Module Details

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title Signal Processing and Seismic Analysis
Code ENVS343
Coordinator Professor S De Angelis
Earth, Ocean and Ecological Sciences
Year CATS Level Semester CATS Value
Session 2022-23 Level 6 FHEQ First Semester 15


This module aims:

To provide an understanding of the theory and fundamental principles of signal processing;

To provide an understanding of the application of signal processing techniques to seismology;

To gain familiarity with state-of-the-art seismic processing workflows as applied in industry and earthquake monitoring.

Learning Outcomes

(LO1) To be able to apply signal processing techniques to problems in reflection, refraction and passive seismology.

(LO2) To identify problems in seismic processing, which can be solved by signal processing techniques and to evaluate the uncertainties in processed seismic data.

(LO3) To be able to use a computer-based seismic processing system and understand the fundamentals of a seismic processing work flow.

(LO4) To be able to develop signal processing routines in MATLAB and graphically communicate the results.

(LO5) To gain an understanding of the principle theory and routines of signal processing.

(S1) Problem solving skills

(S2) IT skills

(S3) Numeracy

(S4) Communication skills



The students will be introduced to the following Signal Processing techniques: Discrete Fourier Transformation (DFT), Properties of the Discrete Fourier transformation, Fast Fourier Transformation (FFT), Aliasing, Nyquist Theorem, Sampling Theorem, Convolution, Deconvolution, Spectra, Z-transform, Auto- and Cross-correlation, Time filtering including Butterworth filter and Wiener Filter, Frequency filtering, Introduction to methods of array seismology.

The practicals for this course will make use of the MATLAB signal processing language and examples of reall seismic traces will be used.

The students will be introduced to the fundamentals seismic interpretation including applications to conventional and unconventional energy sources.

In the practicals student will work on real world seismic data set and use the knowledge gained in the lectures to process the data.

Teaching and Learning Strategies

Teaching Method 1 - Lecture
Description: Topics are paired with practical sessions
Attendance Recorded: Yes

Teaching Method 2 - Laboratory Work
Description: Each laboratory session is paired with lectures
Attendance Recorded: Yes

The module is taught through a combination of lectures and computer-based practicals. The lectures will introduce students to the theory of seismic data processing and interpretation. The PC-based practical sessions will demonstrate the practical application of signal processing to real-world seismic datasets.

Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 20


Timetable (if known)              
Private Study 112


EXAM Duration Timing
% of
Penalty for late
Written exam, unseen, 2-hour duration. In presence. There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When):  120    50       
CONTINUOUS Duration Timing
% of
Penalty for late
Conference Poster This is an anonymous assessment.    50       

Recommended Texts

Reading lists are managed at Click here to access the reading lists for this module.