Master of science-level of the Bologna process in Petroleum And Mining Engineering (Ingegneria Del Petrolio E Mineraria) - Torino Master of science-level of the Bologna process in Ingegneria Per L'Ambiente E Il Territorio - Torino
The aim of the course is to develop basic understanding of spatially referenced data analysis and to explore the potential of Geographic Information Systems application in environmental studies. The course builds up on the practical skills in geospatial data mining and mapping. It offers detailed discussion on a wide range of geospatial data visualization methods and introduces quantitative analysis of geospatial phenomena.
The course aims at providing both a theoretical understanding and a practical introduction to the use of GIS techniques. Applications concern different environmental aspects addressing cartographic, hydrologic and petroleum issues.
Educational Approach: developing the theoretical concepts, the educational approach is based on class presentations while the lab activities include computer-assisted in-class exercises and team projects. Students' extensive individual work is required.
The aim of the course is to develop basic understanding of spatially referenced data analysis and to explore the potential of Geographic Information Systems application in environmental studies. The course builds up on the practical skills in geospatial data mining and mapping. It offers detailed discussion on a wide range of geospatial data visualization methods and introduces quantitative analysis of geospatial phenomena.
The course aims at providing both a theoretical understanding and a practical introduction to the use of GIS techniques. Applications concern different environmental aspects addressing cartographic, hydrologic and petroleum issues.
Educational Approach: developing the theoretical concepts, the educational approach is based on class presentations while the lab activities include computer-assisted in-class exercises and team projects. Students' extensive individual work is required.
In this course, the students will learn:
• Basic concepts about geostatistics, spatial analysis, correlation and probability estimation
• Interpolation methods and filtering techniques
• Extraction of geometrical surface parameters (slope, aspect, contour lines, curvature, …) and visibility analysis (line of sight, observer point, visibility, …)
After attending the course, students will be able to:
• describe and characterize one sample with the main statistical parameters
• estimate correlation between variables or parameters
• use the appropriate interpolation method depending on the problem considered
• apply different filtering techniques
• make a effective presentation of final result in GIS environment using 2D/3D layout and views.
The lab activities deal with the environmental spatial analysis using hydraulic/hydrologic and petroleum data.
In this course, the students will learn:
• Basic concepts about geostatistics, spatial analysis, correlation and probability estimation
• Interpolation methods and filtering techniques
• Extraction of geometrical surface parameters (slope, aspect, contour lines, curvature, …) and visibility analysis (line of sight, observer point, visibility, …)
After attending the course, students will be able to:
• describe and characterize one sample with the main statistical parameters
• estimate correlation between variables or parameters
• use the appropriate interpolation method depending on the problem considered
• apply different filtering techniques
• make a effective presentation of final result in GIS environment using 2D/3D layout and views.
The lab activities deal with the environmental spatial analysis using hydraulic/hydrologic and petroleum data.
Pre-requisites are basic knowledge of geological and hydrogeological concepts, computing and geospatial data acquisition and visualization techniques.
Pre-requisites are basic knowledge of geological and hydrogeological concepts, computing and geospatial data acquisition and visualization techniques.
The program is divided into 5 modules of lectures, for a total duration of 60 hours, and a series of practical exercises to be performed at both the LAIB and the Laboratory of Photogrammetry, Geomatics and GIS at the DIATI.
DELIVERY MODES
Lessons (about 30 h)
Module 1: Basic concepts of theory of observations
Definitions of basic concepts on measurement and estimation of a random 1D/2D variable, mean, median, standard deviation, probability density function (PDF), cumulative density function (CDF). In this module, some aspects about the measurement of real objects and statistical interpretation are considered. Moreover, it will focused the attention on correlation, accuracy and precision concepts.
Module 2: GIS/database Design procedure:
The modelling procedure, external model, conceptual model (Entity/Relationship), logical model (Relational DB), internal model, cardinality, basic rules for data modelling (complex attributes, multi-values fields), 3D GIS support and visualization
Module 3: The interpolation/approximation methods
The interpolation methods play a crucial role in environmental spatial analysis. Different interpolation techniques such as IDW, correlogram, variogram, different Kriging (simple, universal, linear, co-Kriging) methods will be deeply analyzed and considered, focusing the attention on different kinds of applications especially related to petroleum and hydrological activities. The linear regression as interpolation method applied to different data
Module 4: Digital Terrain model and digital Surface model
Definition of DTM and DSM, contents (point cloud, breaklines, dead zone, …), dense model, irregular (TIN) and regular grids, estimation of surface parameters (slope, aspect, contour lines, curvature,…), visibility analysis (line of sight, skyline, viewshade, observer, …)
Module 5: Filtering, model building and inversion techniques.
