Academic literature on the topic 'IDW GEOSTATISTICS'
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Journal articles on the topic "IDW GEOSTATISTICS"
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Syaeful, Heri, and Suharji Suharji. "Geostatistics Application On Uranium Resources Classification: Case Study of Rabau Hulu Sector, Kalan, West Kalimantan." EKSPLORIUM 39, no. 2 (January 31, 2019): 131. http://dx.doi.org/10.17146/eksplorium.2018.39.2.4960.
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ABSTRACT In resources estimation, geostatistics methods have been widely used with the benefit of additional attribute tools to classify resources category. However, inverse distance weighting (IDW) is the only method used previously for estimating the uranium resources in Indonesia. The IDW method provides no additional attribute that could be used to classify the resources category. The objective of research is to find the best practice on geostatistics application in uranium resource estimation adjusted with geological information and determination of acceptable geostatistics estimation attribute for resources categorization. Geostatistics analysis in Rabau Hulu Sector was started with correlation of the orebody between boreholes. The orebodies in Rabau Hulu Sectors are separated individual domain which further considered has the hard domain. The orebody-15 was selected for further geostatistics analysis due to its wide distribution and penetrated most by borehole. Stages in geostatistics analysis cover downhole composites, basic statistics analysis, outliers determination, variogram analysis, and calculation on the anisotropy ellipsoid. Geostatistics analysis shows the availability of the application for two resources estimation attributes, which are kriging efficiency and kriging variance. Based on technical judgment of the orebody continuity versus the borehole intensity, the kriging efficiency is considered compatible with geological information and could be used as parameter for determination of the resources category. ABSTRAK Pada estimasi sumber daya, metode geostatistik telah banyak digunakan dengan kelebihan adanya alat atribut tambahan untuk mengklasifikasikan kategori sumber daya. Namun demikian, pembobotan inverse distance (IDW) adalah satu-satunya metode yang sebelumnya digunakan untuk mengestimasi sumber daya uranium di Indonesia. Metode IDW tidak memberikan tambahan atribut yang dapat digunakan dalam mengklasifikasikan kategori sumber daya. Tujuan dari penelitian adalah mendapatkan praktek terbaik untuk aplikasi geostatistik pada estimasi sumber daya disesuaikan dengan informasi geologi dan penentuan atribut geostatistik yang dapat digunakan untuk kategorisasi sumber daya. Analisis geostatistik di Sektor Rabau Hulu diawali dengan korelasi tubuh bijih antara lubang bor. Tubuh-tubuh bijih di Sektor Rabau Hulu merupakan domain individual yang selanjutnya dipertimbangkan memiliki domain tegas. Tubuh bijih-15 dipilih untuk digunakan pada analisis geostatistik selanjutnya karena distribusinya yang luas dan paling banyak dipenetrasi bor. Tahapan dalam analisis geostatistik mencakup komposit downhole, analisis statistik dasar, determinasi outliers, analisis variogram, dan perhitungan ellipsoid anisotropi. Analisis geostatistik menghasilkan kemungkinan aplikasi dua atribut estimasi sumber daya, yaitu kriging efisiensi dan kriging varians. Berdasarkan penilaian teknis kemenerusan tubuh bijih terhadap intensitas lubang bor, kriging efisiensi dipertimbangkan sesuai dengan informasi geologi dan dapat digunakan sebagai parameter untuk penentuan kategori sumber daya.
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Idir, Yacine Mohamed, Olivier Orfila, Vincent Judalet, Benoit Sagot, and Patrice Chatellier. "Mapping Urban Air Quality from Mobile Sensors Using Spatio-Temporal Geostatistics." Sensors 21, no. 14 (July 9, 2021): 4717. http://dx.doi.org/10.3390/s21144717.
