Geological Types Research Articles

A Method for Identifying Channeling Paths in Low-Permeability Fractured Reservoirs

Often oilfield fractured horizontal wells produce water flowing in multiple directions. In this study, a method to identify such channeling paths is developed. The dual-medium model is based on the principle of inter-well connectivity and considers the flow characteristics and related channeling terms. The Lorentz curve is drawn to qualitatively discern the geological type of the low-permeability fractured reservoir and determine the channeling direction and size. The practical application of such an approach to a sample oilfield shows that it can accurately identify the channeling paths of the considered low-permeability fractured reservoir and predict production performances according to the inter-well connectivity model. As a result, early detection of water channeling becomes possible, paving the way to real-time production system optimization in low-permeability fractured reservoirs.

Geological characteristics and enrichment model of Permian Mao 1 Member shale gas reservoirs in Nanchuan area

To understand the shale gas reservoirs in the first member of the Permian Maokou Formation (Mao 1 Member) in Nanchuan area of the Sichuan Basin, we used outcrops, cores, mineralogical and geochemical datas, thin-section analysis, and argon-ion-polishing scanning electron microscopy results with logging and seismic attribute prediction techniques to study the sedimentary facies, source rocks, reservoir properties and types. The geological characteristics and enrichment model of shale gas reservoirs of the Mao 1 Member were revealed and are summarized as follows: (1) the Maokou Formation can be divided into four members from bottom to top. The Mao 1 Member is located in the relatively deep-water gentle slope of a carbonate platform, comprising well-developed dark-gray/grayish-black carbonaceous mudstone, calcareous mudstone, argillaceous limestone, and bioclastic limestone. Carbonaceous and calcareous mudstones, with a relatively high total organic carbon content (TOC0.5–5.1%) and moderate thermal maturity (Ro: 2.0–2.3%), are potentially good hydrocarbon source rocks with possibly new type of atypical shale gas reservoir; (2) organic pores, dissolution pores, grain margin fractures, and shrinkage fractures are developed in the Mao 1 Member and may form a reservoir of a complex “pore–fracture–network,” which is beneficial to gas storage and migration; (3) the shale gas in the Mao 1 Member has the accumulation and enrichment model of “integrated source and reservoir, continuous distribution, and structure-fracture dual reservoir control” with a continuous distribution area exceeding 500 km2 and a geological resource volume exceeding 70 billion cubic meters; therefore, it has great exploration potential for shale gas. The research results are crucial in improving the understanding of new type of shale gas geology and guide shale gas exploration in southeastern Sichuan.

Flood Response and Civil-Military Coordination in Pakistan

It is an established fact that Pakistan is prone to disasters and damage caused by these disasters is immeasurable and varies with the geographical location, climate, and type of earth surface, geology and degree of vulnerability. The paper focus on underpinnings of flood response, however, emphasis will be on role of Corps of Engineers (Army), Civil-Military coordination in 2010 Floods and prolonged employment of Army on such tasks. The main focus of this paper is on the existing role of military, their relationship with the civil set-up and the expectations of both the group from each other. Moreover, this paper also reviews about the existing frameworks and mechanisms of coordination between the two groups. The paper may help managers, policy makers and army engineers and government authorities to realistically evolve flood response, and decentralized mode of operation should be adapted from national to regional level in order to follow an integrated framework for bringing all stakeholders and victims together for developing an organized response system. However, the prolonged employment of Army on mitigation of disasters must be avoided.

Centres of endemism in Borneo and their environmental correlates revealed by endemic plant genera

Identifying areas of high value for biodiversity and understanding their potential environmental correlates is a critical task useful for prioritising conservation attention as natural habitats continue to be threatened. The distributions of species of 65 plant genera endemic to Borneo were mapped and modelled to examine where they are concentrated in centres of endemism, taking into consideration the historical unevenness in general botanical collecting. Overlapping distributions indicate that the areas richest in species of endemic genera are found especially in the lowland forests of northwest Borneo. In comparison, endemic species from selected non-endemic genera are concentrated in upland areas such as the central mountain chain and Mount Kinabalu. Spatial regression models show that species richness of the endemic genera is negatively correlated with historical climate instability and present-day precipitation seasonality but positively correlated with present-day annual precipitation, temperature seasonality, number of rivers and number of geological types. Centres of plant endemism revealed by the endemic genera, a distinctive subset of Borneo's endemic species, reaffirm the critical importance of lowland forest habitats in Borneo for plant diversity and endemism.

