Beyond Conventional Seismic Imaging
Course Description
I. Wavefield Data Analysis Time images usually provide sufficient information for a variety of subsurface models of moderate complexity and facilitate the estimation of the model for depth migration. Improving the quality of time sections remains the focus of intensive research. In particular, a lot of efforts are directed towards improving the accuracy of moveout correction. The proposed course discusses time imaging procedures such as Multifocusing and Common Reflection Surface when each image trace is constructed by stacking traces which need not belong to the same CMP gather. In this case a new and more general moveout correction is requested. These new methods open a way for reliable wavefield analysis and wavefront parameters estimation. The latest represents a basis for different applications including signal enhancement, velocity model building, statics correction, AVO analysis. II. Seismic Diffraction Currently applied seismic processing and imaging are almost exclusively based on seismic reflection. The latest is the response to continuity in the subsurface. At the same time accurate and reliable imaging of small scale geological elements and discontinuities of the subsurface such as faults, unconformity, fractures etc. are a key to improve seismic resolution. In unconventional reservoirs the main objective is detection of fracture corridors. Small scale objects give rise to a diffraction response. Use of seismic diffraction is a rapidly emerging technology which has tremendous potential to reduce exploration and production risks and increase oil and gas recovery. The course integrates elements of the theory of wave propagation, diffraction modeling and imaging, and interpretation. The main objectives are: understanding the role of small and medium scale subsurface objects and elements in forming the total seismic wavefield and using diffraction for imaging. III. Imaging without precise knowledge of the subsurface velocity model In the proposed course I introduce a way to look at model-independent seismic imaging using the quantum mechanics concept. Can Feynman’s path-integral idea be used for seismic imaging? We can construct the seismic image by summation over the contributions of elementary signals propagated along a representative sample of possible paths between the source and receiver points. When the velocity model is estimated with uncertainties, a single stationary path does not produce a correctly focused subsurface image. In contrary, quantum imaging uses all possible trajectories accounts for multiple stationary paths and takes into account model uncertainties. IV. Pitfalls and challenges of seismic inversion Proposed solutions are usually based on the criterion of the best fit between calculated and observed data. But it is well understood that by itself, a good fit does not guarantee that an inverted model is correct. Seismic inversion may lead to construction of several subsurface models with significantly different geological meaning, all of which fit the observed data equally well. The ill-posedness of seismic inverse problems is fundamental and does not depend on a particular type of algorithm or on the approach underlying the algorithms. In this course, I formulate a number of fundamental questions which should be addressed to make the inverse problems a mature science rather than a set of recipes. V. Time Reversal in Seismic Time Reversal (TR) plays an important role in seismic. It is directly connected to reverse time migration, interferometry and virtual source methods. Recently time reversal is proposed to localize subsurface sources in passive seismic and scatterers in active seismic surveys. Unlike in conventional migration, time reversal approach, in principle, does not require application of imaging condition. Numerical implementation of the time reversal method uses back propagation of the time-reversed recorded wavefield followed by an analysis of its obtained focusing. The physical implementation of TR, called Time Reversal Mirror (TRM), is used in various applications: underwater acoustics, telecommunication, cancer therapy, lithotripsy, nondestructive testing, etc. I demonstrate physical implementation of the TRM in seismic. Results of the field experiment show very promising results. I discuss possible applications of the method in seismic exploration and production.
Course Objectives
Upon completion of the course, participants will be able to: 1. Understand the role of time and depth imaging withing the general exploration work-flow. 2. Understand the differences between several prestack data analysis approaches, in particular CMP, CRS andincrease MF. 3. Appreciate importance and potential of seismic diffraction for increase resolution and reliability of seismic imaging. 4. Understand the uncertain nature of seismic velocity model and acquaintance to a way of taking the uncertainties into account. 5. Understand and admit fundamental problems of seismic inversion including FWI.
Course Outline
Introduction • From statistics to determinism • Overcoming uncertainties I. Non CMP-based methods for data analysis and imaging • Time versus depth imaging • Why CMP method works? • Non-hyperbolic moveout • Why CMP method fails? • Non-CMP based moveout: principles • Wavefront parameter estimation: Multifocusing and Common Reflection Stack • Applications: signal enhancement, statics correction, multiple attenuation, stack, migration II. Seismic Diffraction • Reflections versus difraction • History • Modeling • Diffraction imaging • Wavefield separation • Case studies III. Imaging without precise velocity model: Quantum seismic imaging • Feynman “path-summation” picture of the world • Path-summation seismic imaging IV. Pitfalls and challenges of seismic inversion • Inversion – thinking backward • Non-uniqueness of geophysical inversion • FWI: the present status V. Time Reversal in Seismic
Participants’ Profile
Participants should have a basic knowledge of seismic data acquisition and processing, static correction, CMP stacking for zero-offset approximation, normal moveout (NMO) correction, velocity analysis, semblance coherency measure, ray theory.
Prerequisites
Basic knowledge of seismic data acquisition and processing. static correction, CMP stacking for zero-offset approximation, normal moveout (NMO) correction, velocity analysis, semblance coherency measure, dip moveout. Basic knowledge in ray theory.
Recommended Reading
Participants are recommended to read the following articles before attending the course: • Peter Hubral, 2001. The hidden roots of human discovery and creativity. First break, Volume 19.11 November 2001 • Richard Feynman, 1985. Surely You’re Joking, Mr. Feynman!: Adventures of a Curious Character, Edward Hutchings (editor), W. W. Norton
About the Instructor
Evgeny Landa obtained his MSc degree in geophysics at Novosibirsk University (1972) and PhD degree in geophysics at Tel Aviv University (1986). He started his carrier in the former Soviet Union, Novosibirsk as a researcher, and senior geophysicist at the Siberian Geophysical Expedition. After immigrating to Israel, he worked at the Geophysical Institute of Israel as a researcher, Head of the R&D group and Head of the Seismic Department (1981—2002). During 2002-2014 he worked as Director of OPERA (Applied Geophysical Research Group) in Pau (France) where he was involved in different aspects of seismic data processing, velocity model building and time and depth imaging. His work on velocity model building by coherency inversion has had a strong impact on today’s seismic depth imaging workflows and forms an important part of the GeoDepth (Paradigm) software package. Recently he is a professor of Tell Aviv University. His research interest involves using non-reflecting energy for increasing seismic resolution and imaging without precise velocity information. He has published more than 60 papers in international journals and his book ‘Beyond Conventional Seismic Imaging’. He is a member of EAGE and SEG, from which he received the Awards of Best Paper (SEG, Honorary Mentioned, 2005) and the EAGE Eotvos Award (2007 and 2009)