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With the advancement of technology and the arrival of miniaturized environmental sensors that offer greater performance, the idea of building mobile network sensing for air quality has quickly emerged to increase our knowledge of air pollution in urban environments. However, with these new techniques, the difficulty of building mathematical models capable of aggregating all these data sources in order to provide precise mapping of air quality arises. In this context, we explore the spatio-temporal geostatistics methods as a solution for such a problem and evaluate three different methods: Simple Kriging (SK) in residuals, Ordinary Kriging (OK), and Kriging with External Drift (KED). On average, geostatistical models showed 26.57% improvement in the Root Mean Squared Error (RMSE) compared to the standard Inverse Distance Weighting (IDW) technique in interpolating scenarios (27.94% for KED, 26.05% for OK, and 25.71% for SK). The results showed less significant scores in extrapolating scenarios (a 12.22% decrease in the RMSE for geostatisical models compared to IDW). We conclude that univariable geostatistics is suitable for interpolating this type of data but is less appropriate for an extrapolation of non-sampled places since it does not create any information.
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AbdelRahman, Mohamed A. E., Yasser M. Zakarya, Mohamed M. Metwaly, and Georgios Koubouris. "Deciphering Soil Spatial Variability through Geostatistics and Interpolation Techniques." Sustainability 13, no. 1 (December 28, 2020): 194. http://dx.doi.org/10.3390/su13010194.
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Detailed knowledge of soil properties is fundamentally important for optimizing agriculture practices and management. Meanwhile, the spatial distribution of soil physicochemical properties is considered a fundamental input of any sustainable agricultural planning. In the present study, ordinary kriging, regression kriging and IDW were chosen for deciphering soil spatial variability and mapping soil properties in a reclaimed area of the Behera Governorate of Egypt where soil arose from two different types, one sandstone and the other limestone. Geostatistics were used to show the interrelationships and conditions of soil properties (available phosphorus, potassium and nitrogen, EC, pH, Sp, ESP, CEC, OC, SAR, and CaCO3). The results of mapping spatial soil variability by Geostatistics could be used for precision agriculture applications. Based on the soil test results, nutrient management recommendations should be applied regarding variable rates of fertilizers. The performance of the maps was evaluated using Mean square error (MSE). Inverse distance weight (IDW) showed higher efficiency than Kriging as a prediction method for mapping the studied soil properties in the study area. The results of the present study suggest that the application of the selected fit model worldwide in any relevant study of soil properties of different geological sources is feasible.
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Permata, Linda. "Non-linear Geostatistics Approach for An Integrated Surface Mapping in Epithermal Gold Deposit, Lampung." Journal of Science and Applicative Technology 5, no. 2 (July 1, 2021): 259. http://dx.doi.org/10.35472/jsat.v5i2.444.
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A conventional surface mapping is calculated by any means of linear interpolator such as nearest neighborhood point (NNP), inverse distance (IDW)/inverse distance square (IDS), polygon, contour weighing, Ordinary Kriging (OK). The latter is included in geostatistic methods and provides more advanced weighing method that differs from the rest. Although OK provides smoothing over mapping data but it does not cover categorial (non-value) data. Besides, it is not best in strongly skewed data that are common in exploration data and is limited to the expected value at some location. On the other hand, a non-linear interpolator is conducted to estimate the conditional expectation at a location, that not only to simply predict the grade or other parameter itself, but also the probability of the parameter at a location with known nearby samples. An integrated surface mapping should have many kinds of data that can be categorized into continous data (grade, thickness, elevation, etc.) and categorial data (lithology, alteration, structural data, etc.). In order to create a block that consist of all data available in a given deposit, a non-linier transformation will be conducted to estimate values at determined thresholds by Kriging methods – known as Indicator Kriging method and its variants.
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Ly, S., C. Charles, and A. Degré. "Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium." Hydrology and Earth System Sciences 15, no. 7 (July 18, 2011): 2259–74. http://dx.doi.org/10.5194/hess-15-2259-2011.
