地质导向技术在L型煤层气水平井 T-P05井中的应用

通过分析山西L型煤层气水平井的技术难点,着重建立造斜着陆与水平段导向两大导向模型,形成了以标志层划分与对比、地层倾角推算、地质建模和实时轨迹控制四个方面为主的L型煤层气水平井地质导向技术流程,该技术在T-P05井的成功应用,不仅丰富了煤层气水平井地质导向技术的内容与方法,更进一步验证了该技术在现场具有较强的可操作性和良好的应用前景,值得大力推广。     

泥浆护壁成孔灌注桩后注浆技术正确应用研究

为保证泥浆护壁成孔灌注桩后注浆技术正确应用,首先分析了后注浆技术对泥浆护壁灌注桩的作用机理以及天津地区的应用现状,然后通过对影响其应用效果的多种因素,如从业人员资格、成孔成桩质量、注浆阀、注浆泵、注浆相关参数等分析研究,提出相应的措施或建议。     

岩溶塌陷灾害的岩溶地下水气压力监测技术及应用

文章系统、全面地介绍了岩溶地下水气压力监测技术及其应用成果。该技术在监测成孔、孔口的密封及监测频率等方面创新性地提出了相关的工艺方法,能真实、及时且充分地反映出岩溶管道裂隙系统中的地下水气压力变化特点,可为岩溶塌陷的机理研究、监测和预警提供科学依据。岩溶地下水气压力监测技术工艺简单、操作方便、成本低廉,经过20多年的改进,已成功应用于全国11个典型岩溶塌陷区,服务于高铁、水源地、油气管线、市政建设等潜在岩溶塌陷风险性评价、安全降深、监测预警等方面,取得了很好的效果。      

Porphyry Copper Deposit Prognosis in the Middle Region of the Bangonghu–Nujiang Metallogenic Belt,Tibet, Using ASTER Remote Sensing Data

The B angonghu–N ujiang metallogenic belt is considered to be T ibet’s third copper belt after the Y ulong and G angdese copper belts. The D uolong gold‐rich porphyry copper deposit, located in the western part of the B angonghu–N ujiang belt was recently recognized as a superlarge prospect. The A dvanced S paceborne T hermal E mission and R eflection R adiometer (ASTER ) was used to characterize the D uolong porphyry deposit alteration area, and three methods, color enhancement, band ratio transformation, and spectral angle mapping, were utilized to extract the phyllic and argillic alteration zones, which are typically considered the most important predictors of porphyry copper. Seven prospecting areas, which match mapped alteration zones, were delineated in the D uolong deposit. In addition, an ASTER image of the eastern region of the B angonghu–N ujiang belt in the X iongmei area was used to extract alteration information, and an area with image characteristics similar to the D uobuza and B olong ore deposits was identified as a prospecting area. Numerous malachite outcrops were identified in the field, and both laboratory analysis and isotopic dating confirmed that the deposit had formed concurrently with the D uobuza deposit (119 M a). Geologic mapping at the 1:5000 scale was conducted in the area, and three types of ore‐bearing rocks were identified, indicating that this area has significant potential to host ore deposits. The discovery of the X iongmei copper mining area is significant for the B angonghu–N ujiang belt.     

Development of medium-term prediction methods: A case study of the August 14, 2016 Onor (Mw = 5.8) earthquake on Sakhalin

The potential of the load-unload response ratio (LURR) method for medium-term earthquake prediction is studied for Sakhalin Island as an example. An approach to the generation of predicted conditions and assessment of their implementation in real time is considered. The results of a retrospective analysis of other large Sakhalin earthquakes are used for generalization. It is shown that deviations of prediction parameters from specified values are satisfactory for this method. It is recommended that this method be used to compile summaries of medium-term predictions for Sakhalin provided that catalogs are filled as soon as possible.     

Foundations of petroleum prediction based on the activation of geochemical processes by direct current

Petroleum prediction in local objects and the applicability of geologic environment parameters in this regard are considered. The proposed guidelines for petroleum potential prediction are based on the analysis of the distribution of typomorphic epigenetic multivalent elements loosely fixed in rocks before and after electric current treatment. The advantage of geoelectrochemical methods providing data on the chemical composition of above-productive deposits is demonstrated.     

