Subjects -> EARTH SCIENCES (Total: 771 journals)     - EARTH SCIENCES (527 journals)    - GEOLOGY (94 journals)    - GEOPHYSICS (33 journals)    - HYDROLOGY (29 journals)    - OCEANOGRAPHY (88 journals) EARTH SCIENCES (527 journals)            First | 1 2 3
 Showing 201 - 371 of 371 Journals sorted alphabetically Hydrological Processes       (Followers: 44) Hydrology and Earth System Sciences       (Followers: 38) ICES Journal of Marine Science: Journal du Conseil       (Followers: 53) IEEE Geoscience and Remote Sensing Letters       (Followers: 151) IEEE Geoscience and Remote Sensing Magazine       (Followers: 6) IEEE Journal of Oceanic Engineering       (Followers: 11) Indian Geotechnical Journal       (Followers: 4) Indonesian Journal on Geoscience       (Followers: 1) Inland Waters Innovative Infrastructure Solutions Interdisciplinary Environmental Review       (Followers: 3) International Geology Review       (Followers: 17) International Journal of Advanced Geosciences       (Followers: 2) International Journal of Advanced Remote Sensing and GIS       (Followers: 50) International Journal of Applied Earth Observation and Geoinformation       (Followers: 36) International Journal of Coal Geology       (Followers: 2) International 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Water       (Followers: 4) International Journal of Speleology       (Followers: 3) Iraqi National Journal of Earth Sciences iScience       (Followers: 1) Island Arc       (Followers: 5) ISPRS International Journal of Geo-Information       (Followers: 5) Italian Journal of Geosciences Izvestiya, Atmospheric and Oceanic Physics       (Followers: 1) Izvestiya, Physics of the Solid Earth       (Followers: 2) Jahresberichte und Mitteilungen des Oberrheinischen Geologischen Vereins       (Followers: 2) JETP Letters       (Followers: 3) Journal of Earth Science & Climatic Change       (Followers: 14) Journal of Advances in Modeling Earth Systems       (Followers: 5) Journal of African Earth Sciences       (Followers: 11) Journal of Analytical and Numerical Methods in Mining Engineering Journal of Applied Geophysics       (Followers: 15) Journal of Applied Volcanology       (Followers: 7) Journal of Arid Land Journal of Asian Earth Sciences       (Followers: 15) Journal of Asian Earth 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52) Journal on Geoinformatics, Nepal       (Followers: 2) Jurnal Ilmiah Perikanan dan Kelautan / Scientific Journal of Fisheries and Marine Kartografija i geoinformacije (Cartography and Geoinformation) Lake and Reservoir Management       (Followers: 7) Landslides       (Followers: 26) Latin American Journal of Sedimentology and Basin Analysis       (Followers: 1) Lethaia       (Followers: 5) Letters in Mathematical Physics       (Followers: 4) Limnologica       (Followers: 4) Limnology       (Followers: 9) Lithology and Mineral Resources       (Followers: 3) Lithos       (Followers: 9) Malaysian Journal of Geosciences Marine and Freshwater Research       (Followers: 6) Marine and Petroleum Geology       (Followers: 21) Marine Biology Research: New for 2005       (Followers: 2) Marine Economics and Management       (Followers: 3) Marine Environmental Research       (Followers: 31) Marine Geodesy       (Followers: 4) Marine Geology       (Followers: 31) Marine Geophysical Researches     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Similar Journals
 Natural Resources ResearchJournal Prestige (SJR): 0.8 Citation Impact (citeScore): 3Number of Followers: 8      Hybrid journal (It can contain Open Access articles) ISSN (Print) 1573-8981 - ISSN (Online) 1520-7439 Published by Springer-Verlag  [2469 journals]
• Evolution of the Surface Area of Critical Lagoon Systems in the Salar de
Atacama

