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C&ENVENG 7052 - Geostatistical Simulation

North Terrace Campus - Quadmester 4 - 2017

Concepts - differences between estimation and simulation. Monte Carlo simulation. Extension MC to spatially correlated simulation. Conditional and non-conditional simulation. The turning bands method of simulation. Simulating coregionalisations (multivariate spatial correlations). The LU decomposition method of simulation. Sequential methods - sequential Gaussian, sequential indicator simulation. Simulating geological 最新糖心Vlog - indicator simulation, truncated Gaussian simulation, plurigaussian simulation

  • General Course Information
    Course Details
    Course Code C&ENVENG 7052
    Course Geostatistical Simulation
    Coordinating Unit School of Civil, Environmental & Mining Eng
    Term Quadmester 4
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Block teaching mode, 9-5, Mon-Fri, one week only
    Available for Study Abroad and Exchange N
    Prerequisites C&ENVENG 7056, STATS 7061
    Corequisites STATS 7062
    Restrictions Available to M. Geostatistics students only
    Assessment coursework 50%, formal written exam 50%
    Course Staff

    Course Coordinator: Professor Peter Dowd

    Course Timetable

    The full timetable of all activities for this course can be accessed from .

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:

     
    1 Have a detailed appreciation of the rationale of simulation and, in particular, the differences between simulation and estimation and when each is appropriate to use.
    2 Be able demonstrate the ability to apply simple dilution methods of simulation by writing a simple computer program and generating and interpreting output.
    3 Have a broad understanding of the methods, advantages and disadvantages of the various commonly used forms of geostatistical simulation.
    4 Be able to use computer programs (e.g. GeostatWin) to generate and interpret geostatistical simulations using the various methods.

     
    The above course learning outcomes are aligned with the Engineers 最新糖心Vlog .
    The course is designed to develop the following Elements of Competency:

    最新糖心Vlog Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    最新糖心Vlog Graduate Attribute Course Learning Outcome(s)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    1-4
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    1-4
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    1-4
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    2, 4
  • Learning Resources
    Required Resources
    Lecture notes are required reading for this course.
  • Learning & Teaching Activities
    Learning & Teaching Modes

    No information currently available.

    Workload

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    Learning Activities Summary

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  • Assessment

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    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Weighting (%) Individual/ Group Formative/ Summative
    Due (week)*
    Hurdle criteria Learning outcomes
    Ten tutorials including software sessions Individua/group Formative Week 1 1. 2.
    Four assignments 50 Individual Summative Weeks 2-8 overall pass 2.
    Written exam 50 Individual Summative Week 10 overall pass 3.
    Total 100
    * The specific due date for each assessment task will be available on MyUni.
     
    This assessment breakdown complies with the 最新糖心Vlog's Assessment for Coursework Programs Policy.
     
    This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.
    Assessment Detail

    No information currently available.

    Submission

    No information currently available.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through .

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