大数据环境下内蒙古浩布高地区铅锌多金属矿智能矿产预测研究

传统机器学习算法已广泛应用于矿产预测,但面对地质大数据的高维稀疏、不平衡小样本等特性仍缺乏有效处理和分析的方法,设计适合地质大数据特点的机器学习算法是智能矿产预测亟需解决的新问题。本文以内蒙古浩布高地区的铅锌多金属矿产预测为例,提出了一种面向地质大数据的半监督协同训练矿产预测模型。首先对研究区地质找矿信息和地球化学异常信息进行定量分析,提取断裂构造、二叠系地层、燕山期侵入岩、地层与岩体接触带、围岩蚀变及Pb、Zn、Sn、Cu地球化学异常共9种找矿因子。然后利用递归特征消除法优选找矿因子组合,不包括Sn异常在内的8个找矿因子组合被选为最优组合。最后,利用支持向量机和随机森林算法作为基分类器进行半监督协同训练矿产预测,绘制成矿概率分布图。ROC曲线和预测度曲线分析结果表明,半监督协同训练模型的AUC值和预测效率都高于随机森林和支持向量机模型。研究结果也为大数据环境下的智能矿产预测提供了一种新的思路。     

卷积神经网络及其在矿床找矿预测中的应用——以安徽省兆吉口铅锌矿床为例

大数据人工智能地质学刚刚起步,基于大数据智能算法的地质研究是非常有意义的探索性实验。利用大数据和机器学习解决矿产预测问题,有助于人们克服不能全面考虑地质变量的困难及评估当前模型在已有数据中的可靠性。元素地表分布特征量主要受原岩成分、成矿作用影响和地表过程的影响,它们携带某些指示矿体就位的信息,即矿体在地下空间就位时在地表的响应,且未在地表过程中消失。以往的地球化学勘查工作仅仅识别异常,但未能发现矿体在地表响应的成矿特征量。本文以安徽省兆吉口铅锌矿床为例,通过机器学习,利用卷积神经网络算法,不断挖掘元素Pb分布特征与矿体地下就位空间的耦合相关性。经过1000次训练后,可以得到准确率0. 93,损失率0. 28的卷积神经网络模型。这种神经网络模型就是矿体在地下就位时元素在地表分布的响应,可以用来进行矿产资源预测。应用该模型对未知区进行预测,结果显示第53号区域具有很大概率存在尚未发现的矿体。     

基于人工鱼群算法和SCA等效理论的井中横波速度预测方法

在建立页岩岩石物理模型的基础上,根据等效自相容近似(SCA)岩石物理模型,构建出岩石的纵波速度、横波速度与岩石密度、组分和孔隙度等的定量关系,得出使理论纵波速度和实际纵波速度最接近的孔隙纵横比,进而将该孔隙纵横比作为约束条件来实现横波速度预测。反演算法利用人工鱼群算法来计算最佳孔隙纵横比,并将预测的横波速度与实际测得的横波速度对比,证明了人工鱼群算法的有效性。     

Progress in the Application of Ground Gravity Observation Data in Earthquake Prediction

The mechanism of earthquake inoculation and the process of earthquake occurrence are very complicated. Additionally, earthquakes do not happen very often, and we lack enough cognition to the earth’s interior structure, activity regularity and other key elements. As a result, research progress about the theory of earthquake precursors has been greatly restricted. Ground gravity observation has become one of the main ways to study earthquake precursor information in many countries and regions. This paper briefly summarized the surface gravity observation technology and observation network in China: the surface gravity measurement instrument developed from Huygens physical pendulum in seventeenth Century to today’s high-precision absolute gravimeter, and its accuracy reached to ±1×10^-8 m/s². China has successively established the National Gravity Network, Digital Earthquake Observation Network of China,the Crustal Movement Observation Network of China Ⅰ and the Crustal Movement Observation Network of China, to provide a public platform for monitoring non tidal gravity change, seismic gravity and tectonic movement. The use of specific examples illustrated the role of gravity observation data in earthquake prediction. The gravity observation data of ground gravity can be used to capture the information of gravity change in the process of strong earthquake inoculation, and to provide an important basis for the long-term prediction of strong earthquakes. The temporal and spatial variation characteristics of the regional gravity field and its relation to strong earthquakes were analyzed: Before the earthquake whose magnitude is higher than M_S 5, generally there will be a large amplitude and range of gravity anomaly zones. Strong earthquakes occur mainly in areas where the gravity field changes violently. The dynamic change images of gravity field can clearly reflect the precursory information of large earthquakes during the inoculation and occurrence. Finally, the existing problems of surface gravity technology in earthquake precursor observation were put forward and the use of gravity measurement data in earthquake prediction research was prospected.