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Abstract. Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (kriging) are widely applied in spatial interpolation from point measurement to continuous surfaces. The first step in kriging computation is the semi-variogram modelling which usually used only one variogram model for all-moment data. The objective of this paper was to develop different algorithms of spatial interpolation for daily rainfall on 1 km2 regular grids in the catchment area and to compare the results of geostatistical and deterministic approaches. This study leaned on 30-yr daily rainfall data of 70 raingages in the hilly landscape of the Ourthe and Ambleve catchments in Belgium (2908 km2). This area lies between 35 and 693 m in elevation and consists of river networks, which are tributaries of the Meuse River. For geostatistical algorithms, seven semi-variogram models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) were fitted to daily sample semi-variogram on a daily basis. These seven variogram models were also adopted to avoid negative interpolated rainfall. The elevation, extracted from a digital elevation model, was incorporated into multivariate geostatistics. Seven validation raingages and cross validation were used to compare the interpolation performance of these algorithms applied to different densities of raingages. We found that between the seven variogram models used, the Gaussian model was the most frequently best fit. Using seven variogram models can avoid negative daily rainfall in ordinary kriging. The negative estimates of kriging were observed for convective more than stratiform rain. The performance of the different methods varied slightly according to the density of raingages, particularly between 8 and 70 raingages but it was much different for interpolation using 4 raingages. Spatial interpolation with the geostatistical and Inverse Distance Weighting (IDW) algorithms outperformed considerably the interpolation with the Thiessen polygon, commonly used in various hydrological models. Integrating elevation into Kriging with an External Drift (KED) and Ordinary Cokriging (OCK) did not improve the interpolation accuracy for daily rainfall. Ordinary Kriging (ORK) and IDW were considered to be the best methods, as they provided smallest RMSE value for nearly all cases. Care should be taken in applying UNK and KED when interpolating daily rainfall with very few neighbourhood sample points. These recommendations complement the results reported in the literature. ORK, UNK and KED using only spherical model offered a slightly better result whereas OCK using seven variogram models achieved better result.
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Logan, J., and M. A. Mueller. "Using Geospatial Techniques and GIS to Develop Maps of Freeze Probabilities and Growing Degrees." HortScience 35, no. 4 (July 2000): 558D—558c. http://dx.doi.org/10.21273/hortsci.35.4.558d.
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Tennessee is located in an area of diverse topography, ranging in elevation from <100 m to ≈2000 m, with numerous hills and valleys. The physiography makes it very difficult to spatially interpolate weather data related to vegetable production, such as spring and fall freeze dates and growing degree days (GDD). In addition, there is a poor distribution of cooperative weather stations, especially those with 30 years or more of data. There are climate maps available for Tennessee, but they are of such a general format as to be useless for operational applications. This project is designed to use a geographic information system (GIS) and geospatial techniques to spatially interpolate freeze (0 °C) dates and GDD for different base temperatures and make the data available as Internet-based maps. The goal is to develop reasonable climate values for vegetable growing areas <1000 m in elevation at a 100 square km resolution. The geostatistics that we are evaluating include Thiessen polygons, triangulated irregular network (TIN), inverse distance weighting (IDW), spline, kriging, and cokriging. Data from 140 locations in and around Tennessee are used in the analysis. Incomplete data from 100 other locations are used to validate the models. GDD, which have much less year-to-year variability than freeze dates, can be successfully interpolated using inverse distance weighting (IDW) or spline techniques. Even a simple method like Thiessen produces fairly accurate maps. Freeze dates, however, are better off analyzed on an annual basis because the patterns can vary significantly from year to year. The annual maps can then be superimposed to give a better estimate of average spring and fall freeze dates.
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Herlina, Herlina, and Diyono Diyono. "ANALISIS GEOSTATISTIK UNTUK PEMETAAN PERUBAHAN KUALITAS AIR TANAH KAWASAN KARST KABUPATEN GUNUNGKIDUL." Elipsoida : Jurnal Geodesi dan Geomatika 3, no. 01 (July 3, 2020): 1–12. http://dx.doi.org/10.14710/elipsoida.2020.7762.
