Quantitative characterization of different coal rank reservoirs permeability based on NMR and X-CT technology

With the increasing development of coalbed methane (CBM) field, the quantitative characterization and evaluation of coal reservoir physical properties is becoming more and more important to CBM scale development. In order to solve the limitations of conventional methods for testing coal reservoir physical properties, the authors used the high-tech technologies such as nuclear magnetic resonance technology and CT scanning technology to effectively solve the problems of in-situ and integrity of rock samples and acquire the porosity and permeability. Nuclear magnetic resonance and CT scanning experiments of coal samples were carried out to rapidly obtain the pore type, pore size distribution and connectivity, effective porosity, spatial distribution of pore fissures and other refined coal reservoir physical parameters, based on the samples of middle and low rank coal in Shenfu block and high rank coal in Shizhuangnan block. So a set of quantitative characterization analysis technology that can be applied to coal reservoirs with different coal rank was formed.     

Geology and mineralization of the Sanshandao supergiant gold deposit (1200 t) in the Jiaodong Peninsula,China: A review

The Jiaodong Peninsula in Shandong Province, China is the world’s third-largest gold metallogenic area, with cumulative proven gold resources exceeding 5000 t. Over the past few years, breakthroughs have been made in deep prospecting at a depth of 500–2000 m, particularly in the Sanshandao area where a huge deep gold orebody was identified. Based on previous studies and the latest prospecting progress achieved by the project team of this study, the following results are summarized. (1) 3D geological modeling results based on deep drilling core data reveal that the Sanshandao gold orefield, which was previously considered to consist of several independent deposits, is a supergiant deposit with gold resources of more than 1200 t (including 470 t under the sea area). The length of the major orebody is nearly 8 km, with a greatest depth of 2312 m below sea level and a maximum length of more than 3 km along their dip direction. (2) Thick gold orebodies in the Sanshandao gold deposit mainly occur in the specific sections of the ore-controlling fault where the fault plane changes from steeply to gently inclined, forming a stepped metallogenic model from shallow to deep level. The reason for this strong structural control on mineralization forms is that when ore-forming fluids migrated along faults, the pressure of fluids greatly fluctuated in fault sections where the fault dip angle changed. Since the solubility of gold in the ore-forming fluid is sensitive to fluid pressure, these sections along the fault plane serve as the target areas for deep prospecting. (3) Thermal uplifting-extensional structures provide thermodynamic conditions, migration pathways, and deposition spaces for gold mineralization. Meanwhile, the changes in mantle properties induced the transformation of the geochemical properties of the lower crust and magmatic rocks. This further led to the reactivation of ore-forming elements, which provided rich materials for gold mineralization. (4) It can be concluded from previous research results that the gold mineralization in the Jiaodong gold deposits occurred at about 120 Ma, which was superimposed by nonferrous metals mineralization at 118–111 Ma. The fluids were dominated by primary mantle water or magmatic water. Metamorphic water occurred in the early stage of the gold mineralization, while the fluid composition was dominated by meteoric water in the late stage. The S, Pb, and Sr isotopic compositions of the ores are similar to those of ore-hosting rocks, indicating that the ore-forming materials mainly derive from crustal materials, with the minor addition of mantle-derived materials. The gold deposits in the Jiaodong Peninsula were formed in an extensional tectonic environment during the transformation of the physical and chemical properties of the lithospheric mantle, which is different from typical orogenic gold deposits. Thus, it is proposed that they are named “Jiaodong-type” gold deposits.©2021 China Geology Editorial Office.     

超声波测风仪风速的不同算法误差分析

超声波测风仪与气象业务用风向标测风仪相比具有诸多优势,可为气象业务中风向风速观测急需解决的较多问题提供解决方案。为促成超声波风速仪尽早在气象部门业务应用,同时解决资料同化等问题,研究和选择适用于超声波测风仪的风速平均(平滑)算法显得极为重要。为此,从超声波测风仪测量原理出发,介绍了超声波测风仪获取数据的特点;利用台站获取的超声波测风仪风速的秒数据,采用不同时段、不同平均(平滑)方法,计算风速多种形式的平均值,通过统计、分析和比较,获得了标量和矢量不同算法下风速平均值的特性差异及其之间的误差,进一步验证了标量平均大于矢量平均的结论。通过对超声波测风仪的风速算法研究及其误差分析,对减小因算法带来的风速测量误差提供方法,同时探讨了超声波测风仪在气象业务使用的可能和方向。     

