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Curricular information is subject to change
On completion of this module, students should be able to:
1. Understand the link between measured geophysical fields and geological units
2. Describe the variations of the geophysical response of geological units under different primary fields
3. Understand the concept of non-invasive subsurface visualization (3D) over time (4D)
4. Characterize the relation between data resolution, survey design, and signal to noise ratio
5. Reflect, describe, and apply geophysics to solve geological, environmental, and societal problems
6. Analyze ambiguity in data interpretation (the interplay between frequency content, depth of signal, size of the body, and intensity of physical properties)
Lecture 1: Exploring patterns in geophysical data
Main applications of geophysical methods. Forward and inverse modeling and the connection between geology and geophysical anomalies. Basic elements of a geophysical experiment. Qualitative and quantitative interpretation.
Lecture 2: Physical properties of rocks
Elements that influence physical properties (composition, geometry, interfaces, thermodynamic condition). Variations of electrical conductivity, electrical polarization, magnetism, velocity and density with variations in texture, grain size and composition. Bowen's series and physical properties. Properties of different rock types.
Lecture 3: Magnetic and gravity methods
Active and passive geophysical methods. Gravitational force and magnetism and the connection with density and magnetic susceptibility of rocks, respectively. From point mass and single loop theory to 3D practical applications. Equipment and data acquisition. Data reduction and processing. Line spacing and anomaly detection. Main principles of data interpretation.
Lecture 4: Electrical, electromagnetic, and radiometric methods
Meaning of Maxwell equations and connection with the electrical conductivity of rocks. Equipment and data acquisition. Data reduction and processing. Line spacing and anomaly detection. Main principles of data interpretation.
Lecture 5: Data interpretation and integration
Meaning and methods of data integration. Knowledge and data driven methods. Case studies. The UN sustainable development goals (SDGs) to transform our world and how geosciences can help. Case study on Equality, Diversity and Inclusion in geosciences.
| Student Effort Type | Hours |
|---|---|
| Lectures | 10 |
| Practical | 15 |
| Autonomous Student Learning | 25 |
| Total | 50 |
Not applicable to this module.
| Description | Timing | Component Scale | % of Final Grade | ||
|---|---|---|---|---|---|
| Multiple Choice Questionnaire (Short): Short quizzes | Throughout the Trimester | n/a | Standard conversion grade scale 40% | No | 20 |
| Continuous Assessment: Assessment of practical coursework throughout the trimester | Throughout the Trimester | n/a | Standard conversion grade scale 40% | No | 50 |
| Examination: A written examination | Unspecified | No | Standard conversion grade scale 40% | No | 30 |
| Resit In | Terminal Exam |
|---|---|
| Summer | Yes - 1 Hour |
• Feedback individually to students, post-assessment
• Peer review activities
Not yet recorded.