Excellence in Research and Innovation for Humanity

International Science Index

Commenced in January 1999 Frequency: Monthly Edition: International Abstract Count: 42523

Geological and Environmental Engineering

639
74760
Physical and Mechanical Phenomena Associated with Rock Failure
Abstract:
Failure mechanism of rocks is one of the fundamental aspects to study rock engineering stability. Rock is a material that contains flaws, initial damage, micro-cracks, etc. failure of rock is a dynamic, gradual and cumulative process of nucleation, growth, propagation, coalescence of micro-cracks, which is a non-equilibrium, non-linear evolutionary process. In the present study, the effect of brittleness and loading rate on the physical and mechanical phenomena produced in rock during loading sequences is considered. For this purpose, Acoustic Emission (AE) technique is used to monitor fracturing process of three rock types (Onyx Marble, Sandstone and soft Limestone) with different brittleness and Sandstone samples under different loading rate. The results of experimental tests revealed that brittleness and loading rate have a significant effect on the mode and number of induced fracture in rocks. An increase in rock brittleness increases the frequency of induced cracks, and the number of tensile fracture decreases when loading rate increases.
638
74679
Statistical Analysis for Evaluation of Spatial and Temporal Variations in Ganga River Water Quality
Abstract:
In this study, statistical hypothesis tests are carried out to identify spatial and temporal patterns in Ganga river water quality. Data for eight water quality components (Temperature pH, DO, BOD, COD, Total Coliform, Fecal Coliform and Total Kjeldahl Nitrogen) measured at 34 stations along the river for each month of the year 2004 and 2009 was used for analysis. Data was obtained from survey and measurements carried out under Ganga River Basin Management Plan (GRBMP) project funded by Ministry of Environment and Forests (MoEF), India. In order to obtain meaningful water quality information that is understandable to legislative decision makers, Water Quality Index (WQI) was computed from measured values of water components. A custom R package was written to compute unweighted arithmetic water quality indices. The hypothesis for spatial, temporal and seasonal changes in computed WQI values were defined. These were tested using Moran’s I, Mann Kendall and Wilcoxon tests. The result from hypothesis tests revealed significant spatial correlation in values of WQI and WQI values were not found to vary significantly for the year 2004 and 2009.
637
74667
A Hybrid Image Fusion Model for Generating High Spatial-Temporal-Spectral Resolution Data Using Operational Land Imager-Moderate Resolution Imaging Spectroradiometer-Hyperion Satellite Imagery
Abstract:
Nowadays, a large number of Earth observation satellites have been launching, with various Spatial, Temporal and Spectral Resolution (STSR), which contribute significantly to Earth surface monitoring ability. It seems that there is a boom in Earth observation field, nevertheless, because of the limitations of satellite sensor’s technology and budget constraints, there exist compromises between STSR of satellite data. That is to say, even though so many satellites have been launched, none of them can obtain high STSR data simultaneously. These compromises limit the application of existing remotely sensed data significantly, especially for the remote sensing applications that requires fine spatial detail, long-term and frequent coverage, and hyper-spectral (HS) satellite imagery, such as precise global or regional change detection, time series analysis, urban dynamic monitoring, natural disaster monitoring, real-time air quality monitoring, etc. Image fusion provides a feasible means to overcome the limitations of the current Earth observation data, mainly including spatial and spectral fusion, and spatial and temporal fusion. However, these fusion technologies can only solve part of the resolution enhancement problems, which cannot generate synthetic images with high STSR simultaneously. This study proposed a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which adopts the Landsat-8 Operational Land Imager (OLI, including its panchromatic (PAN) and multi-spectral (MS) bands), Moderate Resolution Imaging Spectroradiometer (MODIS) and Hyperion images as data sources. HSTSFM blends the high spatial resolution from OLI-PAN image, i.e., 15 m, the high temporal resolution from MODIS images, i.e., daily observations, and the high spectral resolution from Hyperion image, i.e., 146 good-quality bands out of 242 bands to produce daily HS images with a spatial resolution of 15 m, which aims to satisfy the growing demand of high STSR satellite images. The proposed HSTSFM model contains three fusion steps: (1) PAN and MS image fusion with an Enhanced Synthetic Variable Ratio (ESVR) algorithm to get high spatial resolution OLI-MS image at the base date; (2) Spatial and temporal image fusion with One-Pair Image Dictionary Learning method to obtain high spatial resolution OLI-MS image at the prediction date; (3) Temporal and spectral image fusion with a Modified Color Resolution Improvement Software Package (MCRISP) algorithm to obtain the high spatial resolution Hyperion image at the prediction date, i.e., the final predicted high STSR image. The proposed method adopted the Beijing area, China as a test region, and used the actual OLI-PAN and Hyperion images at the prediction date to evaluate the precision of the fusion result from spatial detail information and spectral properties similarities aspects. The experimental results indicate that HSTSFM can capture the land cover changes accurately and has good spatial and spectral fidelity to the reference OLI-PAN and Hyperion images. The proposed HSTSFM can fuse spatial, temporal, and spectral information from different types of satellite sensors, which has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.