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Gunungkidul Regency has a karst area of approximately 807 km2 or 53% of the total area of its territory. There is a tendency for expansion in karst mining leading to a number of potentials, including damage to the water system which is a pollution of karst water sources. Temperature, turbidity, Total Dissolve Solid (TDS), PH, hardness, manganese, iron, and chloride are parameters affecting groundwater quality. Measurement of the concentration of each parameter is performed through a long process and expensive costs. Therefore, not all measurements are performed in the entire area of Gunungkidul. Hence, it is important to interpolate the eight parameters using the geostatistical method. Geostatistical kriging method is an estimation method that reduces the error of variance estimation by a cross-correlation between primary and secondary variables. The best semivariogram for a five-year period with the smallest RMSE value is the temperature in 2018 using an gaussian model, turbidity in 2018 using a IDW model, Total Dissolve Solid (TDS) in 2017 using a gaussian model, PH in 2016 using a linear exponential, hardness in 2019 using a exponential model, manganese in 2017 using a circular model, iron in 2017 using a exponential model, and chlorides in 2015 using a RBF. Monitoring points of groundwater quality using these eight parameters have different variances so that five parameters are producing more than one RMSE value. To resolve this, besides comparing several interpolation methods, natural logarithmic transformations and the correlation of actual values with estimates were also performed. The correlation between the actual value and the estimation indicates that the estimation produced by the non-transformed data is more accurate than the transformed data. The estimated results of each parameter are visualized in the form of a map so that changes in groundwater quality every year can be seen. Besides the maps, the results of this study are shown in graphs of changes in the form of cross-sections of each parameter from 2015 to 2019. Visualization of changes in the quality level groundwater is expected to give input for relevant agencies in the conservation of water resources. Keywords: Karst Mining, Mapping, Geostatistics, Groundwater Quality.
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Bernardi, A. C. C., G. M. Bettiol, G. G. Mazzuco, S. N. Esteves, P. P. A. Oliveira, and J. R. M. Pezzopane. "Spatial variability of soil fertility in an integrated crop livestock forest system." Advances in Animal Biosciences 8, no. 2 (June 1, 2017): 590–93. http://dx.doi.org/10.1017/s2040470017001145.
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Knowledge on spatial variability of soil properties is useful for the rational use of inputs, as in the site specific application of lime and fertilizer. Crop-livestock-forest integrated systems (CLFIS) provide a strategy of sustainable agricultural production which integrates annual crops, trees and livestock activities on a same area and in the same season. Since the lime and fertilizer are key factors for the intensification of agricultural systems in acid-soil in the tropics, precision agriculture (PA) is the tool to improve the efficiency of use of these issues. The objective of this research was to map and evaluate the spatial variability of soil properties, liming and fertilizer need of a CLFIS. The field study was carried out in a 30 ha area at Embrapa Pecuária Sudeste in São Carlos, SP, Brazil. Soil samples were collected at 0–0.2 m depth, and each sample represented a paddock. The spatial variability of soil properties and site-specific liming and fertilizer needs were modeled using semi-variograms, the soil fertility information were modeled. Spatial variability soil properties and site specific liming and fertilizer need were modeled by kriging and inverse distance weighting (IDW) techniques. Another approach used was based on lime and fertilizer recommendation considering the paddocks as the minimum management unit. The results showed that geostatistics and GIS were useful tools for revealing soil spatial variability and supporting management strategies. Soil nutrients were used to classify the soil spatial distribution map and design site-specific lime and fertilizer application zones. Spatial analyses of crop needs and requirement can provide management tools for avoiding potential environmental problems, caused by unbalanced nutrient supplies.
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Han, Zhifeng, Jianxin Liao, Qi Qi, Haifeng Sun, and Jingyu Wang. "Radio Environment Map Construction by Kriging Algorithm Based on Mobile Crowd Sensing." Wireless Communications and Mobile Computing 2019 (February 3, 2019): 1–12. http://dx.doi.org/10.1155/2019/4064201.
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In the IoT era, 5G will enable various IoT services such as broadband access everywhere, high user and devices mobility, and connectivity of massive number of devices. Radio environment map (REM) can be applied to improve the utilization of radio resources for the access control of IoT devices by allocating them reasonable wireless spectrum resources. However, the primary problem of constructing REM is how to collect the large scale of data. Mobile crowd sensing (MCS), leveraging the smart devices carried by ordinary people to collect information, is an effective solution for collecting the radio environment information for building the REM. In this paper, we build a REM collecting prototype system based on MCS to collect the data required by the radio environment information. However, limited by the budget of the platform, it is hard to recruit enough participants to join the sensing task to collect the radio environment information. This will make the radio environment information of the sensing area incomplete, which cannot describe the radio information accuracy. Considering that the Kriging algorithm has been widely used in geostatistics principle for spatial interpolation for Kriging giving the best unbiased estimate with minimized variance, we utilize the Kriging interpolation algorithm to infer complete radio environment information from collected sample radio environment information data. The interpolation performance is analyzed based on the collected sample radio environment information data. We demonstrate experiments to analyze the Kriging interpolation algorithm interpolation results and error and compared them with the nearest neighbor (NN) and the inverse distance weighting (IDW) interpolation algorithms. Experiment results show that the Kriging algorithm can be applied to infer radio environment information data based on the collected sample data and the Kriging interpolation has the least interpolation error.