2010—2016年江西省暖季短时强降水特征分析

利用江西省2010—2016年5—9月1597个观测站逐小时降水资料对江西省短时强降水进行统计分析。采用REOF将降水场划分为5个区域：赣北南部（Ⅰ区）,抚州市及赣州中部（Ⅱ区）,赣北北部（Ⅲ区）,赣南南部、北部（Ⅳ区）以及赣中西部（Ⅴ区）。短时强降水高频区主要分布在山地及河谷附近,分别为湘赣交界罗霄山脉东侧、武夷山西侧、信江河谷、乐安河谷和昌江河谷。河谷附近短时强降水频次以昌江河谷最高（16.9次/a）,山地附近最高在罗霄山脉东侧（12.6次/a）,极端短时强降水分别位于上饶市东北部山区（3.7次/a）及九岭山南侧的锦江河谷（3.3次/a）。短时强降水主要发生在5月第3候,6、7月第3~4候以及8月第2~3候。Ⅳ、Ⅴ区具有单峰型的日变化特征;Ⅰ、Ⅱ、Ⅲ区具有双峰型的日变化特征。主峰基本集中在下午17时;次峰在上午08—10时。短时强降水对暴雨贡献率基本在40%以上,Ⅰ、Ⅱ区的暴雨天气过程将近一半是由短时强降水贡献的。信江河谷是暴雨雨量中心,但并不是短时强降水雨量中心;昌江河谷与武夷山西麓既是暴雨中心也是短时强降水中心。     

蒙脱石红移、蓝移及水化特征的谱学分析

对提纯蒙脱石、钠化蒙脱石、有机插层蒙脱石进行紫外-可见光学吸收谱分析、红外光谱分析,发现蒙脱石随着粒度的变化产生红移和蓝移现象。1631插层样品较钠化样品红移20 nm以上,而提纯的胶体粒子样品较1631插层样品SM G-1631红移80 nm;由于提纯蒙脱石样品粒度变细羟基伸缩振动吸收峰向高波数移动了1.69 cm-1,即蓝移了1.69cm-1。蒙脱石水化性能的XRD分析表明,蒙脱石吸水后晶层发生膨胀、剥离,脱水时分散后的晶层发生凝聚作用,即面-面结合作用,形成蒙脱石“定向性层状集合体”衍射峰的d值产生了相应的变化,这种凝聚作用是蒙脱石分散剥离的逆作用,但凝聚后形成的凝聚蒙脱石的衍射谱特征与原始蒙脱石的大不相同。蒙脱石红移、蓝移及水化特征的谱学分析研究丰富了天然纳米蒙脱石矿物材料晶体化学研究的内容,具有重要的理论意义。     

Spatial changes in a macrozoobenthic community along environmental gradients in a shallow brackish lagoon facing Sendai Bay, Japan

The spatial distribution, abundance, and assemblage structure of macrozoobenthos were examined at 45 stations in a brackish lagoon (Idoura Lagoon, Japan) to examine the animal–environmental relations in estuarine soft-bottom habitats. We found a total of 23 taxa; the polychaetes Heteromastus sp., Hediste spp., and Prionospio japonica and the isopod Cyathura muromiensis numerically dominated the community. Cluster analysis and one-way analysis of similarity (ANOSIM) identified seven groups of stations that had significantly different macrozoobenthic communities; these were subsequently consolidated into five habitat groups according to their association with environmental characteristics. Canonical correspondence analysis (CCA) showed that salinity, silt-clay content, and the oxidation–reduction potential (ORP) of the sediment strongly affected the macrozoobenthos distribution pattern in the lagoon, whereas other factors (e.g., relative elevation of the habitat and sediment organic content) had much weaker effects. Similarity percentages (SIMPER) procedures indicated that the polychaete Notomastus sp. and the bivalve Macoma contabulata were specific to habitats with low salinity and reduced mud, whereas the bivalve Nuttallia olivacea was specific to sandy bottoms. Heteromastus sp. and Hediste spp. achieved their highest densities in rather oxidized sediments. The acid-volatile sulfide (AVS) content in the sediment was suggested as another possible factor affecting macrozoobenthic density. Our results clearly demonstrate that macrozoobenthic assemblages in estuarine soft-bottoms have high spatial heterogeneity on a small scale (e.g., hundreds of meters) related to physical and chemical environmental changes. Our data also suggested the importance of sediment redox condition (e.g., ORP and AVS content) and sediment grain size as structuring factors in estuarine soft-bottom communities as well as the salinity in the habitat.     