636
74553
Estimation of Reservoirs Fracture Network Properties Using an Artificial Intelligence Technique
Abstract:
The main objective of this study is to develop a subsurface fracture map of naturally fractured reservoirs by overcoming the limitations associated with different data sources in characterising fracture properties. Some of these limitations are overcome by employing a nested neuro-stochastic technique to establish inter-relationship between different data, as conventional well logs, borehole images (FMI), core description, seismic attributes, and etc. and then characterise fracture properties in terms of fracture density and fractal dimension for each data source. Fracture density is an important property of a system of fracture network as it is a measure of the cumulative area of all the fractures in a unit volume of a fracture network system and Fractal dimension is also used to characterize self-similar objects such as fractures. At the wellbore locations, fracture density and fractal dimension can only be estimated for limited sections where FMI data are available. Therefore, artificial intelligence technique is applied to approximate the quantities at locations along the wellbore, where the hard data is not available. It should be noted that Artificial intelligence techniques have proven their effectiveness in this domain of applications.
635
74339
Inversion of Gravity Data for Density Reconstruction
Abstract:
Inverse problem generally used for recovering hidden information from outside available data. Vertical component of gravity field we will be going to use for underneath density structure calculation. Ill-posing nature is main obstacle for any inverse problem. Linear regularization using Tikhonov formulation are used for appropriate choice of SVD and GSVD components. For real time data handle, signal to noise ratios should have to be less for reliable solution. In our study, 2D and 3D synthetic model with rectangular grid are used for gravity field calculation and its corresponding inversion for density reconstruction. Fine grid also we have considered to hold any irregular structure. Keeping in mind of algebraic ambiguity factor number of observation point should be more than that of number of data point. Picard plot is represented here for choosing appropriate or main controlling Eigenvalues for a regularized solution. Another important study is depth resolution plot (DRP). DRP are generally used for studying how the inversion is influenced by regularizing or discretizing. Our further study involves real time gravity data inversion of Vredeforte Dome South Africa. We apply our method to this data. The results include density structure is in good agreement with known formation in that region, which puts an additional support of our method.
634
74317
Evaluation of Array Database to Manage and Query Massive Sensor Data
Abstract:
Most environmental monitoring observations are recorded at a fixed number of stations with constant frequency. Arrays are a natural choice to represent these, with space and time as the two dimensions. Current implementations of SOS (Sensor Observation Services) however typically use a normalized relational database as data backend. If data size grows to billions of records, querying and updating the database becomes relatively slow, with indexes taking up a lot of resources. This study evaluates the use of SciDB, an array database as a backend for a big sensor dataset and compares it with a relational database, PostgreSQL. A common platform was set up to test the performance and compare the approaches of two systems. Result of the experiments conducted during this study shows that SciDB has significant advantage over PostgreSQL for queries like sequential scan, group by aggregation, join and computation of quantiles on the used dataset. Index on PostgreSQL table reduces the response time for filter and slicing queries but, index size grows substantially as data size is increased. On other hand SciDB’s compression technique greatly reduces the disk storage space.
633
74079
Runoff Simulation by Using WetSpa Model in Garmabrood Watershed of Mazandaran Province, Iran
Abstract:
Hydrological models are applied to simulation and prediction floods in watersheds. WetSpa is a distributed, continuous and physically model with daily or hourly time step that explains of precipitation, runoff and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave Equation which depend on the slope, velocity and flow route characteristics. Garmabrood watershed located in Mazandaran province in Iran and passing over coordinates 53° 10´ 55" to 53° 38´ 20" E and 36° 06´ 45" to 36° 25´ 30"N. The area of the catchment is about 1133 km2 and elevations in the catchment range from 213 to 3136 m at the outlet, with average slope of 25.77 %. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe Model Efficiency Coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 61% and 83.17 % respectively.
632
74038
Ultrasonic Techniques to Characterize and Monitor Water-in-Oil Emulsion
Abstract:
Oil-water emulsions are commonly encountered in various industrial operations and at different stages of crude oil production and processing. Emulsions are often difficult to track and treat and can cause a number of costly problems which need to be avoided. The characteristics of the emulsion phase can vary with crude composition and types of impurities present in oil. The objectives of this study are the development of ultrasonic techniques to track and characterize emulsion phase generated during production and cleaning of crude oil. The position of emulsion layer is monitored with the help of ultrasonic probes suitably placed in the vessel. The sensitivity of the technique and its potential has been demonstrated based on extensive testing with different oil samples. The technique is also being developed to monitor emulsion phase characteristics such as stability, composition, and droplet size distribution. The ultrasonic parameters recorded are changes in acoustic velocity, signal attenuation and its frequency spectrum. Emulsion has been prepared with light mineral oil sample and the effects of various factors including mixing speed, temperature, surfactant, and solid particles concentrations have been investigated. The applied frequency for ultrasonic waves has been varied from 1 to 5 MHz to carry out a sensitivity analysis. Emulsion droplet structure is observed with optical microscopy and stability is examined by tracking the changes in ultrasonic parameters with time. A model based on ultrasonic attenuation spectroscopy is being developed and tested to track changes in droplet size distribution with time.