Abstract: Abstract The Salar de Atacama in northern Chile hosts the biggest lithium reserves globally. However, concerns have arisen regarding the environmental impact of lithium extraction on its basin; in particular, the possible drought of its lagoons that sustain unique natural ecosystems. This investigation implemented an image processing and statistical methodology to assess the area evolution and dynamic behavior of these main water bodies between 1986 and 2018. Results showed that these lagoon systems have not presented significant changes despite increasing lithium production, even for the years of large brine extraction. The analysis indicated that the total surface area of the lagoons varied within a restricted range at 95% confidence level: on average, of the total area covered by these systems 0.03% could have been lost or 0.01% could have been gained per year. Moreover, a multivariate analysis indicated that brine extraction did not have a negative impact on the evolution of the surface areas of the lagoons during the last three decades.
PubDate: 2022-05-15

• Multiple-Point Geostatistics-Based Three-Dimensional Automatic Geological
Modeling and Uncertainty Analysis for Borehole Data

Abstract: Abstract The three-dimensional characterization of geological structures is important for determining the distribution of subsurface mineral resources. However, geological structures and geological phenomena have great stochasticity and uncertainty at the microscopic level. Traditional multiple-point geostatistics use mostly three-dimensional conceptual models or two-dimensional sections as training images, while simulations using direct low-dimensional borehole data are lacking. In this paper, we propose a new multiple-point geostatistical method to automatically reconstruct three-dimensional geological models directly from borehole data, which can significantly reduce the complexity of intermediate manual operations. First, the geological structure characteristics in the borehole data are extracted, and then an initial prior model is constructed based on geological constraints. Next, for the non-stationary problem, the mobile local scan approach is proposed to make the simulation nodes scan in a certain range of scaled area to simultaneously achieve the zonal simulation effect and eliminate the discontinuity problem between zonal boundaries. Based on this solution, the whole modeling workflow is designed. Finally, the algorithm is validated using actual plains area geological survey data, compared to other modeling methods, and evaluated for model uncertainty. The results show that the proposed 3D geological modeling method can effectively expose the stratigraphic structural morphology, stratigraphic attributes and overburden relationships. It will provide decision support for resource exploration and reduce exploration costs.
PubDate: 2022-05-14

• A “Weighted” Geochemical Variable Classification Method Based
on Latent Variables

Abstract: Abstract Clustering of variables relies on relationships among them. The strength of those relationships is generally measured by the correlation coefficients between pairs of variables. This paper proposes specified variable weighted correlation coefficients and takes the clustering around latent variables (CLV) approach as an example to transform the common clustering method into a “weighted” clustering method. The aim is to eliminate factors that are unrelated to the variable that was adopted for weighting to ensure that the cluster centers are sufficiently different and have good correlations with the adopted variable. A log-transformed dataset was used to evaluate the proposed method. Three clusters were obtained under the restriction of the As element, and they represented three ore-controlling factors related to the Goldenville Formation, namely geologic features such as formation, fault contacts, and granitoid intrusions. Not only did the new cluster centers account for most of the variability related to the weighted element (As) but they also showed significant differences in spatial distributions.
PubDate: 2022-05-12

• Pre-drill Assessments and Drilling Outcomes in Mexico in 2018–2022 and
Historical Experience from Norway and the Netherlands: Lessons Learned and
Recommendations for Future Petroleum Exploration

Abstract: Abstract This study compares key pre-drill exploration assessments and drilling outcomes for conventional petroleum prospects/wells evaluated and drilled in Mexico in 2018–2022. All data come from open sources, which facilitates an independent and unbiased performance analysis of the exploration industry (21 operating companies). The study includes 375 exploration prospects/wells and 80 drilled wells with at least some known exploration outcomes. The geological success rate (58%) is much higher than the average pre-drill probability of geological success (PoS, 35%). Explorers, in general and on average, significantly overestimated geological risks before drilling and made many more discoveries than expected. The 71 drilled wells with known volumetric outcomes delivered the total recoverable resources [2966 million barrels of oil equivalent, mmboe (1 million barrels of oil equivalent = 158,987 m3 of oil.)] close to the total average risked expectation (3325 mmboe), which is a good outcome. However, assessments of success case volumes for individual prospects were rather poor. The majority of discoveries contain recoverable resources that differ by a factor of two or more (from 12 times less to 190 times more) from the pre-drill assessed volumes. The national Mexican company Pemex, on average, significantly underestimated the success-case volumes, while the international oil companies, on average, significantly overestimated them. Based on this study of recent petroleum exploration in Mexico and previous similar studies in Norway and in the Netherlands, we conclude that the pre-drill assessments of geological PoS values and success-case resource volumes have not improved over the last 30 years. We recommend that exploration companies should focus on improving forecasting abilities of the explorers.
PubDate: 2022-05-11