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Ly, S., C. Charles, and A. Degré. "Spatial interpolation of daily rainfall at catchment scale: a case study of the Ourthe and Ambleve catchments, Belgium." Hydrology and Earth System Sciences Discussions 7, no. 5 (September 27, 2010): 7383–416. http://dx.doi.org/10.5194/hessd-7-7383-2010.
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Abstract. Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (krigings) are widely used in spatial interpolation from point measurement to continuous surfaces. However, the majority of existing geostatistical algorithms are available only for single-moment data. The first step in kriging computation is the semi-variogram modelling which usually uses only one variogram model for all-moment data. The objective of this paper was to develop different algorithms of spatial interpolation for daily rainfall on 1 km2 regular grids in the catchment area and to compare the results of geostatistical and deterministic approaches. In this study, we used daily rainfall data from 70 raingages in the hilly landscape of the Ourthe and Ambleve catchments in Belgium (2908 km2). This area lies between 35 and 693 m in elevation and consists of river networks, which are tributaries of the Meuse River. For geostatistical algorithms, Cressie's Approximate Weighted Least Squares method was used to fit seven semi-variogram models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) to daily sample semi-variogram on a daily basis. Seven selected raingages were used to compare the interpolation performance of these algorithms applied to many degenerated-raingage cases. Spatial interpolation with the geostatistical and Inverse Distance Weighting (IDW) algorithms outperformed considerably interpolation with the Thiessen polygon that is commonly used in various hydrological models. Kriging with an External Drift (KED) and Ordinary Cokriging (OCK) presented the highest Root Mean Square Error (RMSE) between the geostatistical and IDW methods. Ordinary Kriging (ORK) and IDW were considered to be the best methods, as they provided smallest RMSE value for nearly all cases.
Dissertations / Theses on the topic "IDW GEOSTATISTICS"
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Sarmah, Dipsikha. "Evaluation of Spatial Interpolation Techniques Built in the Geostatistical Analyst Using Indoor Radon Data for Ohio,USA." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1350048688.
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Franke, Jonas. "Spatiotemporal dynamics of stress factors in wheat analysed by multisensoral remote sensing and geostatistics." [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=986005169.
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Nowak, Wolfgang. "Geostatistical methods for the identification of flow and transport parameters in the subsurface." Stuttgart Inst. für Wasserbau, 2004. http://deposit.d-nb.de/cgi-bin/dokserv?idn=97474896X.
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Li, Chuanling. "Dynamics of late quaternary mammal population inferred from geostatistical study of the faunmap database and its implications for conservation." [S.l.] : [s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=971929661.
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Bentley, Andrew Phillip Keller. "Characterizing Subsurface Complexity of Aeolian Morphotypes with Georadar." Master's thesis, Temple University Libraries, 2013. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/226136.
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GeologyM.S.
Aeolian landforms are classified based on their plan morphology, which is a function of sediment transport volume, wind direction, and vegetation. In the case of compound landforms or two-dimensional exposures (outcrops), there is insufficient information for discriminating between 3D morphotypes (e.g., barchans vs. parabolic dunes). To characterize the dip-section architecture of near end-member morphologies (interacting barchans and sparsely vegetated parabolics), a series of axial transects were selected from >25 km of high-resolution (500 MHz) ground-penetrating radar (GPR) data from the gypsum dune field of White Sands National Monument, New Mexico. For dunes of comparable size (6-7 m high), a series of attributes were analyzed for unsaturated portions along the thickest (axial) radargram sections. Given the limitations in vertical resolution (7 cm in dry sand), the average measureable slipface thickness in barchans ranged between 10-22 cm, whereas parabolic slipfaces were thinner at 10-14 cm. High-amplitude diffractions produced by buried vegetation, semi-lithified pedestals, and bioturbation structures were rare within barchans (point-source diffraction density = 0.03/m2; hyperbolics per 1-m-wide cross-sectional area of the image), in contrast to a point-source density of 0.07/m2 in parabolics. An aeolian internal complexity threshold (ϖ) is proposed, which incorporates standardized scores of slipface thickness, point-source diffraction density, and continuity of major bounding surfaces at mesoscale range determined through semivariogram analysis. For the study region, these variables were sufficient for discriminating barchans (ϖ = -2.39 to -0.25; ϖ ̅b= -1.65) from parabolic (ϖ = 0.13 to 2.87; ϖ ̅p= 1.65) dunes. This threshold has the potential for differentiating dune morphotypes in areas where surface morphology is masked and for identifying compound landforms (e.g., a re-activated parabolic dune converted into a barchan in situ). Ultimately, characterization of bedding complexity in ancient aeolian sequences will provide useful information about key paleoenvironmental variables.