631
73869
Analysis of Production Forecasting in Unconventional Gas Resources Development Using Machine Learning and Data-Driven Approach
Abstract:
Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that apply to different approach for production forecasting due to uncertainly and complexity of fluid flow. Therefore, it is important that accurate production forecasting in unconventional gas resources. In this paper, we present a production forecasting workflow involving machine learning and data-driven approach which is a straightforward process, production correlation of obtaining information from various data sets to perform production forecasting of unconventional gas resources. This study takes advantage of applying various machine learning method in order to investigate the impact of native and design parameters on production as well as optimizing the predictive model using artificial neural network method. We applied to a Eagle Ford Shale asset that includes 200 horizontal wells from 3 county-Webb, La Salle, Dimmit to make data sets for Input- output of the prediction model. The proposed workflow involves using decision of data sets to train and clustering using machine learning and importance weight analysis for input data of predictive model which, subsequently, is used to predict the well production and performance of both existing wells and new planed wells. The proposed method can be used as assistance of decision making process that employs various data from native and design parameters for forecasting of existing wells and new wells in unconventional resources. It is not only useful for evaluating the effects of various parameters on productivity, but also provide a reliable approach to predict well production towards different completion plan in anywhere filed.
630
73841
Use of Landsat OLI Images in the Mapping of Landslides: Case of the Taounate Province in Northern Morocco
Abstract:
Northern Morocco is characterized by relatively young mountains experiencing a very important dynamic compared to other areas of Morocco. The dynamics associated with the formation of the Rif chain (Alpine tectonics), is accompanied by instabilities essentially related to tectonic movements. The realization of important infrastructures (Roads, Highways,...) represents a triggering factor and favoring landslides. This paper is part of the establishment of landslides susceptibility map and concerns the mapping of unstable areas in the province of Taounate. The landslide was identified using the components of the false color (FCC) of images Landsat OLI: i) the first independent component (IC1), ii) The main component (PC), iii) Normalized difference index (NDI). This mapping for landslides class is validated by in-situ surveys.
629
73762
Accessibility Analysis of Urban Green Space in Zadar Settlement, Croatia
Abstract:
The accessibility of urban green spaces (UGS) is an integral element in the quality of life. Due to rapid urbanization, UGS studies have become a key element in urban planning. The potential benefits of space for its inhabitants are frequently analysed. A functional transport network system and the optimal spatial distribution of urban green surfaces are the prerequisites for maintaining the environmental equilibrium of the urban landscape. An accessibility analysis was conducted as part of the Urban Green Belts Project (UGB). The development of a GIS database for Zadar was the first step in generating the UGS accessibility indicator. Data were collected using the supervised classification method of multispectral LANDSAT images and manual vectorization of digital orthophoto images (DOF). An analysis of UGS accessibility according to the ANGst standard was conducted in the first phase of research. The accessibility indicator was generated on the basis of seven objective measurements, which included average UGS surface per capita and accessibility according to six functional levels of green surfaces. The generated indicator was compared with subjective measurements obtained by conducting a survey (718 respondents) within statistical units. The collected data reflected individual assessments and subjective evaluations of UGS accessibility. This study highlighted the importance of using objective and subjective measures in the process of understanding the accessibility of urban green surfaces. It may be concluded that when evaluating UGS accessibility, residents emphasize the immediate residential environment, ignoring higher UGS functional levels. It was also concluded that large areas of UGS within a city do not necessarily generate similar satisfaction with accessibility. The heterogeneity of output results may serve as guidelines for the further development of a functional UGS city network.
628
73744
Rescaled Range Analysis of Seismic Time-Series: Example of the Recent Seismic Crisis of Alhoceima
Abstract:
Persistency, long-term memory and randomness are intrinsic properties of time-series of earthquakes. The Rescaled Range Analysis (RS-Analysis) was introduced by Hurst in 1956 and modified by Mandelbrot and Wallis in 1964. This method represents a simple and elegant analysis which determines the range of variation of one natural property (the seismic energy released in this case) in a time interval. Despite the simplicity, there is complexity inherent in the property measured. The cumulative curve of the energy released in time is the well-known fractal geometry of a devil’s staircase. This geometry is used for determining the maximum and minimum value of the range, which is normalized by the standard deviation. The rescaled range obtained obeys a power-law with the time, and the exponent is the Hurst value. Depending on this value, time-series can be classified in long-term or short-term memory. Hence, an algorithm has been developed for compiling the RS-Analysis for time series of earthquakes by days. Completeness time distribution and locally stationarity of the time series are required. The interest of this analysis is their application for a complex seismic crisis where different earthquakes take place in clusters in a short period. Therefore, the Hurst exponent has been obtained for the seismic crisis of Alhoceima (Mediterranean Sea) of January-March, 2016, where at least five medium-sized earthquakes were triggered. According to the values obtained from the Hurst exponent for each cluster, a different mechanical origin can be detected, corroborated by the focal mechanisms calculated by the official institutions. Therefore, this type of analysis not only allows an approach to a greater understanding of a seismic series but also makes possible to discern different types of seismic origins.