• A Mechanical Model and Numerical Method for Gas Seepage Analysis
Considering Gas Desorption in Heterogeneous Coal

Abstract: Abstract The primary purpose of this paper is to research the law of gas seepage considering gas desorption in heterogeneous coal theoretically. A mechanical model on gas seepage considering gas desorption in heterogeneous coal is established, and the governing equation of gas seepage is discretized by the finite volume method with a new meshing strategy. Moreover, the gas state distribution and change in coal with different heterogeneity are calculated. The numerical results show that the effects of coal heterogeneity on gas seepage and desorption are significant. The coal with high heterogeneity is not accessible for gas to seep in it, resulting in a great gas pressure gradient, which is necessary for an outburst initiation. Additionally, the gas pressure gradient in the coal with high heterogeneity decreases more slowly than that with low heterogeneity. Hence, the possibility of outburst initiation is greater, and the outburst duration may be longer if the coal has high heterogeneity. Due to the strong randomness of the distribution and change of gas velocity in heterogeneous coal, the coal and gas outbursts in the field may be far more complex than that induced in the laboratory by using briquette, which is close to a homogeneous porous medium.
PubDate: 2022-05-11

• Testing the Mineral Resources-Induced Environmental Kuznets Curve
Hypothesis in Africa

Abstract: Abstract Mineral resources are indispensable in manufacturing clean energy equipment, and this technology is going through a flourishing era at the stake of climate change. However, the extraction of these mineral resources poses several environmental concerns. This article aims to evaluate the effects of mineral resources, energy intensity, urbanization, and economic development on carbon dioxide (CO2) emissions and test the environmental Kuznets curve (EKC) hypothesis. For this purpose, this study sampled 33 African mineral resources endowed countries with available data from 1990 to 2015. The empirical analysis focused on the main panel and its subpanels—low income (LI), lower middle income (LMI), upper middle income (UMI) panels—to capture the income inequality effects. We employed the heterogeneous fully modified ordinary least squares and dynamic ordinary least squares models to generate robust and reliable long-run parameters. The estimation results suggest that mineral resources endowment worsens carbon diffusion in the panel countries, such as LI, LMI, and overall. Similarly, energy intensity increases CO2 emissions for LMI, UMI and overall panels. As for urbanization, it has a bicephalous inference that harms the environment at the panel level of LI countries while it decarbonizes at the level of LMI, UMI, and overall panels. The LI, UMI, and overall panels support a U-shaped curve rather than an EKC. Moreover, CO2 emissions have a feedback Granger causality relationship with all its determinants. The findings have useful policy insights for green policy.
PubDate: 2022-05-09

• Petrophysical Characterization of the Turonian and Cenomanian Intervals in
the Abu Gharadig Field, Western Desert, Egypt: Inferences on Reservoir
Quality and Resource Development

Abstract: Abstract Characterization of reservoir petrophysical properties provides critical insights into reservoir deliverability and field development strategy. The main objective of this work is to present a comprehensive core-based petrophysical assessment of the Cenomanian Bahariya Formation and the Turonian Abu Roash (AR-D and AR-E, respectively) Members of the Abu Gharadig field situated in the Western Desert, Egypt. The AR-D is water-wet and consists of micro- to mesoporous shallow marine limestone lithofacies with moderate porosity (Φ), poor horizontal permeability (Kh) with poor permeability anisotropy due to the presence of vertical fractures, while the nano- to mesoporous argillaceous limestone lithofacies is very tight. Both the lithofacies exhibit primary and secondary depositional fabrics. Overall, the AR-D member exhibits impervious to poor reservoir quality, and so a suitable stimulation strategy will be essential to produce from this interval. The AR-E interval implies a tidal depositional environment. The calcareous sandstone lithofacies of the AR-E is macro- to megaporous and exhibits moderate to high porosity (> 15%) and excellent permeability (up to 305 mD). The meso- to microporous glauconitic siltstones of the AR-E have poor porosity and permeability. Both lithofacies are characterized by high water saturation, preserve primary depositional fabrics and consist of isotropic pore system along with some connected horizontal pores yielding higher permeability anisotropy. The Bahariya Formation consists of fine to medium grained massive sandstone lithofacies with minor siltstone intercalations, indicating a channel deposit in a coastal or fluvio–deltaic environment. It exhibits high porosity (~ 20%) and permeability (up to 649 mD) but shows very high water saturation. It preserves the primary depositional fabrics with isotropic pore system. The thin siltstone intercalations may act as vertical barriers. Based on the petrophysical assessment, we made recommendations on the reservoir development aspects.
PubDate: 2022-05-02

