87 research outputs found
An empirical method to compensate the NMR calibrated porosity of the tight volcanic rocks based on comprehensive laboratory studies
The nuclear magnetic resonance (NMR) response is known to deviate from the true value for the volcanic reservoirs, particularly when the pore throat size is ultralow. Consequently, the related petrophysical parameters such as porosity, permeability, and pore size distribution from NMR measurements are greatly influenced. An empirical method to correct the NMR calibrated porosity for the tight volcanic rocks is proposed after comprehensive investigations of influential factors combined with mineralogical and petrophysical analyses. The laboratory result indicates that the relative porosity deviation is negatively correlated with the geometric mean of the transversal relaxation time (T2) but positively correlated with the clay content. Moreover, both the paramagnetic materials, such as the manganese (Mn) content, and the diamagnetic materials, such as the magnesium (Mg) content, contribute to the NMR relaxation intensity reduction but with different mechanisms. The NMR calibrated porosity can be compensated through multiple regressions with these controlling factors, which can be generalized to other tight volcanic reservoirs
Toward the development of smart capabilities for understanding seafloor stretching morphology and biogeographic patterns via DenseNet from high-resolution multibeam bathymetric surveys for underwater vehicles
The increasing use of underwater vehicles facilitates deep-sea exploration at a wide range of depths and spatial scales. In this paper, we make an initial attempt to develop online computing strategies to identify seafloor categories and predict biogeographic patterns with a deep learning-based architecture, DenseNet, integrated with joint morphological cues, with the expectation of potentially developing its embedded smart capacities. We utilized high-resolution multibeam bathymetric measurements derived from MBES and denoted a collection of joint morphological cues to help with semantic mapping and localization. We systematically strengthened dominant feature propagation and promoted feature reuse via DenseNet by applying the channel attention module and spatial pyramid pooling. From our experiment results, the seafloor classification accuracy reached up to 89.87%, 82.01%, and 73.52% on average in terms of PA, MPA, and MIoU metrics, achieving comparable performances with the state-of-the-art deep learning frameworks. We made a preliminary study on potential biogeographic distribution statistics, which allowed us to delicately distinguish the functionality of probable submarine benthic habitats. This study demonstrates the premise of using underwater vehicles through unbiased means or pre-programmed path planning to quantify and estimate seafloor categories and the exhibited fine-scale biogeographic patterns
CFD Modelling and Simulation of Water Turbines
The design and development of water turbines requires accurate methods for performance prediction. Numerical methods and modelling are becoming increasingly important tools to achieve better designs and more efficient turbines, reducing the time required in physical model testing. This book is focused on applying numerical simulations and models for water turbines to predict tool their performance. In this Special Issue, the different contributions of this book are classified into three state-of-the-art Topics: discussing the modelling of pump-turbines, the simulation of horizontal and vertical axis turbines for hydrokinetic applications and the modelling of hydropower plants. All the contributions to this book demonstrate the importance of the modelling and simulation of water turbines for hydropower energy. This new generation of models and simulations will play a major role in the global energy transition and energy crisis, and, of course, in the mitigation of climate change
Advances in Methane Production from Coal, Shale and Other Tight Rocks
This collection reports on the state of the art in fundamental discipline application in hydrocarbon production and associated challenges in geoengineering activities. Zheng et al. (2022) report an NMR-based method for multiphase methane characterization in coals. Wang et al. (2022) studied the genesis of bedding fractures in Ordovician to Silurian marine shale in the Sichuan basin. Kang et al. (2022) proposed research focusing on the prediction of shale gas production from horizontal wells. Liang et al. (2022) studied the pore structure of marine shale by adsorption method in terms of molecular interaction. Zhang et al. (2022) focus on the coal measures sandstones in the Xishanyao Formation, southern Junggar Basin, and the sandstone diagenetic characteristics are fully revealed. Yao et al. (2022) report the source-to-sink system in the Ledong submarine channel and the Dongfang submarine fan in the Yinggehai Basin, South China Sea. There are four papers focusing on the technologies associated with hydrocarbon productions. Wang et al. (2022) reported the analysis of pre-stack inversion in a carbonate karst reservoir. Chen et al. (2022) conducted an inversion study on the parameters of cascade coexisting gas-bearing reservoirs in coal measures in Huainan. To ensure the safety CCS, Zhang et al (2022) report their analysis of available conditions for InSAR surface deformation monitoring. Additionally, to ensure production safety in coal mines, Zhang et al. (2022) report the properties and application of gel materials for coal gangue control