Temple University--Theses
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Höfler, Veit, Christine Wessollek, and Pierre Karrasch. "Knowledge-based modelling of historical surfaces using lidar data." SPIE, 2016. https://tud.qucosa.de/id/qucosa%3A35116.
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Currently in archaeological studies digital elevation models are mainly used especially in terms of shaded reliefs for the prospection of archaeological sites. Hesse (2010) provides a supporting software tool for the determination of local relief models during the prospection using LiDAR scans. Furthermore the search for relicts from WW2 is also in the focus of his research.¹ In James et al. (2006) the determined contour lines were used to reconstruct locations of archaeological artefacts such as buildings.² This study is much more and presents an innovative workflow of determining historical high resolution terrain surfaces using recent high resolution terrain models and sedimentological expert knowledge. Based on archaeological field studies (Franconian Saale near Bad Neustadt in Germany) the sedimentological analyses shows that archaeological interesting horizon and geomorphological expert knowledge in combination with particle size analyses (Köhn, DIN ISO 11277) are useful components for reconstructing surfaces of the early Middle Ages.³ Furthermore the paper traces how it is possible to use additional information (extracted from a recent digital terrain model) to support the process of determination historical surfaces. Conceptual this research is based on methodology of geomorphometry and geo-statistics. The basic idea is that the working procedure is based on the different input data. One aims at tracking the quantitative data and the other aims at processing the qualitative data. Thus, the first quantitative data were available for further processing, which were later processed with the qualitative data to convert them to historical heights. In the final stage of the work ow all gathered information are stored in a large data matrix for spatial interpolation using the geostatistical method of Kriging. Besides the historical surface, the algorithm also provides a first estimation of accuracy of the modelling. The presented workflow is characterized by a high exibility and the opportunity to include new available data in the process at any time.
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TIWARI, ABHIJEET. "SPATIO- TEMPORAL WATER QUALITY ASSESSMENT OF RIVER GANGA AT DIFFERENT LOCATIONS IN WEST BENGAL, INDIA THROUGH WQI AND SPI." Thesis, 2023. http://dspace.dtu.ac.in:8080/jspui/handle/repository/20078.
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An effort has been develop to access the water quality status of river Ganga in West Bengal India for drinking purpose using unified techniques. For this study, 14 parameters at 10 location from Beharampur to Diamond Harbour over 39 months (2020january —2023march) were considered. The eastern stretch of Ganga showed a variation of Water Quality Index (WQI) from 24.4539 to 1790.2545 and Synthetic Pollution Index (SPI) from 0.244539 to 1.7902545 in 36 months. . The map interpolated through GIS exposed that the entire river stretch in 36 months and location near to ocean during the entire period of 36 months were severely polluted (WQI >100 or SPI > 1).Turbidity ,DO and BOD concentration mainly contribute to the high scores of indices. Further, the origin of these ions was estimated through multivariate statistical techniques using SPSS .. It was recognized that the origin of these pollutant is mainly attributed to seawater influx, that of fluoride to human and industrial activities , and other parameters originated through geological as well as human activities. Based on the research, a few possible water treatment mechanisms are suggested to render the water fit for drinking.
