Seismic Attributes and Their Applications in Seismic Interpretation
|Dr Behzad Alaei (Earth Science Analytics, Bergen, Norway)|
|Geophysics –Integrated Geophysics|
|English, Norwegian, Persian|
|5 CPD points|
DECOMPOSITION FAULTS INTEGRATION NOISE WORKFLOWS
Seismic attributes have been increasingly used in both exploration and reservoir characterization and has been integrated in the seismic interpretation process. Seismic attribute analysis can extract information from seismic data that is otherwise hidden and have been used to identify prospects, ascertain depositional environments (e.g. fluvial or deep water channels, carbonate buildups), detect and enhance faults and fracture sets to unravel structural history, and even provide direct hydrocarbon indicators. They have proven to be useful in different geological settings such as clastic, carbonate, and salt related basins as well as different tectonic regimes including extensional, strike-slip, and compressional. Developments in digital recording and modern visualization techniques had great impact on the growth of seismic attributes in the past decades. The purpose of this course is to introduce seismic attributes with their applications in seismic interpretation using examples from different sedimentary basins and also through certain attribute workflows. It is aimed to provide geoscientists with the minimum required theory of how each attribute is generated, with a greater emphasis on the application in the exploration and reservoir characterization.
The course is divided into two parts: attributes review/applications and workflows. The first part starts with a review of seismic attributes and discusses the noise (random and coherent) reduction as one essential step of all attribute studies. The number of seismic attributes has recently increased dramatically causing confusion for geoscientists to select appropriate ones. In this course, trace-based attributes, volumetric dip and azimuth, fault detection and enhancement attributes, volumetric curvature, and frequency decomposition are presented using examples from different geological settings. Frequency decomposition is briefly presented with different decomposition methods such as wavelet transform, Fourier transform and matching pursuit analysis. Examples illustrate the interpretation challenges associated with frequency decomposition data interpretation. The concept of multi-attributes and geobody extraction is introduced at the end of the first part of the course with examples on combinations of amplitude, phase, discontinuity and frequency attributes to visualize different geological objects.
In the second part of the course stratigraphic and structural workflows are presented. The workflows (and the elements for their planning) aim to show the integration of several attributes for specific interpretation purposes, with examples of stratigraphic (fluvial/shallow marine clastic systems, attribute expressions of deep water turbidites and carbonate settings) and structural imaging workflows. Lastly, the course analyses the importance of the integration of seismic attribute analysis processes with the other seismic interpretation (qualitative or quantitative) workflows.
Upon completion, participants will be familiar with a range of relevant attributes used in seismic exploration and reservoir characterization. They will know the basics of how those attributes were calculated and will gain understanding of their applications in seismic interpretation. They will be able to plan some attribute workflows and they will know how to integrate attribute analysis with other disciplines of qualitative/quantitative seismic interpretation.
Part I: Seismic Attributes
- Definition and historical review
- Structure of the short course
- Input data cleaning:
- Noise reduction applications with examples
- Workflow oriented noise removal process
- Focus on structurally oriented edge preserving methods to remove noise
- Mean and median filters for noise removal
- Trace-based attributes:
- Complex trace analysis and the elementary attributes of envelope (reflection strength), instantaneous phase, instantaneous frequency, and cosine of phase attributes
- Simple examples with interpretation applications
- Dip and Azimuth volumes:
- Quantitative estimate of dip and azimuth through seismic volumes to map morphology of seismic texture
- Introduction and theory
- Dip and Azimuth calculation methods including:
- Calculating temporal and spatial derivatives of the phase estimated using complex trace analysis
- Explicit dip scan to find the most coherent reflector
- Gradient structure tensor
- Examples with applications for both structural and stratigraphic interpretation aspects.
5. Coherence (Measurements of the similarity of seismic waveform)
- Different approaches including:
- Cross correlation
- Gradient structure Tensor-based coherence
- Role of dip and azimuth steering volumes on coherence calculation
- Several examples and interpretation criteria
6. Fault attributes, attribute enhancement approaches:
- Identify objects representing faults from background noise.