Distribution of phytoplankton community in relation to environmental parameters in cage culture area of Sepanggar Bay,Sabah, Malaysia

This paper covers spatial and temporal variation in phytoplankton communities and physico-chemical water properties in the cage culture area of Sepanggar Bay, Sabah, Malaysia based on field measurement conducted during July 2005 to January 2006 to study the spatial and temporal variation in phytoplankton communities and physico-chemical water properties of the bay. Phytoplankton samples and water parameters data were collected from five different stations located inside the bay during Southwest, Interseasonal and Northeast monsoons. Forty phytoplankton genera, representatives of 23 families, were found in the study area with a mean abundance of 1.55 ± 1.19 × 10⁶ cells L⁻¹. Most of these genera belong to diatoms (82.17%), Dinoflagellates (17.55%) and cyanobacteria (0.29%). Three genera were found to be dominant (>10%) in phytoplankton abundance and these were Coscinodiscus spp. (36.38%), Chaetoceros spp (17.65%) and Bacteriastrum spp. (10.98%). The most dominant genus was Coscinodiscus spp. which showed high abundance during all monsoons and stations (except Station 3). Among the seven environmental parameters tested in this study, water temperature, pH and suspended sediment concentration were found to be significantly different between monsoons. On the other hand, no significant differences were found between stations for the studied physico-chemical parameters. A clear differences in phytoplankton densities were observed between monsoons and stations with higher mean abundances during interseasonal monsoon (2.40 ± 1.37 × 10⁶ cells L⁻¹) and at station five (2.05 ± 0.74 × 10⁶ cells L⁻¹), respectively. Conversely, the diversity indices, both Shannon–Wiener (H^′)$\left(H^{\prime }\right)$ and Pielou (J^′)$\left(J^{\prime }\right)$, showed no significant difference throughout stations and monsoons (except (H^′)$\left(H^{\prime }\right)$ for monsoons). Analysis of similarity (ANOSIM) results demonstrated temporal differences in phytoplankton community structure with highly diverse phytoplankton assemblage. Through cluster analysis five groups of phytoplankton were attained (at 40% similarity level) though no marked separation of the taxonomic classes pointed towards the constant pattern of the phytoplankton assemblage in the studied area.     

Mapping benthic habitat in regions of gradational substrata: An automated approach utilising geophysical,geological, and biological relationships

The relationship between acoustic backscatter, sediment characteristics and benthic habitat is examined using high-resolution sidescan sonar data collected at the Loch Linnhe artificial reef site on the west coast of Scotland. The site is typical for the continental shelf of NW Europe, with a mix of seabed environments from muddy to coarse, stony substrata on a 10–100 m length scale. A sidescan sonar mosaic was produced and classified according to derived backscatter parameters (mean, median and standard deviation of the backscatter values) using an unsupervised classification procedure. The accuracy of the final classified map was assessed by comparison with a ground-truthing survey in which the biological habitat was derived from underwater video footage. The sidescan correctly predicted seabed surface characteristics of observed biological habitat with 78% accuracy. A second, and more challenging test of the acoustic data to correctly predict biological habitat was made by comparing it with data from 21 grab sampling stations. These stations were divided into three groups using multivariate statistical techniques based on their backscatter properties. Benthic assemblage structure was found to be significantly distinct between the high and low, and the medium and low backscatter stations. There was a low to moderate but significant correlation between the multivariate patterns of acoustic backscatter, benthic assemblage structure, and particle size distribution. The work shows that even in areas with subtle and gradational changes in substratum, the sidescan was able to predict biological community with an acceptable accuracy.     

基于声波探测海底浅层沉积物特性的方法研究

利用声波在水中的传输特性进行海底浅层沉积物特性的探测。在实践应用中有实验室方法、现场测量方法和海底声学遥测方法,并研制出大量的仪器。由于海上和海底实际条件的限制,声波探测方法都存在一定的不足之处,由此提出了声衰减测试沉积物特性以及建立实验室模拟海底环境探测方法的设想。     

流体替代技术及应用分析

地震技术是研究隐蔽油气藏的关键技术。岩石物理是地震信号与储层性质之间的桥梁,它可以帮助我们更好的理解岩石和流体性质的地震响应。流体替代分析是岩石物理分析的重要部分,它是流体识别和储层定量研究的工具之一,在AVO分析中起了重要的作用。流体替代的理论基础是Gassmann方程。在岩石物理技术指导下,对某工区探井进行了流体替代分析,并根据替代后的结果分析了波阻抗随深度、岩性和含油气性变化的规律,同时根据替代结果进行了AVO正演研究,比较分析了储层中流体分别为盐水、气和油时的响应特征,并据此根据实际的部分叠加道集进行了烃类异常识别。