Geophysics Courses

The overall objective is to introduce to entry level geophysicists, seismic interpreters and geologists, petrophysicists, and reservoir engineers the key concepts and principles of seismic data acquisition, seismic data processing and seismic interpretation, that form the technical basis for value added seismic applications in exploration, field appraisal and reservoir management. Emphasis is on the fundamental and practical understanding of the technical requirements for extraction of geophysical, geological and rock property information. Data examples and exercises are used to illustrate key concepts, practical issues and pitfalls as they affect seismic data quality and interpretation. The course starts with an introduction in elasticity theory, rock physics, wave phenomena, and signal analysis. These are necessary topics for a proper appreciation of the seismic method. Data acquisition deals with seismic survey design and instrumentation, i.e. sources and receivers, for land and marine environments. Acquisition parameters and their impact on subsequent processing and interpretation will be discussed, as well as acquisition in terms of the spatial sampling of a surface wavefield, and in terms of illumination of subsurface targets. New developments in acquisition – survey design as well as instrumentation – will also be discussed; e.g. long offset full azimuth field design and broadband seismic acquisition. Data processing can be characterised as a sequence of processing steps that start with the field data and ends with an image in depth of the subsurface structure together with a velocity model and, ideally, amplitudes that can be used for further applications. Each of these processing steps has a number of alternative implementations and for each implementation there is a choice of parameters. During this course all processing steps will discussed together with their alternative implementations, parameter choices and strong and weak points. Data interpretation uses the depth image and velocity information for structural interpretation. Amplitude information, provided this information is preserved during processing, can be used for the subsequent derivation of lithological information, i.e. rock physics attributes, as well as used as direct hydrocarbon indicators (DHIs). The procedures like AVO (= amplitude versus offset) and seismic inversion will be discussed. In addition other procedures to exploit the seismic data will be discussed: time-lapse seismic (or 4D seismic), the derivation of seismic attributes like dip and azimuth, coherence, curvature and spectral decomposition. Developments like multi-component seismic, including OBC (ocean bottom cable) acquisition and processing together with their contribution to structural and lithological interpretation will be discussed. Anisotropy and fracture characterisation is naturally part of this discussion.

Traditionally, reflection seismic is used for its kinematic attributes, i.e. reflection traveltimes. However, we can also use reflection seismic for its dynamic attributes, i.e. reflection amplitudes, specifically, the behaviour of these amplitudes versus angle of incidence: AVA = amplitude versus angle, or, equivalently, AVO = amplitude versus offset. AVO attributes are used as independent evidence for the occurrence of hydrocarbons (in addition to structural evidence), as a hydrocarbon discriminator and as a lithology indicator. This course starts with a discussion of new developments in seismic data acquisition that have an impact on the accuracy of the AVO attributes, e.g. long offsets, wide-azimuth geometries and broadband data acquisition. It deals with elastic constants, wave propagation, boundary conditions, rock physics, and fluid substitution algorithms. It gives an overview of the factors that affect seismic amplitudes and of proper ways to process the seismic data such that amplitude information is preserved, which is then followed by the extraction of the relevant attributes and their interpretation. All aspects that are related with seismic inversion are dealt with, theoretical as well as practical. An AVO workshop will be part of the course. Seismic inversion is the process of converting seismic reflectivity data into (a) models of elastic properties of the subsurface, or into (b) a quantitative rock-property description of a reservoir. Seismic inversion may be pre-stack or post-stack, deterministic or geostatistical, and typically includes other reservoir measurements such as well logs and cores. Using the Bayesian approach, in which all available information can be reconciled, a statistical assessment of the desired reservoir properties can be obtained. The choice for a specific seismic inversion technique depends on the stage of development: Reconnaissance with no well control within the seismic Exploration and appraisal with well control within the seismic Focused reservoir characterization with well control and key reservoir parameters with their uncertainties. The course consists of the following four chapters: Rock physics: elasticity theory and the Gassmann equation AVO: formulation, processing and derivation of attributes Geostatistics: estimation of variables, probability theory and Bayesian statistics Seismic inversion: elastic and lithologic and deterministic and stochastic The course will deal with all aspects of deterministic and stochastic inversion.