- Apply filters to enhance already detected faults from background noise.
- Plan different filter sizes to enhance faults with different scales (regional to small scale).
7. Curvature attribute:
- Definition and background theory
- Surface and volume curvature measurements
- Interpretation applications using some examples
8. Frequency decomposition:
- Introduction and mathematics of spectral decomposition using graphic illustrations
- Review of decomposition methods:
- DFT (discrete Fourier transform)
- CWT (continuous wavelet transform)
- MPD (matching pursuit decomposition)
- Examples and applications in layer thickness estimation, stratigraphic variations (seismic facies) and Direct Hydrocarbon detection
- Non-uniqueness will be addressed together with resultant challenges in interpretation of frequency decomposed data
9. Multi attributes, geobody extraction, and iso proportional slicing:
- Some attribute blending methods such as RGB blending, and opacity blending
- Geological object identification
- Machine learning examples of multi attributes
- Selection of appropriate attributes
- Quantitative extraction of certain attribute volumes
- Iso proportional slicing as an important interpretation tool
Part II: Workflows
- Seismic attribute analysis workflow planning:
- Stratigraphic, structural, reservoir characterization
- Factors controlling the seismic attribute workflow planning
- Workflow examples: fault imaging, carbonate imaging
- Integration of attribute analysis with other disciplines of seismic interpretation
The course addresses geoscientists involved in exploration and production projects where seismic studies play a role and who wish to learn the basic theory of the main seismic attributes used in exploration and production, as well as their applications and how to integrate them in exploration and reservoir characterization studies.
Participants should have knowledge of seismic interpretation. Mathematical concepts of attributes are presented with minimum required equations and graphic illustrations. Some basic knowledge of seismic exploration may help.
About the instructor
Dr. Behzad Alaei is geophysicist and co-founder of Earth Science Analytics AS. He has PhD in exploration seismology from University of Bergen, Norway. He has 25 years of industry and research experience focused on seismic exploration, forward modelling of complex structures, seismic imaging, seismic attributes, and machine learning applications in geoscience. He carried out several seismic attribute studies over different sedimentary basins from Asia to Norwegian continental shelf and Gulf of Mexico. In the recent years, he has been involved in the integration of seismic fault attributes with structural geological investigations of faults as well as development of machine learning techniques in geoscience.
He is a member of EAGE, SEG, and CSEG.
Explore other courses under this discipline:
Instructor: Dr Dave L. Cantrell (Cantrell GeoLogic and Stanford University, USA)
Reservoir quality prediction has long been the ultimate goal of industry geologists, yet few have achieved this in a truly quantitative fashion. This workshop presents a new approach to reservoir quality prediction that involves the integration of a variety of modeling techniques to understand, quantify and predict the geological processes that control reservoir quality. Since initial reservoir quality is established at the time of deposition, numerical process models are used to predict initial reservoir quality; diagenetic process models are then used to modify these initial results and ultimately produce a quantitative and geologically-based prediction of present-day subsurface reservoir quality.
Instructors: Prof. Dr Stephen Tyson and Dr Ing Sebastian Hörning (Universiti Teknologi Brunei and The University of Queensland)
The course will show the attendees how to test for linear spatial dependence and introduce the concepts of non-linear geostatistics. Attendees will develop an excel spreadsheet and a python notebook which can be used for spatial data analysis and non-linear stochastic simulation. Existing geostatistics algorithms based on the kriging matrix can be shown to underestimate the connectivity of extreme values because they assume a linear spatial dependence model. Moreover, the estimation of uncertainty based on these techniques uses the kriging variance, which is not dependent on the values of the spatially distributed variable. It can also be shown that these uncertainty estimate are often implausible. This course will explain the reasons why most spatial variables in geoscience do not have a linear spatial dependence, even after monotonic transformations, and what the impact of this in the estimation of petrophysical properties. The course will show the attendees how to test for linear spatial dependence and introduce the concepts of non-linear geostatistics. Attendees will develop an Excel spreadsheet and a python notebook which can be used for spatial data analysis and non-linear stochastic simulation.