627
73734
Analysing Trends in Rice Cropping Intensity and Seasonality across the Philippines Using 14 Years of Moderate Resolution Remote Sensing Imagery
Abstract:
Rice is grown on over 100 million hectares in almost every country of Asia. It is the most important staple crop for food security and has high economic and cultural importance in Asian societies. The combination of genetic diversity and management options, coupled with the large geographic extent means that there is a large variation in seasonality (when it is grown) and cropping intensity (how often it is grown per year on the same plot of land), even over relatively small distances. Seasonality and intensity can and do change over time depending on climatic, environmental and economic factors. Detecting where and when these changes happen can provide information to better understand trends in regional and even global rice production. Remote sensing offers a unique opportunity to estimate these trends. We apply the recently published PhenoRice algorithm to 14 years of moderate resolution remote sensing (MODIS) data (utilizing 250m resolution 16 day composites from Terra and Aqua) to estimate seasonality and cropping intensity per year and changes over time. We compare the results to the surveyed data collected by International Rice Research Institute (IRRI). The study results in a unique and validated dataset on the extent and change of extent, the seasonality and change in seasonality and the cropping intensity and change in cropping intensity between 2003 and 2016 for the Philippines. Observed trends and their implications for food security and trade policies are also discussed.
626
73612
Hydro-Chemical Characterization of Glacial Melt Waters Draining from Shaune Garang Glacier, Himachal Himalaya
Abstract:
A detailed study of the ion chemistry of the Shaune Garnag glacier meltwater has been carried out to assess the role of active glacier in the chemical denudation rate. The chemical compositions of various ions in meltwater of the Shaune Garang glacier were analyzed during the melting period 2015 and 2016. Total 112 of melt water samples twice in a day were collected during ablation season of 2015 and 2016. To identify various factors controlling the dissolved ionic strength of Shaune Garang Glacier meltwater statistical analysis such as correlation matrix, Principle Component Analysis (PCA) and factor analysis were applied to deduce the result. Cation concentration for Ca²⁺ > Mg²⁺ > Na⁺ > K⁺ in the meltwater for both the years can be arranged in the order as Ca²⁺ > Mg²⁺ > Na⁺ > K⁺. Study showed that Ca²⁺ and HCO₃⁻ found to be dominant on the both melting period. Carbonate weathering identified as the dominant process controlling the dissolved ion chemistry of meltwater due to the high ratios of (Ca²⁺ + Mg²⁺) versus TZ+ and (Ca²⁺ + Mg²⁺) versus (Na⁺ + K⁺) in the study area. The cation denudation rate of the Shaune Garnag catchment is 3412.2 m⁻² a⁻¹, i.e. higher than the other glacierised catchment in the Himalaya, indicating intense chemical erosion in this catchment.
625
73505
Triassic Magmatism in Southern Beishan Orogen, Northwest China: Zircon U–Pb Geochronology, Petrogenesis and Tectonic Implications
Authors:
Abstract:
The tectonic evolution of the Beishan orogen, which forms part of the Central Asian Orogenic Belt, remains debated. This study reports the identification of three Triassic granitic plutons representing two distinct stages of magmatism in southern Beishan orogen. Zircon U–Pb dating constrains the early stage as 238–237 Ma and the late stage as 229–227 Ma. The granitoids belong to high-K calc-alkaline and shoshonitic series and exhibit alkalic-calcic and calc-alkalic features, and are weakly peraluminous rocks. Most of these granitoids are highly fractionated I-type and A-type granites. They have relatively high Isr values (0.7049–0.7086) and weak negative εNd(t) values of −1.5 to −2.1, with young Nd model ages of 1.04–0.91 Ga, indicating a crustal contribution. They also show markedly positive zircon εHf(t) values (+3.4 to +11.8) and two-stage Hf model ages of 1.06–0.69 Ga, indicating a mixture of mantle and crustal components. The lithospheric mantle beneath this region incorporating older subducted materials was metasomatized by fluids or melts. Partial melting of the metasomatized lithospheric mantle resulted in underplated magmas, which provided the heat and material input to generate the granitoids. The Middle Triassic granitic plutons show moderate negative Eu anomalies, enrichment of LILEs and depletion in Nb, Ta, and Ti suggesting partial melting of crustal components in response to the underplated mantle-derived magmas, probably linked to lithospheric delamination and asthenospheric upwelling. The Late Triassic granitic plutons show characteristics of post-orogenic granite with strong negative anomalies of Eu, Ba, Nb, Sr, P, and Ti, indicating fractional crystallization and crustal contamination during the emplacement process.