The importance of seasonality at different levels of ecological organization in the marine ecosystem of the Northwestern Mediterranean Sea
[eng] From an oceanographic perspective, seasonality has been widely studied, and abundant research exists about low trophic level organisms such as phytoplankton and zooplankton. Nevertheless, at a regional scale, this information is not always homogenous and certain areas lack longer time series to track seasonal cycles. This knowledge gap is emphasized as one moves to higher trophic level organisms, whose studies tend to focus on single seasons or inter-annual variation rather than on seasonal changes and intra-annual dynamics. This Ph.D. thesis aims to broaden the knowledge about the marine ecosystem of the Northwestern Mediterranean Sea incorporating the importance of seasonality in key ecological processes, such as body condition, fitness, spatial distribution, and trophic ecology of marine species, and, finally, the structure and functioning of marine food webs. Seasonality is approached at different levels of the marine community, including the demersal component focusing on commercially important species of fish (Merluccius merluccius, Lophius budegassa, Lophius piscatorius, Mullus barbatus), crustaceans (Liocarcinus depurator, Squilla mantis) and cephalopods (Illex coindetii, Eledone cirrhosa), the pelagic component targeting the most abundant and commercially important small pelagic fish species (Sardina pilchardus and Engraulis encrasicolus), and at the ecosystem level using system indicators. To attain these objectives, various methodological approaches have been combined, such as species distribution models, stable isotopes analysis, bayesian isotope mixing isotope models, analysis of biometrical/biophysical parameters (Kn, GSI, fat content), generalized additive models and ecosystem modelling. Results show seasonal variations in species distribution with species-specific patterns in the case of demersal species. Bathymetry, temperature and fishing effort are important drivers explaining biomass spatial distribution of these species. European hake is further studied in one of the chapters, and the predicted posterior mean weight distribution also presents spatial differences between winter and summer. Ontogenetic and seasonal variations are also detected in the diet of this species. Spatial and seasonal variations in fitness are found at the local scale for European sardines and anchovies. These changes are mostly explained by environmental variables while spatial and seasonal factors are also important. Moreover, trophic variables also contributed to the species dynamics, suggesting that variations in prey abundance, composition and quality can impact their fitness. At the ecosystem level, we investigate changes in indicators of ecosystem structure and functioning when using seasonal input data vs annual averages in marine ecosystem models for the characterization of our study area. We find several indicators showing significant variations in ecosystem structure and energy transfer. Overall, the findings of this Ph.D. show seasonal variation at different levels of biological organization and in various ecological processes, which highlights the relevance of seasonality in the marine realm, specifically in the Northwestern Mediterranean Sea. Therefore, we can conclude that considering seasonality in ecological studies can provide complementary insights into our understanding of species biological and ecological dynamics, which cascades up to the knowledge about ecosystem structure and functioning.[spa] Desde una perspectiva oceanográfica y climatológica, la estacionalidad se ha estudiado ampliamente y existen múltiples investigaciones desarrolladas con organismos situados en niveles tróficos bajos, como el fitoplancton y el zooplancton. Sin embargo, a escala regional, esta información no siempre es homogénea y algunas zonas carecen de series temporales largas. Esta laguna de conocimiento se acentúa a medida que se avanza hacia organismos de nivel trófico superior. Esta tesis pretende mejorar el conocimiento sobre el ecosistema marino del mar Mediterráneo noroccidental investigando el efecto de la estacionalidad en algunos procesos ecológicos clave, como la condición corporal, la distribución espacial y la ecologÃa trófica de las especies, asà como en la estructura y el funcionamiento de las redes tróficas marinas. La estacionalidad se aborda a distintos niveles de la comunidad marina, incluyendo el componente demersal (especies de peces, crustáceos y cefalópodos), pelágico (la sardina y el boquerón) y a nivel de ecosistema. Para alcanzar estos objetivos, se han combinado diversos enfoques metodológicos (e.g. modelos de distribución de especies, análisis de isótopos estables, análisis de parámetros biométricos/biofÃsico y modelización de ecosistemas). Para las especies demersales, los resultados muestran variaciones estacionales en su distribución espacial, y la batimetrÃa, la temperatura y el esfuerzo pesquero aparecen como importantes impulsores. La merluza europea se estudia con más detalle en uno de los capÃtulos y se detectan variaciones ontogenéticas y estacionales