Seismic reservoir geophysics can be defined as “The use of geophysical methods to assist in delineating or describing a reservoir or monitoring the changes in a reservoir as it is produced.” Reservoir geophysics is applied across a wide spectrum of the oilfield life cycle from discovery and early development to tertiary recovery. One critical part of this process is a good understanding of the various stages of seismic processing and the relationships between attributes derived from the seismic and the elastic properties, and rock and fluid properties. Reservoir characterization combines surface seismic with borehole seismic, well data, i.e. petrophysical data and rock and fluid properties and production history.

The overall objective is to introduce to seismic interpreters and geophysicists the key concepts, principles and practicalities that form the technical basis for value added seismic applications in exploration, field appraisal and reservoir management. Learning objectives are a practical understanding of present day processing methods and their implementation. Emphasis is on practical understanding of seismic acquisition, processing, imaging and technical requirements for extraction of geological and petrophysical information. Data examples, exercises and workshops are used to illustrate key concepts, practical issues and pitfalls as they affect seismic data quality and interpretation. The modular course design allows ready adaptation to shorter or longer versions and direct linkage to advanced treatment of specific topics.

As there exist a variety of ways to acquire seismic data and also a variety of objectives for which the data can be used it becomes clear that there is no standard procedure in seismic data processing. There is also a drive to extract ever more information from the data; hence, the scope for reprocessing. Seismic data processing can be characterized by a sequence of steps where, for each of these steps, there exists a multitude of different approaches. This course gives an overview of the steps that are common in seismic data processing and discusses for each step the variety of alternative implementations together with their implicit assumptions and strengths and weaknesses. This course enables the participants to conduct and/or supervise seismic data processing projects and assess the impact of a chosen workflow with respect to the stated objectives.

With the presence of new data acquisition techniques, like e.g. VSP, hole-to-hole, multi-component, and ocean bottom cable, also new processing methods have to be developed. Existing and new data sets will be exploited for optimal information retrieval: in addition to the conventional P-waves also the S-waves will be investigated and in addition to the kinematic properties, i.e. traveltimes for velocity and structural determination, also the dynamic properties, i.e. phase and amplitudes, for lithology and/or direct hydrocarbon indication will be investigated. Anisotropy, where present, should be taken into account and can be exploited for a.o. fracture orientation and density and time-to-depth conversion. The availability of other types of data like geological data and well data, in a production environment, should be properly integrated in inversion studies to initialize and constrain the results. This course deals with advanced processing methods that are often carried out as part of a special study and may involve the integration of data acquisition, processing and interpretation as well as petrophysics, production geology and reservoir engineering. The topics that will discussed cover a wide spectrum and are representative for what has become feasible nowadays.

Velocity is one of the most important parameter that can be derived from the seismic data. Velocity values are indicative for layer identification and thus convey rock properties. Moreover, velocities relate the seismic measurements that are in (two-way) traveltime to the end product of seismic data processing, i.e. the depth picture of the subsurface that can be obtained via migration or seismic imaging. New developments in acquisition geometries enable the determination of velocities with greater accuracy and also require to take into account anisotropy. The relationships between elastic constants and velocities are explained; this includes the phenomenon of anisotropy. In the end it is the wave equation that describes all wave propagation phenomena. Different types of velocities play a role during the processing sequence; stacking and migration being the most important ones. Migration or seismic imaging is the typical end product of conventional seismic data processing. The process of migration, whereby a proper image in time or depth of the subsurface is obtained, is directly related with the velocity model that both serves as input for the migration process as well as is the result of such a migration. Therefore migration and velocity model building are intimately related processes. DMO (dip moveout) can be considered as an intermediate process; it contains elements of migration and can be used in velocity model building. The implementation of migration is characterized by a multitude of methods and algorithms; there is also a variety of methods to build a velocity model. By the same token there is a number of DMO algorithms. This course gives an overview of all aspects of velocity that one encounters during seismic data processing, of the migration principles, methods and algorithms, of the velocity model building principles and methods as well as of the different DMO algorithms. In addition VSP data acquisition and processing will be discussed. During the course and at the end a number of representative case studies and examples will be shown to illustrate the material covered during this course.