624
73450
Dynamic Change of Floods Disaster Monitoring for River Central Bar by Remote Sensing Time-Series Images
Abstract:
The spatial extent and area of central river bars can always vary due to the impact of water level, sediment supply and human activities. In 2016, a catastrophic flood disaster caused by sustained and heavy rainfall happened in the middle and lower Yangtze River. The flood led to the most serious economic and social loss since 1954, and strongly affected the central river bar. It is essential to continuously monitor the dynamics change of central bars because it can avoid frequent field measurements in central bars before and after the flood disaster and is helpful for flood warning. This paper focused on the dynamic change of central bars of Phoenix bar and Changsha bar in the Yangtze River in 2016. In this study, GF-1 (GaoFen-1) WFV(wide field view) data was employed owing to its high temporal frequency and high spatial resolution. A simple NDWI (Normalized Difference Water Index) method was utilized for river central bar mapping. Human-checking was then performed to ensure the mapping quality. The relationship between the area of central bars and the measured water level was estimated using four mathematical models. Furthermore, a risk assessment index was proposed to map the spatial pattern of inundation risk of central bars. The results indicate a good ability of the GF-1 WFV imagery with a 16-m spatial resolution to characterize the seasonal variation of central river bars and to capture the impact of a flood disaster on the area of central bars. This paper observed a significant negative but nonlinear relationship between the water level and the area of central bars, and found that the cubic function fits best among four models (R² = 0.9839, P < 0.000001, RMSE = 0.4395). The maximum of the inundated area of central bars appeared during the rainy season on July 8, 2016, and the minimum occurred during the dry season on December 28, 2016, which are consistent with the water level measured by the hydrological station. The results derived from GF-1 data could provide a useful reference for decision-making of real-time disaster early warning and post-disaster reconstruction.
623
72988
Finding the Optimal Meeting Point Based on Travel Plans in Road Networks
Abstract:
Given a set of source locations for a group of friends, and a set of trip plans for each group member as a sequence of Categories-of-Interests (COIs) (e.g., restaurant), and finally a specific COI as a common destination that all group members will gather together, in Meeting Point Based on Trip Plans (MPTPs) queries our goal is to find a Point-of-Interest (POI) from different COIs, such that the aggregate travel distance for the group is minimized. In this work, we considered two cases for aggregate function as Sum and Max. For solving this query, we propose an efficient pruning technique for shrinking the search space. Our approach contains three steps. In the first step, it prunes the search space around the source locations. In the second step, it prunes the search space around the centroid of source locations. Finally, we compute the intersection of all pruned areas as the final refined search space. We prove that the POIs beyond the refined area cannot be part of optimal answer set. The paper also covers an extensive performance study of the proposed technique.
622
72809
Determination of Mercury in Gold Ores by CVAAS Method
Abstract:
Gold is recovered from gold ores. Within the ores, there are not only gold but also several types of precious metals. Copper, silver, and platinum group elements (ruthenium, rhodium, palladium, rhenium, osmium, and iridium) are metals commonly found in the ores. These metals combine to form an ore because they have the same properties. It is due to their position in periodic-system-of-elements are near to gold. However, the presence of mercury in every gold ore has not been mentioned, even though it is located right next to gold in the periodic-system-of-elements and they are located in the same block, d-block. Thus, it is possible that mercury is contained in the ores. Moreover, the elements of the same group with mercury—zinc and cadmium—sometimes can be found in the ores. It is suspected that mercury can not be detected because the processing of gold ores usually using fire assay method. Before the ores melting, mercury would evaporate because it has the lowest boiling point of all precious metal in the ores. Therefore, it suggested doing research on the presence of mercury in gold ores by CVAAS method. The results of this study would obtain the amount of mercury in gold ores that should be purified. So it can be produced economically if possible.
621
72792
General Time-Dependent Sequenced Route Queries in Road Networks
Abstract:
Spatial databases have been an active area of research over years. In this paper, we study how to answer the General Time-Dependent Sequenced Route queries. Given the origin and destination of a user over a time-dependent road network graph, an ordered list of categories of interests and a departure time interval, our goal is to find the minimum travel time path along with the best departure time that minimizes the total travel time from the source location to the given destination passing through a sequence of points of interests belonging to each of the specified categories of interest. The challenge of this problem is the added complexity to the optimal sequenced route queries, where we assume that first the road network is time dependent, and secondly the user defines a departure time interval instead of one single departure time instance. For processing general time-dependent sequenced route queries, we propose two solutions as Discrete-Time and Continuous-Time Sequenced Route approaches, finding approximate and exact solutions, respectively. Our proposed approaches traverse the road network based on A*-search paradigm equipped with an efficient heuristic function, for shrinking the search space. Extensive experiments are conducted to verify the efficiency of our proposed approaches.