• Combined Geophysical–Geological Investigation for 3D Geological
Modeling: Case of the Jeffara Reservoir Systems, Medenine Basin, SE
Tunisia

Abstract: Abstract This work presents a comprehensive study based on geophysical and geological data to improve the characterization of regional multilayered reservoir systems in a complex geological setting. A combined approach, involving (a) data integration, (b) joint seismic-geological investigations, (c) mapping of reservoir surfaces and (d) 3D geological modeling, is proposed to characterize the “Jeffara of Medenine Basin” reservoir systems and to enhance the understanding of their functioning. The 3D geological modeling was performed using a 3D interpolation procedure based on potential field theory and integrating both observed data and knowledge-driven understanding. It was implemented using co-kriging techniques, involving two main variables: the “geological contact” and the “orientation data.” The interpolation was constrained by geological knowledge and hypotheses inferred through the stratigraphic pattern of the reservoir formations to be modeled and the faults affecting their continuity. A reliable 3D geological modeling was constructed, describing nine regional reservoir formations and associated structural features (folds and crosscutting faults). A comprehensive analysis of the outputs of the 3D geological model combined with a careful correlation of the potentiometric gradient/lithologic properties insured a better description of the reservoirs compartmentalization and connectivity and helped to construct the conceptual model of the fluid flow path at regional and local scales. All modeling results provide a direct foundation for subsequent numerical flow simulation and hydrodynamic modeling.
PubDate: 2022-04-30

• Prediction of Uniaxial Compressive Strength of Rock Via Genetic
Algorithm—Selective Ensemble Learning

Abstract: Abstract Reasonable and effective determination of uniaxial compressive strength (UCS) is critical for rock mass engineering stability research, design, and construction. To estimate the UCS of rock simply, conveniently, and accurately, a selective ensemble learning technology is introduced here based on modern artificial intelligence research, and a prediction method of the UCS of rock via genetic algorithm—selective ensemble learning (GA–SEL) is proposed. Based on a UCS data set, a batch of different base learners was firstly trained independently with the data sample and the algorithm parameter perturbation method. Then, the optimal base learner subset was searched using GA. Further, the GA–SEL model was constructed by fusing the base learners in that subset. According to the 161 data set collected, the prediction performance of the GA–SEL model was evaluated by four evaluation indices, then two empirical regression models and seven common machine learning models were compared with it. The results of the GA–SEL model agreed with the measured data very well, showing that the model had the best prediction and generalization ability, it was more stable and accurate than the empirical methods and common machine learning models. Because it only needs seven high-quality base learners, the GA–SEL model also has better operation efficiency compared to other ensemble learning models. Therefore, this method could be used as an effective method to predict the UCS of rock and serve for rock engineering problems.
PubDate: 2022-04-28

• “Double Peak” of Dynamic Strengths and Acoustic Emission Responses of

PubDate: 2022-04-28

• Constraints on the Geometry and Gold Distribution in the Black Reef
Formation of South Africa Using 3D Reflection Seismic Data and Micro-X-ray
Computed Tomography