Instructor: Dr Bjorn Wygrala (Schlumberger)
The term “Petroleum Systems” and the technology “Basin and Petroleum Systems Modelling” will be introduced by showing applications in areas with critical exploration challenges, including salt basins and thrustbelts. Technical breakthroughs in the last 10-15 years have been the extension of the technology from 2D to 3D, and the ability to perform multi-phase petroleum migration modelling using different methods in high resolution geological models. This enables temperature, pressure and petroleum property predictions to be made with higher levels of accuracy and in the most complex geological environments such as in the sub-salt or in thrustbelts. Case studies will be used with live software presentations to illustrate key points. Applications of the technology will range from frontier exploration in which large areas with only sparse data are screened, to detailed assessments of exploration risks in structurally complex areas, to petroleum resource assessments of yet-to-find oil and gas.
Instructor: Prof. Dr Michael Poppelreiter (University Technology Petronas)
The most universal, comprehensive and concise descriptive documents on oil and gas wells are well logs. They impact the work of almost every oil field group from geologists to roustabouts to bankers. Familiarity with the applications of well logs is therefore essential for people forging their careers in the oil business. The instructor uses a core-based approach to help participants develop a good grounding in understanding and applying well logging techniques. General principles of physics are presented to explain the functioning of modern logging tools. Wherever possible, the physics of logging measurements is related to everyday tools and applications. Cross-plotting and reconnaissance techniques quickly and efficiently discriminate between water, oil and gas. Error minimization techniques, applicable only to computerized log analysis, produce optimal results. Participants benefit from realistic experience by working in teams on a comprehensive log interpretation exercise.
Instructor: Prof. Dr Richard Swarbrick (Swarbrick GeoPressure Consultancy)
All wells drilled require a pre-drill prediction of pore fluid and fracture pressures which defines the drilling window. This course explains the objectives, methods and uncertainties of prediction, based on extensive global experience. The necessary understanding of the geological/geophysical context of abnormal pressures leading to standard algorithms will be provided. Part of the challenge is terminology and contrasting display methods of geoscience and operations/drilling groups. Both approaches are necessary and investigated in the interactive exercises which will form an essential component of the course.
Instructor: Dr Dirk Nieuwland (NewTec International)
Unconventional hydrocarbon systems require unconventional approaches to decide on drilling locations and development techniques. The information contained in natural fracture systems can be used to support the drilling and well stimulation technique for the development of unconventional hydrocarbon systems such as shale gas. This short course is based on geomechanics as a technique that can be used to understand and to develop unconventional hydrocarbon systems such as shale gas systems, and fractured crystalline basement, where conventional logging and seismic systems are inadequate.
Instructor: Dr Tim Wynn (AGR-Petroleum Services)
Reservoir modelling for field development planning is a well-accepted process but its application to fractured reservoirs requires specific considerations which are less commonly known. This course describes a practical methodology for building 3D static (“geocellular”) reservoir models for naturally fractured reservoirs using standard modelling software, covering such considerations. The issues addressed include the integration of log, core and seismic data, the sourcing and application of in situ stress data, the process of defining and building the static reservoir model itself, and the creation of output in a form appropriate for dynamic modelling using dual porosity reservoir simulators where appropriate. More complex workflows using discrete fracture networks will also be summarised, as will general issues of fracture description, uncertainty-handling and volumetrics.
Instructor: Prof. Dorrik Stow (Heriot-Watt University)
Sandstones deposited in deep marine environments form important hydrocarbon reservoirs in many basins around the world. Interbedded mudstones can be important as source rocks, as well as acting as barriers, baffles and seals. Deepwater reservoirs are currently the principal target for oil and gas exploration, with over 1600 existing turbidite fields and plays.