620
72743
A First Step towards Automatic Evolutionary for Gas Lifts Allocation Optimization
Abstract:
Oil production by means of gas lift is a standard technique in oil production industry. To optimize the total amount of oil production in terms of the amount of gas injected is a key question in this domain. Different methods have been tested to propose a general methodology. Many of them apply well-known numerical methods. Some of them have taken into account the power of evolutionary approaches. Our goal is to provide the experts of the domain with a powerful automatic searching engine into which they can introduce their knowledge in a format close to the one used in their domain, and get solutions comprehensible in the same terms, as well. These proposals introduced in the genetic engine the most expressive formal models to represent the solutions to the problem. These algorithms have proven to be as effective as other genetic systems but more flexible and comfortable for the researcher although they usually require huge search spaces to justify their use due to the computational resources involved in the formal models. The first step to evaluate the viability of applying our approaches to this realm is to fully understand the domain and to select an instance of the problem (gas lift optimization) in which applying genetic approaches could seem promising. After analyzing the state of the art of this topic, we have decided to choose a previous work from the literature that faces the problem by means of numerical methods. This contribution includes details enough to be reproduced and complete data to be carefully analyzed. We have designed a classical, simple genetic algorithm just to try to get the same results and to understand the problem in depth. We could easily incorporate the well mathematical model, and the well data used by the authors and easily translate their mathematical model, to be numerically optimized, into a proper fitness function. We have analyzed the 100 curves they use in their experiment, similar results were observed, in addition, our system has automatically inferred an optimum total amount of injected gas for the field compatible with the addition of the optimum gas injected in each well by them. We have identified several constraints that could be interesting to incorporate to the optimization process but that could be difficult to numerically express. It could be interesting to automatically propose other mathematical models to fit both, individual well curves and also the behaviour of the complete field. All these facts and conclusions justify continuing exploring the viability of applying the approaches more sophisticated previously proposed by our research group.
619
72738
Hg Anomalies and Soil Temperature Distribution to Delineate Upflow and Outflow Zone in Bittuang Geothermal Prospect Area, south Sulawesi, Indonesia
Abstract:
Bittuang geothermal prospect area located at Tana Toraja district, South Sulawesi. The geothermal system of the area related to Karua Volcano eruption product. This area has surface manifestation such as fumarole, hot springs, sinter silica and mineral alteration. Those prove that there are hydrothermal activities in the subsurface. However, the project and development of the area have not implemented yet. One of the important elements in geothermal exploration is to determine upflow and outflow zone. This information very useful to identify the target for geothermal wells and development which it is a risky task. The methods used in this research were Mercury (Hg) anomalies in soil, soil and manifestation temperature distribution and fault fracture density from 93 km² research area. Hg anomalies performed to determine the distribution of hydrothermal alteration. Soil and manifestation temperature distribution were conducted to estimate heat distribution. Fault fracture density (FFD) useful to determine fracture intensity and trend from surface observation. Those deliver Hg anomaly map, soil and manifestation temperature map that combined overlayed to fault fracture density map and geological map. Then, the conceptual model made from north – south, and east – west cross section to delineate upflow and outflow zone in this area. The result shows that upflow zone located in northern – northeastern of the research area with the increase of elevation and decrease of Hg anomalies and soil temperature. The outflow zone located in southern - southeastern of the research area which characterized by chloride, chloride - bicarbonate geothermal fluid type, higher soil temperature, and Hg anomalies. The range of soil temperature distribution from 16 – 19 °C in upflow and 19 – 26.5 °C in the outflow. The range of Hg from 0 – 200 ppb in upflow and 200 – 520 ppb in the outflow. Structural control of the area show northwest – southeast trend. The boundary between upflow and outflow zone in 1550 – 1650 m elevation. This research delivers the conceptual model with innovative methods that useful to identify a target for geothermal wells, project, and development in Bittuang geothermal prospect area.
618
72427
Simulation Study of Asphaltene Deposition and Solubility of CO₂ in the Brine during Cyclic CO₂ Injection Process in Unconventional Tight Reservoirs
Abstract:
A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO2 injection process in unconventional tight reservoir. Cyclic CO2 injection is an enhanced oil recovery process consisting of injection, shut-in and production. The study of cyclic CO2 injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO2 injection process to distinguish the parameters with maximum effect on the oil recovery and comprehend the behavior of cyclic CO2 injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issue in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, Solubility of CO2 in the aquifer is one of the safest and permanent trapping techniques when considering CO2 storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO2 enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters dominating the process. The main objective of this study is to improve techniques for designing cyclic CO2 injection process while considering the effects of asphaltene deposition and solubility of CO2 in the brine; in order to prevent asphaltene precipitation, minimize CO2 emission, optimize cyclic CO2 injection and maximize oil production.
617
72133
Development of a Suitable Model for Energy Storage in Residential Buildings in Ahvaz Using Energy Plus Software
Abstract:
This research tries to study the residential buildings in Ahvaz, the common materials used, and the impact of passive methods of energy storage (as one of the most effective ways to reduce energy consumption in residential complexes) in order to achieve patterns for construction of residential buildings in Ahvaz conditions to reduce energy consumption. In this research, after studying Ahvaz conditions, the components of an existing building were simulated in Energy Plus software, and the climatic data of Ahvaz station was introduced to software. Then to achieve the most optimal conditions of energy consumption in Ahvaz conditions, each of the residential building elements was optimized. The results of simulation showed that using inactive materials and design including double glass, outside wall insulation, inverted roof, etc. in the buildings can reduce energy consumption in the hot and dry climate of Ahvaz. Among the parameters investigated, the inverted roof was the most effective energy saving pattern. According to the results of simulation of the entire building with the most optimal parameters, energy consumption can be saved by a mean of 12.51% in buildings of Ahvaz, and the obtained pattern can also be used in similar climates.