Abstract: Abstract Geological and geophysical models are essential for developing reliable mine designs and mineral processing flowsheets. For mineral resource assessment, mine planning, and mineral processing, a deeper understanding of the orebody's features, geology, mineralogy, and variability is required. We investigated the gold-bearing Black Reef Formation in the West Rand and Carletonville goldfields of South Africa using approaches that are components of a transitional framework toward fully digitized mining: (1) high-resolution 3D reflection seismic data to model the orebody; (2) petrography to characterize Au and associated ore constituents (e.g., pyrite); and (3) 3D micro-X-ray computed tomography (µCT) and machine learning to determine mineral association and composition. Reflection seismic reveals that the Black Reef Formation is a planar horizon that dips < 10° and has a well-preserved and uneven paleotopography. Several large-scale faults and dikes (most dipping between 65° and 90°) crosscut the Black Reef Formation. Petrography reveals that gold is commonly associated with pyrite, implying that µCT can be used to assess gold grades using pyrite as a proxy. Moreover, we demonstrate that machine learning can be used to discriminate between pyrite and gold based on physical characteristics. The approaches in this study are intended to supplement rather than replace traditional methodologies. In this study, we demonstrated that they permit novel integration of micro-scale observations into macro-scale modeling, thus permitting better orebody assessment for exploration, resource estimation, mining, and metallurgical purposes. We envision that such integrated approaches will become a key component of future geometallurgical frameworks.
PubDate: 2022-04-28

• Fractal Analysis of Pore Structure Differences Between Shale and Sandstone
Based on the Nitrogen Adsorption Method

Abstract: Abstract Pore structure, a critical factor influencing the physical properties of oil and gas reservoirs, shows great variation with the reservoir rock type. Efficient exploration and development of oil and gas resources require comprehensive understanding of pore structure differences between various reservoirs. In this study, to clarify these differences, pore size distributions and pore structure parameters were obtained through low-pressure nitrogen (N2) adsorption–desorption experiments using shale, low-permeability sandstone, and tight sandstone as rock types. Pore space fractal dimension obtained from a proposed calculating method and pore surface fractal dimension obtained from the Frenkel–Halsey–Hill model were combined with N2 adsorption results to analyze quantitatively the pore structures of shale and sandstone. The results show that shale consisted mainly of inkbottle-shaped pores whereas sandstone was composed of slit-shaped pores. Compared with sandstone, shale had a larger specific surface area but smaller average pore diameter and pore volume. In addition, the pore structure heterogeneity and pore surface irregularity of shale were more significant, considering its larger fractal dimensions. Relationships among fractal dimensions and porosity, permeability, and pore structure parameters explained that pore size and pore distribution were the main influencing factors of porosity and permeability. These results highlight the practicability of fractal theory in characterizing pore structure and petrophysical properties of unconventional reservoirs.
PubDate: 2022-04-27

• Geochemical Characteristics and Paleoenvironment of Organic-Rich Triassic
Shale in the Central Ordos Basin

Abstract: Abstract With six wells currently producing > 5 tons of oil per day, the organic-rich Chang-7 shale of the Triassic Yanchang Formation in the central Ordos Basin, China, has shown great potential to be a significant shale oil/gas play. To provide (a) theoretical and practical basis for further exploration and development activities in this play and (b) guidance for exploitation of other play of similar type, it is critical to understand what the main controlling factors are for the enrichment of organic matter in the Chang-7 shale and under what environmental and climatic conditions was the organic-rich shale deposited and preserved. To tackle these questions, a series of comprehensive lithological, organic geochemical and elements analyses was carried out in this study. The Chang-73 shale has a thickness of 2–10 m and consists of primarily massive to laminated shales with occasional thin-bedded silty sandstone layers, which were deposited in a shallow to semi-deep lake environment. It has an average TOC of ~ 4%, the majority of which is Types II1 and II2 kerogen, indicating a mixed origin. The shale is currently in a moderate thermal evolutionary stage with average S1 of 3.55 mg/g, S2 of 8.54 mg/g and HI of 285.02 mg/g, representing a moderate- to high-quality source rock. Element data indicated that the shale was developed in a freshwater column that had dysoxic to anoxic conditions under a generally warm and humid climate setting. Organic matter in the shale had a mixed source including in situ production and terrestrial input from rivers, which were almost of the same importance in contributing to the enrichment of organic matter.
PubDate: 2022-04-26