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John, André. "Weiterentwicklung und Anwendung geostatistischer Simulationsverfahren zur unsicherheitsbasierten Modellierung von komplexen, sedimentartig ausgebildeten Lagerstätten." Doctoral thesis, 2014. https://tubaf.qucosa.de/id/qucosa%3A22953.
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Die immer komplexer werdenden geologischen Verhältnisse aktueller Lagerstätten, sowie die Umsetzung einer hoch-selektiven Rohstoffgewinnung, machen eine Modellierung auf Basis von geostatistischen Simulationsverfahren in einem modernen Lagerstättenmanagement notwendig, da diese Verfahren die in-situ Variabilität der struktur- und qualitätsbeschreibenden Lagerstättenparameter realistisch vorhersagen und damit auch realitätsnahe betriebswirtschaftliche Risikoabschätzungen zu den Auswirkungen der Unsicherheiten in der Vorhersage, aufgrund eines unvollständigen Kenntnisstandes, ermöglichen. Die Arbeit beschreibt die Weiterentwicklung und Anwendung von Verfahren der geostatistischen Simulation für die Modellierung komplexer, sedimentartig ausgebildeter Lagerstätten in einem praxisrelevanten Umfang und unter Berücksichtigung der besonderen Anforderungen, welche aus der Charakteristik der Lagerstätte und der Zielsetzung einer selektiven Rohstoffgewinnung abgeleitet wurden. Zunächst wird ein geeigneter Ansatz identifiziert, welcher die Grundlage für eine methodische Erweiterung und effiziente Implementierung, hinsichtlich der zu erfüllenden Anforderungen, bildet. Danach wird die komplette Prozesskette für eine zuverlässige Lagerstättenmodellierung untersucht und praktikable Modellierungsstrategien werden vorgestellt. Ein komplexes Anwendungsbeispiel aus dem Braunkohlenbergbau dient der Evaluierung der vorgestellten
Modellierungsverfahren.The more and more complex geological conditions of current deposits, as well as the implementation of a highly selective extraction of raw materials, require new approaches for the reservoir management. The use of geostatistical simulation methods for modelling the shape and quality of deposits is necessary, because these methods taking into account the natural variability of the deposit attributes and the resulting geological uncertainties. Furthermore this methods allow faithfully and realistic economic risk assessments on the impact of uncertainties in the prediction, due to an incomplete state of knowledge. This work describes the further development and application of geostatistical simulation algorithms for the modelling of complex sediment-like formed deposits in a practically scope, taking into account the special requirements, which are derived from the characteristics of such deposits and the objective of the selective extraction of raw material. First an appropriate simulation approach is identified, which then forms the basis for a methodical expansion and efficient implementation, in terms of fulfilling requirements. In addition, the complete process chain for reliable reservoir modelling is studied and a viable modelling strategy is presented. A complex application example from the lignite mining is used for evaluation of the presented modelling methods.
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Brosig, Andreas. "Skarn testing report: MAP002: D5.4." 2021. https://tubaf.qucosa.de/id/qucosa%3A74144.
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An assessment of tin-skarn resources in the Erzgebirge, Germany, was conducted with the 3-Part Method. For this purpose a Grade-Tonnage Model for this deposit type was established. A literature review produced grade and tonnage data for 23 skarn deposits, of which 9 are in the assessment area. Based on an existing predictive map created with an AI algorithm, seven permissive tracts with a total area of 776 km² were defined. To estimate the number of undiscovered deposits a panel of five experts in the economic geology of the Erzgebirge was assembled. From the expert estimates and the newly developed Grade-Tonnage Model the undiscovered ore and metal tonnages in each permissive tract were evaluated. In four of the seven tracts the probability of the existence of at least one undiscovered deposit is estimated to be greater than 50%, in permissive tract 2 it is even greater than 90%. In each of these tracts, the median assessed undiscovered ore tonnages are several million tons and the tin resources exceed 10,000 tons. For the most perspective tract (Permissive tract 2) the median estimates are 40.6 Million tons of ore with a tin content of 114,000 tons. For tungsten (tonnages calculated as WO3) the numbers are slightly lower.
The results verify the high resource potential of tin skarns in the Erzgebirge and can be used to guide future exploration activities to the most economically promising permissive tracts.