Optimization of fracture design for horizontal wells in Mahu region based on machine learning

The Mahu tight glutenite reservoir is highly heterogeneous, and the geology and construction conditions of each well are uneven. The fracturing design scheme lacks pertinence. The main control factors of the fracturing effect need to be further understood. Therefore, we establish a set of machine learning-based process frameworks for horizontal well productivity prediction and fracturing design optimization in the Mahu area. Taking 75 fractured horizontal wells in the Mahu area as an example, based on 16 influencing factors of 2 types of geology and engineering, the random forest algorithm is used to determine the main control factors of post-fracturing productivity, and a error back Propagation (BP) neural network productivity prediction model optimized by genetic algorithm is established. Based on this, the optimal design of fracturing for horizontal wells is carried out. The results show that the productivity of two wells in the field is increased by 9.3% and 37.3% respectively after the fracturing parameter scheme is optimized. The established productivity prediction and fracturing design optimization methods can be applied to other oil fields and provide targeted guidance for on-site construction.

Spatial distribution and influence factors of landslides triggered by the 2019 Ms 6.0 Changning, Sichuan, China Ms6.0 earthquake: A statistical analysis based on QGIS

Based on the QGIS platform, using high-resolution remote sensing images, this work interpreted co-seismic landslides triggered by the 2019 Changning, Sichuan Ms6.0 earthquake. In total, 496 landslides with an occupation area of 1.2km2 were mapped. Then considering three types of influence factors, seismology, topography and geology, the distribution pattern of these landslides was statistically analysed by PyQGIS console and existing analysis functions. The results show that the landslides are mostly distributed at places with elevations of 400-500m, slopes facing N and SE directions, media of mudstone, tuff and siltstone, sites 2-6km distant to the fault, and zones of PGA 0.4-0.5g. This study will contribute to further understanding of the genesis and risk assessment of co-seismic landslides, providing useful information for research of the tectonic activity in the study area.

Erodibility of soils of varying land utilization types and lithologic materials in central southeastern Nigeria


 
 
 Land use and parent materials influence behaviour of soils including responsiveness to erosion forces. The study investigated some soil properties related to erodibility in Abia and Imo States of Nigeria. Soil sampling was guided by geology and land use type. Random sampling technique was adopted in field studies. Two parent materials and three land use types were chosen for the study. In each parent material, three land use types were studied and in each land use, three soil profiles were sunk, described, and sampled using FAO procedure. Soil samples were subjected to laboratory analyses and data generated were analyzed using descriptive and inferential statistical tools. Results showed that sand sized particles ranged from 533.10 to 778.80 g kg–1 and this distribution differed significantly between parent materials. Silt content ranged from 141.70 g kg–1 in soils derived from false-bedded sandstone to 202.20 g kg–1 in shale-derived soils. Clay-sized particles ranged from 77.30 g kg–1 in soils derived from false-bedded sandstone to 264.70 g kg–1 in shale-derived soils, respectively. Water-stable aggregate ranged from 19.38% in false-bedded sandstone to 29.23% in shale-derived soils. The DR (dispersion ratio) mean values ranged between 4.26 in shale and 8.46 in false-bedded sandstone, while the CDI (clay dispersion index) mean values ranged between 2.17 in shale and 8.41 in false-bedded sandstone, respectively. The forest soils had the lowest values of both DR (6.89) and CDI (6.40) for soils of the false-bedded sandstone, 3.85 and 1.59 for those derived from shale. The clay flocculation index (CFI) had mean of 2.16 in false-bedded sandstone and 7.83 in shale. In soils of the varying land use types, the mean soil pH (H2O) ranged from 4.28 to 4.64 in soils derived from false-bedded sandstone and 4.27-5.57 in those derived from Shale. From the results, parent material and land use influenced soil erodibility parameters (water-stable aggregates, mean-weight diameter, DR, CDI, and CFI) and other soil properties such as organic carbon, bulk density, and moisture content.
 