616
72126
Strategic Mine Planning: A Strengths, Weaknesses, Opportunities, Threats Analysis Applied to Kamoto Oliveira Virgule Open Pit Mine in the Democratic Republic of Congo
Authors:
Abstract:
KOV pit (Kamoto Oliveira Virgule) is located 10 km from Kolwezi town, one of the mineral rich town in the Lualaba province of the Democratic Republic of Congo. The KOV pit is currently operating under the Katanga Mining Limited (KML), a Glencore-Gecamines (a State Owned Company) join venture. Recently, the mine optimization process provided a life of mine of approximately ten years with nine pushbacks using the Datamine NPV Scheduler software. In previous KOV pit studies, we recently outlined the impact of the accuracy of the geological information on a long term mine plan for a big copper mine such as KOV pit. The approach taken discussed three main scenarios and outlined some weaknesses on the geological information side, and now, in the paper that we are going to develop here, we are going to highlight, as an overview, those weaknesses, strengths, and opportunities, in a global SWOT analysis. The approach we are taking here is essentially descriptive in terms of steps taken to optimize KOV pit and, at every step, we categorized the challenges we faced to have a better tradeoff between what we called strengths and what we called weaknesses. Same logic is applied in terms of opportunities and threats. The SWOT analysis conducted in this paper demonstrates that, despite a general poor ore body definition, and very rude ground water conditions, there is room for improvement for such high-grade ore body.
615
71905
Water-Bentonite Interaction of Green Pellets through Micro-Structural Analysis
Abstract:
The quality of pellets produced is affected by quality and type of green pellets, amount of addition of binders and fluxing agents along with the provided firing conditions. The green pellet quality depends upon chemistry, mineralogy and granulometry of fines used for pellet making, the feed size, its moisture content and porosity. During firing of green pellets, ingredients present within reacts to form different phases and microstructure. So in turn, physical and metallurgical properties of pellets are influenced by amount and type of binder and flux addition, induration time and temperature. During iron making process, the metallurgical properties of fired pellets are decided by the type and amount of these phases and their chemistry. Green pelletizing and induration studies have been already carried out with magnetite and hematite ore fines but for Indian iron ores of high alumina content showing different pelletizing characters, these studies cannot be directly interpreted. The main objective of proposed research work is to understand the green pelletizing process and determine the water bentonite interaction at different levels. Swelling behavior of bentonite and microstructure of the green pellet are investigated. Conversion of iron ore fines into pellets, the key raw material and process variables that influence the pellet quality needs to be identified and a correlation should be established between them.
614
71887
Phase Detection Using Infrared Spectroscopy: A Build up to Inline Gas–Liquid Flow Characterization
Abstract:
The characterization of multiphase flow has gained enormous attention for most petroleum and chemical industrial processes. In order to fully characterize fluid phases in a stream or containment, there needs to be a profound knowledge of the existing composition of fluids present. This introduces a problem for real-time monitoring of fluid dynamics such as fluid distributions, and phase fractions. This work presents a simple technique of correlating absorbance spectrums of water, oil and air bubble present in containment. These spectra absorption outputs are derived by using an Fourier Infrared spectrometer. During the testing, air bubbles were introduced into static water column and oil containment and with light absorbed in the infrared regions of specific wavelength ranges. Attenuation coefficients are derived for various combinations of water, gas and oil which reveal the presence of each phase in the samples. The results from this work are preliminary and viewed as a build up to the design of a multiphase flow rig which has an infrared sensor pair to be used for multiphase flow characterization.
613
71696
Remote Sensing Reversion of Water Depths and Water Management for Waterbird Habitats: A Case Study on the Stopover Site of Siberian Cranes at Momoge, China
Abstract:
Traditional water depth survey of wetland habitats used by waterbirds needs intensive labor, time and money. The optical remote sensing image relies on passive multispectral scanner data has been widely employed to study estimate water depth. This paper presents an innovative method for developing the water depth model based on the characteristics of visible and thermal infrared spectra of Landsat ETM+ image, combing with 441 field water depth data at Etoupao shallow wetland. The wetland is located at Momoge National Nature Reserve of Northeast China, where the largest stopover habitat along the eastern flyway of globally, critically-endangered Siberian Cranes are. The cranes mainly feed on the tubers of emergent aquatic plants such as Scirpus planiculmis and S. nipponicus. The effective water control is a critical step for maintaining the production of tubers and food availability for this crane. The model employing multi-band approach can effectively simulate water depth for this shallow wetland. The model parameters of NDVI and GREEN indicated the vegetation growth and coverage affecting the reflectance from water column change are uneven. Combining with the field-observed water level at the same date of image acquisition, the digital elevation model (DEM) for the underwater terrain was generated. The wetland area and water volume of different water levels were then calculated from the DEM using the function of Area and Volume Statistics under the 3D Analyst of ArcGIS 10.0. The findings provide good references to effectively monitor changes in water level and water demand, develop practical plan for water level regulation and water management, and to create best foraging habitats for the cranes. The methods here can be adopted for the bottom topography simulation and water management in waterbirds’ habitats, especially in the shallow wetlands.