• Simulated Block Variance for 3D Drillhole Infill

Abstract: Abstract Drillhole infill has an important role in the mining industry, especially when its aim is to enhance the assessment of variance representativeness of a mineralized rock or any other measured characteristics. Some infill optimization methods propose the use of kriging variance, which is feasible when the goal is to search for sub-sampled regions, but those methods may fail in more complex situations given that a fundamental limitation of kriging variance is to only depend on neighboring samples nearby the estimate location. This paper proposes a method to infer the best location for new drillholes through optimization using as objective function the sum of simulated block variance (SBV), which does not have the same limitation as to the kriging variance. The SBV is reached by stochastic simulation (sequential Gaussian simulation) to compute the variance of each block along with the grid model, and the values are summed to attain the objective function. The objective function minimization is computed by three different methods of search: random search, simulated annealing, and particle swarm optimization. Due to smaller objective function values when applied to a synthetic deposit, simulated annealing with fast cooling schedule algorithm performed better than the others. Further tests led to the conclusion that simulated annealing had more representation of the population. These methods were also applied to a real sampled site, the Capanema Mine, and the simulated annealing with fast cooling also produced the best results with regard to representativeness.
PubDate: 2022-04-25

• A Novel Spectral Index for Identifying Ferronickel (Fe–Ni) Laterites
from Sentinel 2 Satellite Data

Abstract: Abstract Field geological mapping is the initial step of preliminary research in mining. However, in the last decades, the rapid progress of remote sensing data processing and its use for reconnaissance of geological outcrops for the purpose of locating possible mining sites gained increasing attention due to the significant time and cost savings. In this study, a new methodology, focused on mapping ferronickel (Fe–Ni) laterite deposits by using Sentinel-2 satellite data, is introduced. It describes a novel spectral index (called laterite spectral index (LSI)) that enhances laterite surface outcrops. To the best of our knowledge, LSI is the first spectral index tailored for this task, concerning minerals that are simultaneously rich in Fe and Ni. The LSI was applied on a continuum removed image by taking advantage of the spectral features present in two specific spectral areas of 490–560 nm and 842–945 nm. The entire methodology was tested and validated on four different excavation sites in eastern Central Greece based on known drillholes. In all excavation sites, the proposed LSI compared favorably with other relative spectral indices proposed in the literature for the detection of Fe-bearing minerals or Fe-oxides.
PubDate: 2022-04-23

• Physical Properties, Pore-Throat Structure, Fractal Characteristics and
Their Effects on the Gas-Bearing Capacity of Tight Sandstone: A Case Study
from the Northern Tianhuan Depression, Ordos Basin, China

Abstract: Abstract In this study, various testing methods were used to analyze the mineral characteristics, reservoir storage types and pore-throat network characteristics of the Permian tight sandstone in the Upper Paleozoic of the Ordos Basin. A fractal method was applied to evaluate the reservoirs’ microscopic heterogeneity. According to the results, the storage space of the sandstone reservoir is predominantly intra-granular dissolution pores and kaolinite inter-crystalline pores, while primary pores and inter-granular dissolution pores form secondary spaces with low concentration and poor homogeneity of pore-throat size distribution. All samples were divided into four categories on account of porosity (ϕ), pore-throat size distribution and multifractal dimensions (D): Type A (ϕ > 10%) consisted mainly of macropores; Type B (ϕ < 6%, consisting mainly of transitional pores and micropores); Type C1 (6% < ϕ < 10%, consisting mainly of mesopores, D > 2.45); and Type C2 (6% < ϕ < 10%, consisting mainly of mesopores, D < 2.45). In general, the piecewise fractal dimension was associated with porosity, different pore size ranges and the pore-throat parameters. Between Types A and B samples, porosity and pore size distribution were the major controlling factors on gas-bearing capacity, while the microscopic pore-throat heterogeneity had little influence. However, the microscopic pore-throat heterogeneity had a significant effect on gas-bearing capacity in Types C1 and C2 samples. This study discusses the applicable pore size range for fractal analysis of tight sandstone based on fine reservoir division and provides a novel idea for the control of the microscopic pore-throat heterogeneity on gas-bearing capacity in tight sandstone.
PubDate: 2022-04-20

• A New Long-Term Photovoltaic Power Forecasting Model Based on Stacking
Generalization Methodology

