻爆法机械化施工隧道正常施工带来的影响。最后,明确该技术目前存在的问题及解决思路。

滇中引水工程隧洞综合超前地质预报分析及应用

针对隧洞施工过程中不同工程地质条件下何种超前地质预报方法预测更为准确、更为适用和单一方法精确度不够、适用性不强的问题,分别介绍了基于地震波法的长距离隧洞超前地质预报技术和基于电磁法的中、短距离隧洞超前地质预报技术原理及特点,依据其工作原理、工作方式、预报距离等特点,探讨了不同超前地质预报方法的优、缺点及其最适用的工作场景,总结出一套实用性强的综合超前地质预报流程。依托滇中引水工程大理Ⅱ段两个隧洞的工程实例,利用所提出的综合超前地质预报流程,分别介绍了结合长距离的隧道地震预报(TSP)法、中短距离的瞬变电磁法和探地雷达法对断层破碎带和裂隙水等不良地质体的综合预报研究。首先,通过长距离预报方法对地质灾害危险程度进行分级、识别高危地段,再通过短距离预报方法对不良地质体进行更精确的识别与定位,综合分析3种超前地质预报方法的地球物理响应特征,可以推断出不良地质体的类型及其空间分布特征;其次,通过探地雷达探测溶蚀波场特征的案例分析,可以推断出溶蚀的物性特征、规模及其空间分布特征。预报结果与隧洞掌子面开挖揭示的结果基本一致,验证了3种超前地质预报方法预报隧洞不良地质体的可靠性,也证实了所提出的综合超前地质预报流程的实用性,有助于指导物探工作者对不良地质体进行更精确的预报,确保隧洞施工安全。

隧道富水断层破碎带突涌预报与工程对策研究

为解决高原隧道断层破碎带易发突泥冒顶灾害的问题,采用现场调查、地面物探、洞内地震波反射法、瞬变电磁法、超前钻孔等超前地质预报方法,推广洞内物探三维分析,对富水断层破碎带突泥灾害特征、超前地质预报综合成果和工程应对加固措施进行研究。结果表明:三维物探成果能快速精准查明富水破碎带空间形态,成果直观,有效指导风险判识和工程处置措施;对富水断层带预报应充分结合勘察期成果,宏观初判断层分布特性,洞内采用物钻结合、长短结合的方法;首次提出按照“探明破碎带规模形态,查明破碎带物质组分性状,观测地下水特征变化情况”的思路,研判突泥涌水风险;施工处置应按照“探泄结合,先固后进,回堵再泄”的总体原则有序开展。研究成果和手段可为类似突涌灾害超前地质预报和工程应对措施提供参考。