 

PH variability in catchment flows to estuaries – A South African perspective

River inflow plays an integral role on the water quality characteristics of estuaries, including pH. This study aimed to investigate pH variability in river inflow to South African estuaries and how these might be influenced by catchment characteristics. Specifically, three hypotheses were tested: 1) catchment geology is a dominant influencing factor of pH in river inflow, 2) catchment vegetation and anthropogenic pressures, e.g., urban and agriculture, act as modifiers of geology-driven ambient pH, and 3) seasonality in river flow rates can alter pH levels (e.g., pH decreasing during periods of high flow). First, drivers of pH variability were explored in relation to electrical conductivity, total alkalinity, and catchment geology type, as well as vegetation and key anthropogenic pressures. Thereafter, temporal variability was evaluated considering both inter-annual and seasonal variability also including variability in flow rates. Values of pH displayed an exponential relationship with electrical conductivity and total alkalinity, and as hypothesised pH variability was primarily influenced by catchment geology. Results also indicated that catchment vegetation (e.g., peatlands and fynbos) and/or anthropogenic pressures (e.g., urban and agriculture) act as modifiers causing pH to deviate from geology-driven ambient equilibria, especially in Table Mountain Group sandstone-dominated systems. Only limited trends in inter-annual variability were observed, mostly linked to increases in pH with increases in anthropogenic pressures. Further, a significant inverse relationship between pH and river flows was present, mostly in systems showing marked seasonality in rainfall. This study adds to our understanding of the variability of pH in river inflows to estuaries, and highlights some of the key influencing factors. Indeed, results suggest that anthropogenic pressures in catchments potentially are leading to alkalinisation of river inflow, contrary to the potential effect of ocean acidification. Finally, this study highlights the ripple effects of upstream catchment practices on downstream coastal ecosystems such as estuaries, emphasising the need for integrated catchment-to-coast management.

Development of statistical model for predicting terrestrial gamma radiation dose

Natural environmental radioactivity aroused mainly from primordial radionuclides such as 40K and 238U and 232Th decay series, and have been present in varying concentrations within the earth and in the tissue of every living being. Natural radioactivity can be found everywhere; in the soil, public water supplies, oil, and the atmosphere and it poses a measurable exposure to human beings. The present study developed a statistical model that can be used to predict the Terrestrial Gamma Radiation Dose rates (TGRD) based on soil types and geological formations irrespective of the environment. About 295 TGRD measurements were taken using a micro-Roentgen survey meter (model 19) manufactured by Ludlum, from different locations within the study area. Statistical Package for Social Sciences (SPSS) was utilized in establishing the relationships between TGRD with underlying geological formations and soil types as well as in the development of the model. The developed model was tested by predicting the TGRD value over different combinations of soil types and geological formations, and it was found to fit in well with more than 80% degree of accuracy which is within the acceptable limit. The developed model in this study, may help in establishing the background radioactivity levels in a terrestrial environment that can be used to evaluate any changes that may arise as a result of any release due to both natural and or human activities in a certain area.

A novel constrained dense convolutional autoencoder and DNN-based semi-supervised method for shield machine tunnel geological formation recognition