In addition to kinematic attributes, traveltimes, that historically have received the most popular use of the seismic data, nowadays seismic data is also used for dynamic attributes, amplitudes. Examples of the application of AVO attributes are as independent supporting evidence of the occurrence of hydrocarbons in addition to structural evidence, as hydrocarbon discriminator and as a lithology indicator. This course gives an overview of the factors that affect seismic amplitudes and of ways to extract the relevant factor, i.e. the angle dependent reflection coefficient followed by its interpretation. Therefore the course will deal with wave propagation, boundary conditions, rock physics, fluid substitution algorithms, amplitude preserving seismic data processing, including true-amplitude migration, derivation of AVO attributes and the interpretation of these attributes. An AVO workshop will be part of the course.

Conventional seismic data (marine data and vertical geophones for land data) is dominated by P-waves. With the tendency to employ larger spreads also a larger contribution of S-waves will be recorded. However, it is with the use of multi-component seismic, preferably with a multi-component source as well as multi-component receiver, that the full  (vector-)wavefield will be recorded. Such datasets can then be used to extract the P-wave and S-wave characteristics. This requires special multi-component data processing techniques. In addition, as S-waves are more sensitive to anisotropy than P-waves and moreover display the unique feature of shear-wave birefringence (shear-wave splitting), it is necessary to take anisotropy into account in the processing. Such anisotropy can then be related to its causes and allow the derivation of e.g. fracture orientation and fracture density. As a marine environment does not support S-waves, the only way to record S-waves in such an environment is with ocean bottom cables and ocean bottom systems, where use is made of the generation of reflected S-wave energy at the reflectors from incident P-waves. Multi-component data acquisition and the various ways of multi-component data processing will be treated and a full understanding of anisotropy will be provided. A case study with acquisition and processing of a real 3D nine-component seismic survey  combines all aspects of  multi-component seismic and anisotropy and concludes this course.

The occurrence of noise is a pervading problem in seismic data. As there are many types of noise (random, organized in various ways) there are also many ways to reduce its impact. Moreover, while removing the noise, it is essential that the desired signal should be preserved. A representative overview will be given of the various types of noise together with methods to eliminate each type. A special type of organized of noise are multiples. It may even be argued that multiples are useful energy that should be used, after its separation from the primaries, for e.g. imaging. Depending on the environment, a specific type of multiple might be dominant, e.g. in a water layer with arbitrary waterbottom geometry or free-surface generated multiples. Such multiples require specific techniques for prediction and subsequent subtraction. An overview of all multiple types will be given together with methods to eliminate these.

Deconvolution is applied to enhance the vertical resolution of the data; at the same time the phase of the data should be equalized and preferably made zero. This process requires a proper description of the “wavelet”. As such the airgun signal, correlated vibroseis signal, geophone response, instrument response, reverberation mechanism, ghost mechanism, absorption mechanism etc. can be used. Some of these mechanisms can be measured (deterministic deconvolution) and others have to be estimated from the data (data adaptive deconvolution). Once the “wavelet” is known we can deconvolve for it in various ways taking into account the fact that the deconvolution filters have a finite length and the trade-off between enhancement of the resolution and deterioration of the signal-to-noise ratio. The physical processes and associated mathematical expressions of the various mechanisms will be treated.

4D seismic or time-lapse seismic is used to assess the effects of the production of hydrocarbons. Therefore it is required that these effects are such that seismic, which responds to the elastic parameters of P-wave, S-wave velocity and density, will be affected via these parameters sufficiently in order to display an observable effect. Modeling can be applied to investigate this possibility. Repeatability of acquisition geometry and processing workflow is another requirement for a successful application of 4D seismic. 4D differences can be kinematic, i.e. traveltimes, as well as dynamic, i.e. amplitudes, as well as both. Rock physics for modeling exercises and several processing techniques for a proper comparison of two datasets will be treated during this course.