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Naworyta, Wojciech. "Gebirgskinematische Analyse unter Nutzung der räumlichen Statistik." Doctoral thesis, 2004. https://tubaf.qucosa.de/id/qucosa%3A22484.
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W pracy przedstawiono analize dokladnosci prognozowania ruchow powierzchni i gorotworu wywolanych podziemna eksploatacja gornicza. Przeanalizowano czynniki, ktore maja negatywny wplyw na dokladnosc prognozowania oraz analize pomierzonych elementow ruchu gorotworu. Metodami geostatystycznymi przeanalizowano dane pomiarowe z polskiego okregu wydobycia miedzi pod katem ich przestrzennej zmiennosci. Glowna czesc pracy stanowi zaproponowana przez autora metoda symulacji elementow ruchu powierzchni wywolanych podziemna eksploatacja gornicza. Z jej pomoca zbadano w jaki sposob oddzialuja na przebieg prognozowanych elementow ruchu powierzchni niepewnosci zalozenia parametrow eksploatacji i parametrow gorotworu. Zaproponowana metoda, ktora mozna badac proces osiadania w ujeciu dynamicznym, pozwala na obliczenie najbardziej prawdopodobnego przebiegu elementu ruchu powierzchni wraz z obszarem zaufania prognozy oraz prawdopodobieñstwem przekroczenia dowolnie zalozonej wartosci krytycznej.
Book chapters on the topic "IDW GEOSTATISTICS"
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Singh, Prafull, and Pradipika Verma. "A Comparative Study of Spatial Interpolation Technique (IDW and Kriging) for Determining Groundwater Quality." In GIS and Geostatistical Techniques for Groundwater Science, 43–56. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-815413-7.00005-5.
Full textConference papers on the topic "IDW GEOSTATISTICS"
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Papafotiou, A., R. Senger, A. Alcolea, G. W. Lanyon, and J. Ewing. "Modeling Approaches for Evaluating the Effects of Heterogeneity on Two-Phase Flow Associated With the Migration of Waste-Generated Gas From SF/HLW- and L/ILW Repositories in Low-Permeability Formations." In ASME 2011 14th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2011. http://dx.doi.org/10.1115/icem2011-59196.
Full textAbstract:
Different low-permeability formations are considered as potential host rocks for Low / Intermediate Level waste (L/ILW) and spent fuel / high-level / long-lived intermediate-level waste (SF/HLW/ILW) in Switzerland. As part of a generic site evaluation process, emphasis is on the assessment of Mesozoic limestones, marls and claystones in six potential siting areas in Northern and Central Switzerland. An important aspect in the site evaluation process is the characterization of the low-permeability formations in terms of spatial variability of the relevant transport properties (porosity, permeability, clay content), as they may affect the migration of waste-generated gas from L/ILW and SF/HLW/ILW repositories. Numerical modeling studies are presented, aimed at quantifying the impact of spatial variability of rock properties on gas release through the host rock on a deca- to hectometer scale. For this purpose, 2D models of an emplacement tunnel embedded in a low-permeability host rock are developed for both a sequence of limestones and marls with distinct lithological variability (Effingen Beds) and a claystone of moderate spatial variability (Opalinus Clay). For the Effingen Beds, a composite geological model is implemented, comprising stochastic representations of the different facies and the fracture systems. The facies model displays spatial variations in clay content, porosity and permeability within the different facies. The fracture model accounts for the hydraulic effects associated with the faults and fracture systems in the siting area under consideration. For the Opalinus Clay the available geostatistical information (experimental variograms of clay content, porosity, hydraulic conductivity) is used to generate a stochastic facies model based on a log-normal permeability distribution. A separate fracture network model is not established for the Opalinus Clay. A generic gas source-term is assigned to the emplacement tunnel and hydrostatic pressures are initially assumed for the host-rock domain. The comparison of the simulations with different permeability realizations indicates that the heterogeneity of the host rock introduces strong differences in the propagation of the gas pressure perturbation, resulting in significant variations in the lateral propagation of the gas front in the host rock and the gas pressure build-up in the emplacement tunnels. Despite these differences, the calculated peak pressures in the disposal cavern and gas breakthrough along the upper model boundary are similar for multiple realizations, which compare well with the simulated results for a homogeneous model with equivalent averaged properties.