Accurately acquiring the geological information of the tunnel face will help to set the optimal operational parameters, so that the shield machine can achieve better tunneling performance. The design of the shield machine prevents the operator from observing the surrounding environment directly, and the soft methods which can utilize machine parameters to recognize geological conditions indirectly are becoming a research hotspot. However, current soft methods are all supervised methods which can only use the few machine data with geological type labels, and the unlabeled machine data that is much more than the labeled machine data is wasted. To make the most of all the collected in-situ data to boost the performance of the geological formation recognition model, a novel constrained dense convolutional autoencoder and DNN-based semi-supervised method is proposed. To begin with, 177 machine parameters related to geological conditions are selected and preprocessed. Then, a novel geological feature extractor is obtained via the proposed constrained dense convolutional autoencoder and the unlabeled data. Eventually, a DNN-based geological feature classifier is trained on the basis of the established feature extractor and the labeled machine data, which is capable of recognizing geological formation of the tunnel face. In-situ data collected from a Singapore project (stacked twin bored tunnels) was used to prove the superiority of the proposed method. The results show the constrained dense convolutional autoencoder can extract geological-related features accurately, and the proposed method outperforms other supervised soft methods. Its classification performance in one tunnel is 23.98%, 17.47%, 1.93%, and 18.52% higher than the random forest-based, decision tree-based, KNN-based, and SVM-based methods, respectively. Its classification performance in another tunnel is 33.54%, 33.75%, 42.87%, 43.58%, 33.75%, 49.91%, 37.77%, and 27.04% higher than the random forest-based, SVM-based, decision tree-based, DNN-based, KNN-based, CNN-based, ResNet-based, and DenseNet-based methods, respectively. Thus, the novel semi-supervised method has significantly better generalizability than the currently adopted supervised soft methods.

Europa Clipper Preparatory Photometry to Constrain Surface Properties

Abstract We infer the surface reflectance properties of Europa using multispectral data sets available from previous missions. We use 21 full-disk images of Europa from Voyager’s Imaging Science System, Galileo’s Solid State Imaging, and New Horizons’ Long Range Reconnaissance Imager at differing observation geometries (10°–128° (phase angle)) to compute disk-integrated surface-scattering properties over various geologic units. The derived empirical photometric models will serve the practical goals of data acquisition, aid in the calculation of instrument integration times, and facilitate quick-look data products for images acquired by Europa Clipper and other future missions to Europa. We use the Minneart and Lommel–Seeliger plus Lambert reflectance models to constrain the photometric parameters of Europa’s surface. We find that the surface albedo parameter, B 0, in the Minneart function gradually decreases with increasing phase angles. We also note that the photometric properties of Europa (geometric albedo at 0.47 μm is 0.72 on the leading side and 0.62 on the trailing side) require a significant “Lambert” term (A < 1) in the Lommel–Seeliger plus Lambert reflectance model. We also observe that the photometric parameters are not highly dependent on the geologic terrain type despite their visibly different albedos.

A Statistical Analysis of Well Failures in Baltimore County

A statistical evaluation of the Baltimore County water well database is performed to gain insight on the sustainability of domestic supply wells in crystalline bedrock aquifers over the last 15 years. Variables potentially related to well yield that are considered included well construction, geol ogy, well depth, and static water level. A variety of statistical methods are utilized to assess correlation and significance from a database of approxi mately 8,500 wells, and a logistic regression model is developed to predict the probability of well failure by geology type. Results of a two-way analysis of variance technique indicate that the average well depth and yield are sta tistically different among the established geology groups, and between failed and non-failed wells. The static water level is shown to be statistically dif ferent among the geology groups but not among failed and non-failed wells. A logistic regression model results that well yield is the most influential vari able for predicting well failure. Static water level and well depth was not found to be significant in predicting well failure.

