遥感技术在煤炭资源开发状况监督管理中的应用研究

利用高分辨率遥感图象可以快速查明煤炭资源开发状况以及煤炭资源开发的合法性（界内开采、界外开采、越界开采）等,对煤矿安全生产及维护矿业秩序具有重要意义。以我国中部某煤炭开采密集区为试验区,选择不同分辨率的遥感数据,从矿山铺助设施、道路、矿堆、矸石的特征出发,进行矿山开采状况遥感解译;以地理信息系统技术（GIS）为支撑实现采矿权数据、规划数据图层与遥感专题数据的叠加分析和相关分析,判断非法与越界矿山,评价矿产资源开发与保护规划执行情况。     

发挥自身优势 扩大经营 走探采一体化道路

煤炭地质勘查单位,通过几十年的艰苦奋斗,不仅为国家找出了大量的煤炭资源,同时也积累了丰富的管理、施工和技术工作经验,以及大量的地质资料。应该发挥自身优势,充分利用大量的以往地质资料,结合新的找矿理论和先进的地面勘查手段,加大人才培养和引进力度,逐步提升专业技术人员的学识和科技水平,加强基础地质工作,不断寻找新的工作靶区,把握住煤炭勘查市场的主动权。抓住机遇,做好资金积累,加强资本运做,充分利用已有探矿权,走探采一体化道路,做精做强到做大地勘单位,是生存和发展的良好出路。     

努力提高三维地震勘探精度，为西部煤炭工业做出新贡献

以国家重大产业技术开发专项“西部煤炭资源高精度三维地震勘探技术”项目的由来、意义和总体研究目标为引,概括的介绍了项目依托工程中各个专项技术研究完成情况,并对非均匀介质成像技术、高精度三维地震静校正技术、高密度采集技术、特观技术、岩性反演技术、属性体解释技术等六项重大关键技术取得的突破性进展进行了重点说明。指出随着我国煤炭生产重点的逐步西移,应加强诸如叠前、叠后深度偏移技术的研究,以解决复杂山区三维地震面元内地震反射波散射问题,提高其三维地震勘探精度,为西部煤炭工业做出新贡献!     

三维地震小面元采集技术在晋城矿区的应用

依托“西部煤炭资源高精度三维地震勘探技术”工程,对晋城矿区进行了旨在提高小断层,小陷落柱探测能力的高密度三维地震勘探。根据面元选择因素及该区地质任务,采用5m×5m网格进行野外数据采集;考虑炮检距、方位角、覆盖次数、排列片横纵比及煤层埋深（350～500m）等因素,采用中点放炮、60道接收,24次覆盖（横向4次,纵向6次）的8线16炮束状观测系统,基岩中激发。原始资料经同一处理流程后,获得5m×5m×1ms、5m×10m×1ms、10m×10m×1ms及2.5m×2.5m×1ms不同单元的三维数据体多个,通过对比可以发现小断层,小陷落柱在其小面元叠加时间剖面、顺层切片及相干切片都有清晰的反映。实例说明,小面元采集技术可以提高对小构造的纵、横向分辨能力,满足山区对三维地震精确勘探的要求。     

提高管线探测水平分辨率的技术方法

在平顶山矿工路路面改造工程中,使用GX-2型及RD-4000型地下管线探测仪探测地下管网布设情况。根据地下管线种类、管线布设方位、埋置深度、探测难度大小进行了多次试验,在此基础上确定了电磁探测技术与方法：利用直连法提高被测管线中的交变电流,压制邻近平行管线和地下介质中的异常反映;在多管并存、且间距较小的情况下,应选择“梯度法”对磁场水平分量垂直梯度ΔHx进行观测,以得到最大清晰异常;另外,还应根据具体情况,合理选择诸如压制旁侧管线法、选择发射法、偏移感应法、动源发射法等发射方式,保证目标管线中有较强异常呈现。在管线密集区,应尽可能地降低工作频率,以减小旁侧管线中产生的二次电流及二次磁场;为防止信噪比下降,可适当减小收发距,以提高接收机的灵敏度。     

地震勘探技术在深部找煤中的应用

成矿理论与勘探实践证明,东部一些老矿由于勘探深度、范围的限制以及认识上的局限,在矿区深部、周边仍有一些矿未能发现和查明,其中相当一部分仍具有找矿潜力;而寻找西部新的煤炭资源是国家“稳定东部发展西部”战略需要。针对中国东西部不同的地质条件和勘探目标,其地震勘探野外施工方法及资料处理原则有所差异;而资料解释在东部以查明地层赋存形态、煤层赋存范围、构造发育特征为主,西部则以寻找煤系地层波阻抗差异明显、连续性好的反射波组为解释重点。地震勘探技术在中国东西部的二个典型地震时间剖面佐证了其在深部找矿的应用效果。     