en la dieta de esta especie. En el caso de la sardina y el boquerón, se observan variaciones espaciales y estacionales en la condición a escala local. Estos cambios se explican principalmente por variables ambientales y los factores espaciales y estacionales, pero las variables tróficas también contribuyen. A nivel de ecosistema, investigamos los cambios en los indicadores de estructura y funcionamiento de los ecosistemas al utilizar datos de entrada estacionales, frente a medias anuales. Encontramos varios indicadores que muestran variaciones significativas en la estructura del ecosistema y la transferencia de energÃa. En general, los resultados de esta tesis muestran una variación estacional en diferentes niveles de organización biológica y en varios procesos ecológicos, lo que pone de manifiesto la relevancia de la estacionalidad en el mar Mediterráneo noroccidental. Se concluye que considerar la estacionalidad en los estudios ecológicos puede aportar conocimientos complementarios a la comprensión de la dinámica biológica y ecológica de las especies, y a la estructura y el funcionamiento de los ecosistemas marinos
Models, Simulations, and the Reduction of Complexity
Modern science is a model-building activity. But how are models contructed? How are they related to theories and data? How do they explain complex scientific phenomena, and which role do computer simulations play? To address these questions which are highly relevant to scientists as well as to philosophers of science, 8 leading natural, engineering and social scientists reflect upon their modeling work, and 8 philosophers provide a commentary
Combination of Machine Learning Algorithms with Concentration-Area Fractal Method for Soil Geochemical Anomaly Detection in Sediment-Hosted Irankuh Pb-Zn Deposit, Central Iran
Prediction of geochemical concentration values is essential in mineral exploration as it plays a principal role in the economic section. In this paper, four regression machine learning (ML) algorithms, such as K neighbor regressor (KNN), support vector regressor (SVR), gradient boosting regressor (GBR), and random forest regressor (RFR), have been trained to build our proposed hybrid ML (HML) model. Three metric measurements, including the correlation coefficient, mean absolute error (MAE), and means squared error (MSE), have been selected for model prediction performance. The final prediction of Pb and Zn grades is achieved using the HML model as they outperformed other algorithms by inheriting the advantages of individual regression models. Although the introduced regression algorithms can solve problems as single, non-complex, and robust regression models, the hybrid techniques can be used for the ore grade estimation with better performance. The required data are gathered from in situ soil. The objective of the recent study is to use the ML model’s prediction to classify Pb and Zn anomalies by concentration-area fractal modeling in the study area. Based on this fractal model results, there are five geochemical populations for both cases. These elements’ main anomalous regions were correlated with mining activities and core drilling data. The results indicate that our method is promising for predicting the ore elemental distribution
Ocean remote sensing techniques and applications: a review (Part II)
As discussed in the first part of this review paper, Remote Sensing (RS) systems are great tools to study various oceanographic parameters. Part I of this study described different passive and active RS systems and six applications of RS in ocean studies, including Ocean Surface Wind (OSW), Ocean Surface Current (OSC), Ocean Wave Height (OWH), Sea Level (SL), Ocean Tide (OT), and Ship Detection (SD). In Part II, the remaining nine important applications of RS systems for ocean environments, including Iceberg, Sea Ice (SI), Sea Surface temperature (SST), Ocean Surface Salinity (OSS), Ocean Color (OC), Ocean Chlorophyll (OCh), Ocean Oil Spill (OOS), Underwater Ocean, and Fishery are comprehensively reviewed and discussed. For each application, the applicable RS systems, their advantages and disadvantages, various RS and Machine Learning (ML) techniques, and several case studies are discussed.Peer ReviewedPostprint (published version
Fluid Mechanics of Plankton
The cooperation between plankton biologists and fluid dynamists has enhanced our knowledge of life within the plankton communities in ponds, lakes, and seas. This book assembled contributions on plankton–flow interactions, with an emphasis on syntheses and/or predictions. However, a wide range of novel insights, reasonable scenarios, and founded critiques are also considered in this book
Advanced Geoscience Remote Sensing
Nowadays, advanced remote sensing technology plays tremendous roles to build a quantitative and comprehensive understanding of how the Earth system operates. The advanced remote sensing technology is also used widely to monitor and survey the natural disasters and man-made pollution. Besides, telecommunication is considered as precise advanced remote sensing technology tool. Indeed precise usages of remote sensing and telecommunication without a comprehensive understanding of mathematics and physics. This book has three parts (i) microwave remote sensing applications, (ii) nuclear, geophysics and telecommunication; and (iii) environment remote sensing investigations
- …