Reservoir Characterization, Scenario-Based Models Optimize Development Planning

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 202273, “Reservoir Characterization and Scenario-Based Modeling To Optimize Development Planning of the Jurassic Plover Formation in the Ichthys Field, North West Shelf of Australia,” by Kazuyuki Yamamoto, SPE, Shuji Yamamoto, and Toby Jones, INPEX, et al., prepared for the 2020 SPE Asia Pacific Oil and Gas Conference and Exhibition, originally scheduled to be held in Perth, Australia, 20–22 October. The paper has not been peer reviewed. The Plover Formation is one of two reservoirs in the Ichthys field of the Australian North West Shelf. The objective of this study is to build multiple scenario-based models to optimize development planning in preparation for the upcoming production phase. The authors have integrated data and interpretations of thin sections, cores, well logs, and seismic data to create multiple geological concepts for the field and to identify key geological uncertainties. Introduction The Ichthys liquefied natural gas project is one of the world’s largest and involves the development of a gas-condensate field in the Browse Basin. The field is approximately 220 km offshore Western Australia and covers an area of approximately 800 km2 with an average water depth of approximately 250 m. The field is currently under preparation for the development of the Plover Formation. The authors conducted an integrated subsurface evaluation and built reservoir models with newly reprocessed 3D seismic data to optimize Plover development planning. Considering the geological uncertainty given the limited production data gathered before the production phase, the multiple deterministic approach was selected as the best option to optimize development planning. In this approach, it is important to capture all geological scenarios that may occur in the field and to build reservoir models in which the scenario concepts are explicitly integrated. A multidisciplinary team was organized to conduct this study. Geology of the Plover Formation The Plover Formation consists of sandstones, shales, igneous rocks, and a minor amount of coal. The depositional environment is fluvial to shallow marine. The average thickness of the formation is approximately 360 m. Based on the stratigraphic correlation anchored by mainly palynological biostratigraphic data, the formation has been subdivided into five stratigraphic members. The formation is overlain by the Ichthys Formation, which is composed mainly of argillaceous sandstone and shale deposited in a tidally influenced, lower-delta-to-shelf environment. Although the nine existing exploration wells broadly cover the entire field, the spacing between the wells is still large (8–10 km). Further-more, core coverage is low, especially in the reservoir sandstone intervals. Igneous rock, predominantly basaltic in composition and likely extrusive in origin, occurs more in the eastern part of the field. Igneous activity has complicated the distribution and connectivity of the reservoir sandstones in the Ichthys field. Key Geological Uncertainties Rock Type (RT). The results of petrographic analysis of rock samples from the Ichthys field and other surrounding fields indicate that the sandstones of the Plover Formation can be separated into multiple RTs: RT1 and RT2, with RT1 subdivided into RT1a and RT1b. Very little data exist from RT2 in the fluvial/distributary channel sandstones in the Ichthys field in comparison with other fields; this is considered to be the result of limited core. The assumption that RT2 exists in the field is critical to prepare for the possibility that a future well may be drilled that might have some nontrivial quantity of RT2.

Prediction Landslide Location Area Using ANN (Case study in Bangli Regency, Bali Indonesia)

Landslides are significant geo-hazards heavily impacting many regions of the world regarding human lives and economic losses. The large magnitude of natural forces involved in landslides makes actions of mitigation or prevention unfeasible, with exceptions for minor occurrences or under special conditions. Many old methods have been applied in landslide management and/or prediction, such as overlays or weighting methods. The newest/advanced methods are still being developed and one of the newest methods is Artificial Neural Network (ANN). ANN are biologically inspired computer programs designed to simulate how the human brain processes information. Many types of ANN exist; the most famous one is Multilayer Perceptron (MLP) Neural Network Algorithm with FeedForward model. MLP consists of three parts: the input layers as neurons representing the value of data; the hidden layer, which demonstrates the network training process; and the output layer, which provides the prediction of the landslide areas. In this research, the input layer consists of landslide location characteristics, such as the rainfall intensity, land cover, slope, geological types, and rate displacement of landslides. As a case study, Bangli Regency was selected. In 2017 there was a landslide disaster in the Kintamani District, Bangli Regency, which resulted in dozens of people missing or dead, and several houses destroyed. In this study different numbers of neurons were used in the hidden layer (15, 50, 100, and 150 neurons). The best performance is obtained at 150 neurons, with 0.9677 (96,77%) for the test set.

Intermittent rivers and ephemeral streams: Perspectives for critical zone science and research on socio‐ecosystems