In this module, different filtering techniques (e.g. low-pass/high pass filter) and inverse problems will be considered, especially considering hydraulic and petroleum applications.
During geological modelling is frequent the use of filtering techniques on well log data in order to identify characteristics of the log electrical signals, improve stratigraphic correlation or remove unwanted parts of the registration. On 2D or 3D datasets (e.g. maps, distributed petrophysical values) filters can be applied in order to identify the contribution of each spatial component of a given property, remove/enhance property features or calculate trends used during petrophysical distribution. During the lesson different filtering techniques are going to be presented and analyzed that are commonly used during well data analysis and 3D geological modelling.
Lab activities (about 30 h)
The lab activities take about half of the course and are focused on themes considered during the lessons. Specific applications will be done using GIS software especially for geospatial analysis, focusing on analysis tools, 3D data, working with rasters, projections, and environment variables.
The works are carried out in team; finally, a special report must be completed.
The program is divided into 5 modules of lectures, for a total duration of 60 hours, and a series of practical exercises to be performed at both the LAIB and the Laboratory of Photogrammetry, Geomatics and GIS at the DIATI.
DELIVERY MODES
Lessons (about 30 h)
Module 1: Basic concepts of theory of observations
Definitions of basic concepts on measurement and estimation of a random 1D/2D variable, mean, median, standard deviation, probability density function (PDF), cumulative density function (CDF). In this module, some aspects about the measurement of real objects and statistical interpretation are considered. Moreover, it will focused the attention on correlation, accuracy and precision concepts.
Module 2: GIS/database Design procedure:
The modelling procedure, external model, conceptual model (Entity/Relationship), logical model (Relational DB), internal model, cardinality, basic rules for data modelling (complex attributes, multi-values fields), 3D GIS support and visualization
Module 3: The interpolation/approximation methods
The interpolation methods play a crucial role in environmental spatial analysis. Different interpolation techniques such as IDW, correlogram, variogram, different Kriging (simple, universal, linear, co-Kriging) methods will be deeply analyzed and considered, focusing the attention on different kinds of applications especially related to petroleum and hydrological activities. The linear regression as interpolation method applied to different data
Module 4: Digital Terrain model and digital Surface model
Definition of DTM and DSM, contents (point cloud, breaklines, dead zone, …), dense model, irregular (TIN) and regular grids, estimation of surface parameters (slope, aspect, contour lines, curvature,…), visibility analysis (line of sight, skyline, viewshade, observer, …)
Module 5: Filtering, model building and inversion techniques.
In this module, different filtering techniques (e.g. low-pass/high pass filter) and inverse problems will be considered, especially considering hydraulic and petroleum applications.
During geological modelling is frequent the use of filtering techniques on well log data in order to identify characteristics of the log electrical signals, improve stratigraphic correlation or remove unwanted parts of the registration. On 2D or 3D datasets (e.g. maps, distributed petrophysical values) filters can be applied in order to identify the contribution of each spatial component of a given property, remove/enhance property features or calculate trends used during petrophysical distribution. During the lesson different filtering techniques are going to be presented and analyzed that are commonly used during well data analysis and 3D geological modelling.
Lab activities (about 30 h)
The lab activities take about half of the course and are focused on themes considered during the lessons. Specific applications will be done using GIS software especially for geospatial analysis, focusing on analysis tools, 3D data, working with rasters, projections, and environment variables.
The works are carried out in team; finally, a special report must be completed.
The main text consists of the lecture notes provided by the teacher and slides presented during the classes.
The main text consists of the lecture notes provided by the teacher and slides presented during the classes.
Modalità di esame: Prova orale obbligatoria; Elaborato scritto prodotto in gruppo;
Exam: Compulsory oral exam; Group essay;
...
The exam consists of 3 parts:
1. a discussion of exercises on the entire process of environmental spatial analysis with theoretical subjects and DTM/DSM application (vote/30)
2. a discussion of exercises on hydraulic problems made during practical activities (vote/30)
3. a discussion of exercises on petroleum engineering made during practical activities (vote/30).
The final grade is a weighted average of the results of the 3 previous evaluations with weights: P1=0.50, P2 =0.25, P3=0.25.
Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam: Compulsory oral exam; Group essay;
The exam consists of 3 parts:
1. a discussion of exercises on the entire process of environmental spatial analysis with theoretical subjects and DTM/DSM application (vote/30)
2. a discussion of exercises on hydraulic problems made during practical activities (vote/30)
3. a discussion of exercises on petroleum engineering made during practical activities (vote/30).
The final grade is a weighted average of the results of the 3 previous evaluations with weights: P1=0.50, P2 =0.25, P3=0.25.
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.