Abstract: Abstract In recent times, solar energy has become a highly promising source of energy and one of the most regular types of sustainable energy. Forecasting the availability of solar energy has become a concern of many studies because of the intermittent characteristics of solar power. This study proposes a new stacked generalization methodology for predicting long-term photovoltaic power. In the proposed methodology, the base learners used consisted of group method of data handling (GMDH), least squares support vector machine (LSSVM), emotional neural network (ENN), and radial basis function neural network (RBFNN). The backpropagation neural network (BPNN) served as the meta-learner in the stacked approach. The proposed stacked generalization method showed superiority over the four standalone state-of-the-art methods (GMDH, LSSVM, ENN, and RBFNN) when tested with real data using performance indicators such as Bayesian information criteria (BIC), percent mean average relative error (PMARE), Legates and McCabe index (LM), mean absolute error, and root mean square error. The stacked model had the lowest BIC and PMARE values of 10,417.54 and 0.3617% for testing results. It also had the highest LM score of 0.996711 as compared with the benchmark standalone models, confirming its strength in forecasting photovoltaic power.
PubDate: 2022-04-18

• Three-Dimensional Mineral Prospectivity Mapping by XGBoost Modeling: A
Case Study of the Lannigou Gold Deposit, China

Abstract: Abstract Three-dimensional mineral prospectivity mapping (3DMPM) aims to explore deep mineral resources and many methods have been developed for this task in recent years. The eXtreme Gradient Boosting (XGBoost) algorithm, an improvement of the gradient boosting decision tree model, has been used widely in many fields due to its high computational efficiency and its ability to alleviate overfitting effectively. The Lannigou gold deposit in Guizhou is a well-known epithermal gold deposit in the "Golden Triangle" area of Guizhou, Guangxi and Yunnan, China, with potential for deep exploration. Geological data were used to establish a three-dimensional (3D) model, and subsequently a prospectivity model was built based on the metallogenic system and on geological anomaly theories. The 3D spatial reconstruction of mineralization anomalies was completed and 3D prediction layers of the ore-controlling factor were implemented to establish the basic data for the prediction model. The XGBoost classification model was proved efficient for 3DMPM, outperforming the weights of evidence method according to prediction success rate and accuracy.
PubDate: 2022-04-18

• Isotope Rollover of Gaseous Hydrocarbons Induced by Water Pressure in
Laboratory Pyrolysis Experiments: Insights into the Influence of Pressure
on Carbon Kinetic Isotope Effects During Methane Generation

Abstract: Abstract Stable carbon isotope (δ13C) rollover of natural gas has attracted recent attention due to its association with highly productive shale gas. However, the mechanistic causes of δ13C rollover are not fully understood. In this investigation, pyrolysis was carried out using calcareous shale and carbonaceous mudstone under high water pressure (WP) (i.e., 5 × 106–1.2 × 108 Pa). It was found that WP induced the isotope rollover of gaseous hydrocarbons. For both sapropelic and humic organic matter, the δ13C rollover of CH4 (methane), C2H6 (ethane), and C3H8 (propane) occurred when the WP ranged from 3.25 × 107 to 1.2 × 108 Pa. This result can be explained by high WP conditions retarding oil cracking, and enhancing hydrocarbon expulsion and oil generation. The promotion of oil generation resulted in increasing trends of vitrinite reflectance, and inhibition of gaseous hydrocarbons generation resulted in decrease in δ13C1 values with increase in WP. Good functions were found between water pressure and the calculated carbon kinetic isotope effect (KIE) for 12CH4 and 13CH4 produced from sapropelic and humic organic matter. Further calculations showed that the increments of activation volume ( $${\Delta V}_{{12}_{{\mathrm{CH}}_{4}}}^{\ddagger }$$ – $${\Delta V}_{{13}_{{\mathrm{CH}}_{4}}}^{\ddagger }$$ ) were linearly correlated with the kinetic isotope effect of methane ( $$\Delta \mathrm{KIE}$$ ) produced from sapropelic and humic organic matter, indicating that WP may affect the KIE of 12CH4 and 13CH4 by changing the $$\Delta {V}^{\ddagger }$$ of 12CH4 and 13CH4. Overall, these findings suggest that WP affects the carbon isotope fractionation of gaseous hydrocarbons due to the different thermodynamic properties of 12CH4 and 13CH4.
PubDate: 2022-04-15

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