AbstractIntermittent rivers and ephemeral streams (IRES) are now recognized to support specific freshwater biodiversity and ecosystem services and represent approximately half of the global river network, a fraction that is likely to increase in the context of global changes. Despite large research efforts on IRES during the past few decades, there is a need for developing a systemic approach to IRES that considers their hydrological, hydrogeological, hydraulic, ecological, and biogeochemical properties and processes, as well as their interactions with human societies. Thus, we assert that the interdisciplinary approach to ecosystem research promoted by critical zone sciences and socio‐ecology is relevant. These approaches rely on infrastructure—Critical Zone Observatories (CZO) and Long‐Term Socio‐Ecological Research (LTSER) platforms—that are representative of the diversity of IRES (e.g., among climates or types of geology. We illustrate this within the French CZO and LTSER, including their diversity as socio‐ecosystems, and detail human interactions with IRES. These networks are also specialized in the long‐term observations required to detect and measure ecosystem responses of IRES to climate and human forcings despite the delay and buffering effects within ecosystems. The CZO and LTSER platforms also support development of innovative techniques and data analysis methods that can improve characterization of IRES, in particular for monitoring flow regimes, groundwater‐surface water flow, or water biogeochemistry during rewetting. We provide scientific and methodological perspectives for which this interdisciplinary approach and its associated infrastructure would provide relevant and original insights that would help fill knowledge gaps about IRES.This article is categorized under: Water and Life > Stresses and Pressures on Ecosystems Science of Water > Hydrological Processes Water and Life > Conservation, Management, and Awareness

Statistical analysis of terrestrial gamma radiation dose rates in relation to different geological formations and soil types of Katsina State, Nigeria

ABSTRACT Terrestrial gamma radiation is the major source of outdoor radiation exposure to human being. Because of the variation of underlying geological characteristics of surface soil, the terrestrial gamma radiation dose (TGRD) rates vary significantly with the soil type. This work performed in situ measurements of the TGRD rate for a range of geological formation and soils of Katsina State, Nigeria by using a portable hand-held radiation survey metre, RADOS. The TGRD rates ranged between 45 and 271 nGyh−1 with an overall mean value of 116 nGyh−1, which is two times higher than the world average value of 59 nGyh−1. Geological formation (Silicified sheared rock) was found to have the highest mean TGRD value of 163 nGyh−1. Likewise, soil type (lithosols, ferruginous crusts and ferruginous tropical soils) appeared to have the highest mean TGRD value of 134 nGyh−1. One-way ANOVA was used to investigate the variation of the significant difference between the geological formations and soil types with TGRD, which shows the influence of geological formation and soil types on the measured TGRD values of the study area. Measured data could further be used to evaluate the public radiation exposure and in formulating safety standards and radiological guidelines.

Influence of surface geology on phosphorus export in coastal forested headwater catchments in Akita, Japan

ABSTRACT Surface geology is a key factor regulating the geographical patterns of P export; however, geographically extensive data on P export mechanisms from natural coastal mountain regions are lacking. We compared stream-water characteristics in forested headwater catchments with different types of surface geology (marine sedimentary rocks [MSRs] and igneous rocks [IRs]) and evaluated the factors regulating soluble reactive phosphorus (SRP) concentrations in stream water. Geographically extensive stratified sampling was conducted: stream-water and sediment samples were obtained from 66 MSR catchments and 55 adjacent IR catchments along the coastal forested mountain regions in Akita, Japan. SRP and major cations and anions in stream waters were analyzed. To evaluate the effect of ionic composition on SRP, sediments were extracted with NaCl and CaCl2 solutions and the SRP concentrations in the extracts were measured. Stream SRP was significantly higher in MSR catchments (median 23 µg L−1) than in IR catchments (median 8 µg L−1) (P < 0.001), and tended to be higher in MSR catchments with younger rocks. Dissolved inorganic nitrogen (DIN) did not differ between catchments with different geologies; therefore, DIN/SRP was significantly lower in MSR catchments (median 18), close to the Redfield ratio. On a Piper diagram, high-SRP stream waters were of the NaCl water type, and stream SRP was significantly correlated with Na+ (r = 0.642, P < 0.0001). In IR catchments, stream waters had relatively higher Ca2+ and Mg2+ concentrations. SRP in the sediment extracts was significantly higher in MSR catchments and samples obtained by NaCl extraction than in IR catchments and CaCl2-extracted samples. Exchangeable Na+ in sediments was significantly higher in MSR catchments, decreasing Ca2+ in the liquid phase by an ion-exchange reaction, which is likely also key in maintaining high SRP levels. We conclude that MSR catchments in coastal Akita are a significant P source for streams even in headwater forests, and that site-specific NaCl water types and higher exchangeable Na+ concentrations in sediments result in higher SRP concentrations in stream waters. These results have critical implications for P cycles in freshwater ecosystems influenced by Na+.