The Tau Model for Data Redundancy and Information Combination in Earth Sciences: Theory and Application

Many decision-making processes in the Earth sciences require the combination of multiple data originating from diverse sources. These data are often indirect and uncertain, and their combination would call for a probabilistic approach. These data are also partially redundant with each other or with all others taken jointly. This overlap in information arises due to a variety of reasons—because the data arises from the same geology, because they originate from the same location or the same measurement device, etc. The proposed tau model combines partially redundant data, each taking the form of a prior probability for the event being assessed to occur given that single datum. The parameters of that tau model measure the additional contribution brought by any single datum over that of all previously considered data; they are data sequence-dependent and also data value-dependent. Data redundancy depends on the sequence in which the data is considered and also on the data values themselves. However, for a given sequence, averaging the tau model parameters over all possible data values leads to exact analytical expressions and corresponding approximations and inference avenues. Information on multiple-point connectivity of permeability arrives from core data, well-test data and seismic data which are defined over varying supports with complex redundancy between these information sources. In order to compute these tau weights for determining connectivity, one needs a model of data redundancy, here expressed as a vectorial training image (Ti) constructed using a prior conceptual knowledge of geology and the physics of data measurement. From such a vectorial Ti, the tau weights can be computed exactly. Neglecting data redundancy leads to an over-compounding of individual data information and the possible risk of making extreme decisions.     

Non-Linear Theory and Power-Law Models for Information Integration and Mineral Resources Quantitative Assessments

Singular physical or chemical processes may result in anomalous amounts of energy release or mass accumulation that, generally, are confined to narrow intervals in space or time. Singularity is a property of different types of non-linear natural processes including cloud formation, rainfall, hurricanes, flooding, landslides, earthquakes, wildfires, and mineralization. The end products of these non-linear processes can be modeled as fractals or multifractals. Hydrothermal processes in the Earth’s crust can result in ore deposits characterized by high concentrations of metals with fractal or multifractal properties. Here we show that the non-linear properties of the end products of singular mineralization processes can be applied for prediction of undiscovered mineral deposits and for quantitative mineral resource assessment, whether for mineral exploration or for regional, national and global planning for mineral resource utilization. In addition to the general theory and framework for the non-linear mineral resources assessment, this paper focuses on several power-law models proposed for characterizing non-linear properties of mineralization and for geoinformation extraction and integration. The theories, methods, and computer system discussed in this paper were validated using a case study dealing with hydrothermal Au mineral potential in southern Nova Scotia, Canada.     

Intrinsic sample methods for mineral exploration and resource assessment

We report on an objective methodology, referred to as intrinsic sample methodology, for the delineation of exploration target areas or resource areas for assessment. Important features of the methodology include (1) identification of recognition criteria for critical genetic factors, (2) synthesis of new variables from enhanced geodata, (3) estimation of logit probability models, and (4) cutting of estimated logit probabilities to delineate exploration targets or resource areas. The methodology is demonstrated on the Walker Lake quadrangle of Nevada and California.     

Energy efficiency evaluation,technology gap ratio,and determinants of energy productivity change in developed and developing G20 economies: DEA super-SBM and MLI approaches

This study employed Slack-based measure (SBM), Meta-frontier analysis, and Malmquist–Luenberger index (MLI) approaches to measure energy efficiency (EE), production technology heterogeneity, and energy productivity variation and its main determinants in developed and developing G20 countries for the period 1995–2020. The study's findings are: (i) Average EE for G20 countries is 0.8577, but still has an improvement potential of 14.23 percent. (ii) Developed countries have a higher average EE than developing (0.8927 > 0.8290). Results further revealed that energy efficiency scores in Argentina, Australia, Brazil, France, Saudi Arabia, South Africa, the US, the UK, and Korea are>1. (iii) Technology gap ratio (TGR) value in developed countries is higher than in developing (0.9869 > 0.6801), indicating that developed countries have advanced energy technologies superiority. The average MLI is less than one, showing a decline in energy productivity mainly due to a decline in technical efficiency, as EC < TC. (iv) Developed G20 countries get 0.64 percent aggregate growth in energy productivity as their MLI score is 1.0064, mainly due to technological growth (TC = 1.0161). Developing G20 countries, on the other hand, witnessed a decline in their energy productivity during 1995–2020, as MLI = 0.9925 > 1, designating that, on average, there is a 0.75 % decline in MLI.