612
71553
Comparison between Photogrammetric and Structure from Motion Techniques in Processing Unmanned Aerial Vehicles Imageries
Abstract:
Over the last few years, significant progresses have been made and new approaches have been proposed for efficient collection of 3D spatial data from Unmanned aerial vehicles (UAVs) with reduced costs compared to imagery from satellite or manned aircraft. In these systems, a low-cost GPS unit provides the position, velocity of the vehicle, a low-quality inertial measurement unit (IMU) determines its orientation, and off-the-shelf cameras capture the images. Structure from Motion (SfM) and photogrammetry are the main tools for 3D surface reconstruction from images collected by these systems. Unlike traditional techniques, SfM allows the computation of calibration parameters using point correspondences across images without performing a rigorous laboratory or field calibration process and it is more flexible in that it does not require consistent image overlap or same rotation angles between successive photos. These benefits make SfM ideal for UAVs aerial mapping. In this paper, a direct comparison between SfM Digital Elevation Models (DEM) and those generated through traditional photogrammetric techniques was performed. Data was collected by a 3DR IRIS+ Quadcopter with a Canon PowerShot S100 digital camera. Twenty ground control points were randomly distributed on the ground and surveyed with a total station in a local coordinate system. Images were collected from an altitude of 30 meters with a ground resolution of nine mm/pixel. Data was processed with PhotoScan, VisualSFM, Imagine Photogrammetry, and a photogrammetric algorithm developed by the author. The algorithm starts with performing a laboratory camera calibration then the acquired imagery undergoes an orientation procedure to determine the cameras’ positions and orientations. After the orientation is attained, correlation based image matching is conducted to automatically generate three-dimensional surface models followed by a refining step using sub-pixel image information for high matching accuracy. Tests with different number and configurations of the control points were conducted. Camera calibration parameters estimated from commercial software and those obtained with laboratory procedures were comparable. Exposure station positions were within less than few centimeters and insignificant differences, within less than three seconds, among orientation angles were found. DEM differencing was performed between generated DEMs and few centimeters vertical shifts were found.
611
71532
Land Cover Classification Using Sentinel-2 Image Data and Random Forest Algorithm
Abstract:
The currently launched Sentinel 2 (S2) satellite (June, 2015) bring a great potential and opportunities for land use/cover map applications, due to its fine spatial resolution multispectral as well as high temporal resolutions. So far, there are handful studies using S2 real data for land cover classification. Especially in northern Vietnam, to our best knowledge, there exist no studies using S2 data for land cover map application. The aim of this study is to provide the preliminary result of land cover classification using Sentinel -2 data with a rising state – of – art classifier, Random Forest. A case study with heterogeneous land use/cover in the eastern of Hanoi Capital – Vietnam was chosen for this study. All 10 spectral bands of 10 and 20 m pixel size of S2 images were used, the 10 m bands were resampled to 20 m. Among several classified algorithms, supervised Random Forest classifier (RF) was applied because it was reported as one of the most accuracy methods of satellite image classification. The results showed that the red-edge and shortwave infrared (SWIR) bands play an important role in land cover classified results. A very high overall accuracy above 90% of classification results was achieved.
610
71141
Seismic Vulnerability of Structures Designed in Accordance with the Allowable Stress Design and Load Resistant Factor Design Methods
Abstract:
The method selected for the design of structures not only can affect their seismic vulnerability but also can affect their construction cost. For the design of steel structures, two distinct methods have been introduced by existing codes, namely allowable stress design (ASD) and load resistant factor design (LRFD). This study investigates the effect of using the aforementioned design methods on the seismic vulnerability and construction cost of steel structures. Specifically, a 20-story building equipped with special moment resisting frame and an eccentrically braced system was selected for this study. The building was designed for three different intensities of peak ground acceleration including 0.2 g, 0.25 g, and 0.3 g using the ASD and LRFD methods. The required sizes of beams, columns, and braces were obtained using response spectrum analysis. Then, the designed frames were subjected to nine natural earthquake records which were scaled to the designed response spectrum. For each frame, the base shear, story shears, and inter-story drifts were calculated and then were compared. Results indicated that the LRFD method led to a more economical design for the frames. In addition, the LRFD method resulted in lower base shears and larger inter-story drifts when compared with the ASD method. It was concluded that the application of the LRFD method not only reduced the weights of structural elements but also provided a higher safety margin against seismic actions when compared with the ASD method.