Reassessment of Varronia bellonis - a threatened, endemic plant from Puerto Rico.

BackgroundVarroniabellonis (Urb.) Britton is a lianescent or recumbent shrub that is endemic to Puerto Rico where it is restricted to specific geology types with a limited extent on the western half of the Island. The species occurs on serpentinite geology covered by serpentine-derived soils in the west-central mountains and on limestone geology in the the northern karst region. The species area of occupancy is estimated to range between 108 km2 and 268 km2 and its extent of occurrence to be between 644 km2 and 852 km2. The number of locations are estimated to be four. There are 418 known mature individuals in the wild (Hamilton 2020a). The species was previously assessed as Critically Endangered (Linsky and Sustache 2014), based on available information. However, an international team have been collaborating to conserve the species and, based on new information derived from this work, the species is reassessed as Endangered (EN), based on Criteria B1ab(i,ii,iii,iv,v)+2ab(i,ii,iii,iv,v), according to the IUCN Red List Categories and Criteria (version 3.1) and guidelines (IUCN Standards and Petitions Committee 2019).New informationAreas of suitable habitat across the native range of the threatened plant, V.bellonis, were surveyed by a team of experts between 2016 and 2019 to determine the species habitat preferences, identify threats to the species survival and provide an up-to-date meta-population status. The new information enabled members of the international team to reassess the species status and will enable sound and scientifically-based recovery actions to be recommended that can secure Varroniabellonis populations for the future. Parallel efforts are ongoing to explore the species population genetics and reproductive biology.

한반도 남부의 지질 유형별 지형 기복과 삭박 저항력

This study tried to reveal relative surface denudation resistance and ranking by geologic types in the Southern Korean Peninsula using an 1:250,000 digital geologic map and ASTER GDEM. Among rock types such as igneous, sedimentary and metamorphic rocks, metamorphic rock showed the greatest resistance to surface denudation. The most resistant rock to surface denudation by geologic periods (e.g., the Precambrian, Paleozoic, Mesozoic and Cenozoic) was found from the Precambrian. Among the major tectonic settings in the Southern Korean Peninsula such as the Gyeonggi massif, Okcheon belt, Yeongnam massif, Gyeongsang basin and Pohang basin, the Okcheon belt indicated the greatest resistance. The most and least resistant rocks from the representative nine rocks in the Southern Korean Peninsula were Paleozoic limestone, and Cretaceous sedimentary rock and Cenozoic sedimentary rock, respectively. This study suggests that Paleozoic limestone, Cretaceous volcanic rock, Paleozoic sedimentary rock and Precambrian gneiss can be regarded as hard rocks with high elevation, steep slope and complicated relief, while soft rocks with low elevation, gentle slope and simple relief are Jurassic granite, Cretaceous sedimentary rock and Cenozoic sedimentary rock.

Carbon mineralization using plagioclase feldspar-rich mine tailings: characterization and cation extraction

The possibility to capture and store CO2 in mine tailings has gained significant traction as a viable climate mitigation technique. The mineralogy and chemistry of mine tailings can vary drastically depending on the type of mine and local geology. Tailings from Sibanye-Stillwater, a mine in Nye, Montana, USA that produces nickel, copper and platinum group metals (PGM), possess sufficient calcium and magnesium to store CO2. However, efficient CO2 storage is a difficult task due to the heterogeneous mineralogy of the tailings. This study involved using the Alternative AA Route to efficiently extract calcium and magnesium from the Sibanye-Stillwater tailings. At optimized conditions (45o oC, 30 min), about 39% of the Mg and 15% of the Ca in the tailings were extracted. While the Alternative AA Route proved successful in extracting phyllosilicate-bound magnesium, it was ineffective in extracting calcium from the tailings, which is mostly present in the form of plagioclase feldspar. Further studies aimed at targeting calcium extraction while maintaining or increasing magnesium extraction will be necessary to realize the full potential of CO2 storage in the Sibanye-Stillwater tailings.