
Discover how geophysics supports oil and gas exploration using seismic data, gravity, and geophysical tools. Learn the seismic reflection approach and the three stages: data acquisition, processing, and interpretation.
Explore seismic method stages of acquisition, where energy reflects at interfaces with different velocity or density, enabling offshore and onshore surveys using hydrophones, geophones, air guns.
Process seismic data at a processing center to improve signal-to-noise ratio and remove acquisition-related abnormalities, applying a sequence of multiplexing, amplitude recovery, trace editing, statics, and migration.
Correlate horizons across lines using wind and seismic data, generate horizon maps with a workstation, convert time to depths with velocity maps, and interpret rock shapes to locate drilling targets.
Learn onshore seismic data acquisition, land geometries and shot–receiver layouts with overlapping subsurface coverage, and apply noise analysis, array design, and static corrections to improve data quality.
Learn offshore seismic data acquisition aboard a vessel deploying streamers and hydrophones, using air guns as sources, with depth-controlled active streamer sections and multi-line, multi-source configurations.
Explore seismic noise analysis and wave propagation, covering body and surface waves like the Ryley wave and Love wave. Analyze acoustic impedance, reflection coefficients, and primary and multiple reflections.
Learn the basics of seismic reflection theory, including surface and body waves, p-waves, and s-waves. Understand how reflections and transmissions occur at interfaces, governed by acoustic impedance and reflection coefficients.
Learn seismic data processing by understanding resolution and limitations, including vertical resolution of one quarter wavelength, resolvable limit, and lateral resolution near one wavelength.
Examine how the cosine function models periodic motion in seismic data, defining the period, frequency, and wavelength, and relate displacement in an isolated oscillator to the cosine wave.
Explore sampling in time and space, define sample rate, and demonstrate aliasing and Nyquist, stressing anti-aliasing filters and seismic data sampling concepts.
Explore digitisation and sampling of seismic data in time and space. See how analog-to-digital conversion, increased dynamic range, and multiplexed traces enable digital recording and seismic data processing.
Explore digital functions in seismic data processing, focusing on convolution, cross-correlation, and auto-correlation. Learn how a seismic trace is convolved with an operator, and how time-reversed cross-correlation relates to auto-correlation.
Analyze time and frequency domains in seismic data by introducing the impulse (delta) function and Fourier transform, showing how time-domain signals convert to amplitude and phase spectra with reversible transformations.
Explore seismic data processing essentials, including improving signal-to-noise ratio, applying geometric corrections, filtering, data transformation, and migration to locate signals accurately across onshore, offshore, and varied environments.
Analyze how seismic data processing converts analog signals to digital form through sampling and multiplication, then uses multiplexing and resampling with interpolation and decimation to align data across systems.
Explore precise vibroseis correlation by matching the pilot sweep with recorded data to reveal earth reflections and produce a clear seismograph from correlated signals.
Learn editing and muting in seismic data to remove reverse polarity, spikes, and ground noise, boosting the signal-to-noise ratio. Use difference verification to keep true signals intact.
True amplitude recovery in seismic data processing compensates for attenuation and spherical divergence. The lecture explains removing abnormalities not related to rock properties and applying scaling to reveal true reflections.
Explore deconvolution in seismic data processing. Use inverse filtering to restore high frequency content and attenuate distortions caused by the medium.
Explore static corrections in seismic data processing, defining them as time-invariant shifts that remove near-surface effects like elevation and weathering to align traces and improve reflection continuity.
explains dynamic correction in seismic data processing, detailing velocity types, normal moveout, and how velocity analysis informs stacking and data flatness.
Learn to apply multi-channel filtering in the F-k domain to separate low-velocity noise from seismic signals, demonstrating how conversion enables noise removal while noting potential signal overlap.
Learn the basics of seismic data processing for multiple attenuation, distinguishing primaries from multiples, and applying time- and frequency-domain methods, velocity-based separation, and subtraction to reveal subsurface structure.
This lecture explains applying dmo for deep events and performing 3d migration to relocate reflections, reduce energy loss, and preserve dips for accurate drilling planning.
Identify and resolve seismic data processing problems by selecting an optimal processing sequence, including stacking, velocity analysis, and deconvolution. Apply residual static correction, multiple attenuation, and migration to improve interpretation.
Seismic data is recorded in the field on magnetic tape. About three to six weeks later, the information is transmitted to the interpreter as a seismic section.
All of the intervening steps comprise the data processing phase of seismic exploration.
Processing seismic data consists of applying a sequence of computer programs, each designed to achieve one step along the path from field tape to record section. Programs are usually used in a processing sequence, and these are selected from a library of several hundred programs. Each company’s library is unique, although many programs will be almost identical to those of another company.
In each company’s library, there may be several programs designed to produce the same effect through different approaches. For example, one program may operate in the time domain while another works in the frequency domain, yet they may yield similar results.
The course also covers seismic waves propagation & seismic records data digitalization, sampling and how to avoid aliasing in the recorded data and during resampling in order to ensure optimum data quality. The mathematics of seismic data processing will be followed by the fundamentals of seismic data processing. An overview of the best practices and the most recent seismic 2D and 3D seismic processing sequences used onshore and offshore will be provided. The participants will then learn the theoretical biases of the most important terms of seismic processing: the Fourier transform, time and frequency domain, convolution, cross and auto-correlations. The participants will then learn how to build an optimum processing sequence, in order to obtain the best data quality using the latest techniques.