Course Objectives:

This course is designed to provide participants with a thorough understanding of advanced seismic data acquisition and processing techniques. Participants will gain insights into the latest technologies, methods, and best practices used in seismic surveying, from data acquisition through to post-processing and interpretation. The focus will be on handling complex seismic data, optimizing acquisition workflows, and improving the quality of subsurface imaging. By the end of the course, participants will be able to apply advanced processing techniques to enhance seismic imaging and interpretation for improved decision-making in exploration and development.

1. Introduction to Seismic Data Acquisition and Processing

• Understand the basic principles of seismic data acquisition, including reflection seismology, seismic waves, and the role of source-receiver geometry.
• Overview of the seismic data workflow, from data acquisition, pre-processing, post-processing, to interpretation.
• Study the importance of seismic surveys in hydrocarbon exploration, reservoir characterization, and field development planning.

2. Advanced Seismic Data Acquisition Techniques

• 3D and 4D Seismic Surveys: Explore how 3D seismic acquisition enables high-resolution subsurface imaging, and how 4D (time-lapse) seismic is used for monitoring reservoir changes over time.
• Wide-Angle and Full-Azimuth Acquisition: Learn the techniques used in wide-angle seismic surveys for imaging deeper targets and full-azimuth surveys to improve the illumination and resolution of complex subsurface structures.
• Ocean Bottom Seismic (OBS) and Land Seismic Acquisition: Study the differences and considerations in offshore and onshore seismic data acquisition, including marine acquisition systems, ocean-bottom nodes, and land-based equipment.
• Seismic Source Technology: Review seismic source types (e.g., explosives, vibroseis, airguns) and their impact on data quality and resolution.
• Noise Reduction Techniques: Study advanced methods of noise attenuation and signal enhancement to improve data quality in challenging environments, including techniques for handling cultural noise and ambient noise.

3. Seismic Data Pre-Processing

• Data Conditioning: Learn advanced techniques in data conditioning, such as deconvolution, filtering, and detrending, to remove unwanted noise and enhance signal quality.
• Statistical and Geostatistical Methods: Understand how to apply geostatistics to seismic data for improved quality control and noise identification in data sets.
• Velocity Model Building: Learn the process of building velocity models to correct seismic travel times and improve depth conversion accuracy.
• Static and Dynamic Correction: Study the application of statics and dynamics corrections, including topography, weathering layer corrections, and refraction statics.

4. Advanced Seismic Data Processing

• Pre-Stack and Post-Stack Processing: Understand the differences between pre-stack (raw data) and post-stack (migrated data) processing techniques and when to apply each for optimal imaging.
• Seismic Migration Techniques: Learn about migration methods (e.g., time migration, depth migration, Kirchhoff migration, and beam migration) for improving seismic imaging resolution, especially in complex geological settings.
• Seismic Inversion: Study advanced seismic inversion techniques, including post-stack inversion, pre-stack inversion, and full-waveform inversion (FWI), to convert seismic data into quantitative subsurface models.
• Amplitude Versus Offset (AVO): Learn how to use AVO analysis to detect fluid content, porosity, and lithology by analyzing variations in seismic amplitude with offset distance.
• Seismic Attributes: Understand the use of seismic attributes such as instantaneous frequency, instantaneous phase, spectral decomposition, and semblance analysis to reveal hidden geological features.

5. Integration of Seismic with Other Geophysical Data

• Learn the methods for integrating seismic data with well logs, core data, and geological interpretations to produce a more comprehensive subsurface model.
• Explore the use of seismic inversion in combination with petrophysical data for improved reservoir characterization and fluid prediction.
• Study the integration of seismic data with electromagnetic surveys, gravity surveys, and magnetic data to enhance subsurface imaging and interpretation.

6. Advanced Seismic Imaging for Complex Reservoirs

• Imaging in Complex Geologies: Understand the challenges of imaging in salt bodies, subsalt structures, and deepwater environments, and how advanced techniques like reverse time migration (RTM) are applied.
• Subsurface Fractures and Fault Imaging: Learn how seismic data can be used to detect fractures, faults, and bedding planes in the subsurface, and how to account for these structures in seismic interpretation.
• Poroelastic and Anelastic Seismic Processing: Study advanced models for porosity, elastic properties, and anisotropy and how they impact seismic wave propagation in tight formations.

7. Seismic Data Interpretation and Modeling

• Geological Interpretation: Learn advanced techniques in interpreting seismic data to define structural features (e.g., faults, anticlines, salt domes) and stratigraphic traps.
• Reservoir Characterization: Study how to use seismic data for detailed reservoir modeling, including pore pressure analysis, stress distribution, and porosity mapping.
• Time-Lapse (4D) Seismic Interpretation: Explore how to use 4D seismic data to track changes in the reservoir over time, particularly in monitoring fluid migration, production effects, and reservoir compaction.

8. Seismic Data Quality Control and Quality Assurance

• Understand the processes for quality control (QC) of seismic data, including data validation, error detection, and performance monitoring during both acquisition and processing stages.
• Study how to use automated QC tools and real-time data processing to identify issues early in the seismic data workflow.
• Learn how to apply best practices to ensure consistent data accuracy, reliability, and repeatability throughout the seismic acquisition and processing chain.

9. Seismic Data Visualization and Reporting

• Learn how to visualize seismic data and results using advanced visualization software (e.g., 3D visualization, virtual reality (VR)).
• Explore reporting techniques for communicating seismic data interpretation, results, and findings clearly to both technical and non-technical stakeholders.
• Study visualization tools for presenting subsurface models, seismic sections, and attribute maps to improve decision-making in exploration and field development.

10. Future Trends and Technologies in Seismic Data Acquisition and Processing

• Explore emerging technologies in seismic acquisition such as distributed acoustic sensing (DAS), fiber-optic sensing, and robotic seismic systems.
• Study the future of data processing with the integration of artificial intelligence (AI), machine learning (ML), and big data analytics in seismic interpretation and model generation.
• Understand the implications of cloud computing and high-performance computing (HPC) on seismic data processing workflows and the ability to process large-scale seismic datasets in real-time.

Target Audience

This course is designed for professionals involved in seismic data acquisition, processing, and interpretation in the oil and gas industry. The target audience includes:

• Seismic Acquisition Engineers
• Seismic Data Processors
• Geophysicists
• Reservoir Engineers
• Geologists
• Exploration Managers
• Subsurface Modelers