SC1 - Seismic interferometry: turning noise into signal

Lecturer: Dr. Kees Wapenaar, Delft University of Technology

Seismic interferometry is the process of generating new seismic responses by crosscorrelating seismic observations at different receiver locations. A first version of this principle was derived in 1968 by Claerbout, who showed that the reflection response of a horizontally layered medium can be synthesized from the autocorrelation of its transmission response. This amazing result implies that, when a natural noise source in the Earth's subsurface emits waves to the surface, passive measurements of the noise at the surface can be transformed into the reflection response of the Earth's subsurface. Later Claerbout conjectured for the 3-D situation that ‘by crosscorrelating noise traces recorded at two locations on the surface, we can construct the wave field that would be recorded at one of the locations if there was a source at the other’. Schuster argued that a similar principle applies to crosscorrelations of traces in seismic shot records and introduced the principle of interferometric imaging, i.e., forming an image of the subsurface from crosscorrelated seismic traces.

In this course we first discuss the theory of seismic interferometry for 3-D inhomogeneous media. Starting with Green’s theorem, we will derive a number of relations that form the basis for seismic interferometry (amongst others these relations prove Claerbout’s conjecture) and interferometric imaging. Next we discuss a number of applications, like passive reflection seismics (useful for monitoring), improving sparse data sets and interferometric imaging for different geometries. Apart from applications in exploration, seismic interferometry has potential applications in deep seismics and global seismology. The ability to create virtual sources at every seismological station in solid-earth seismology would allow increased illumination of the target area and, consequently, reflection images with increased resolution.

3D passive subsurface imaging is not restricted to ambient seismic noise. We will discuss developments that are underway to retrieve virtual diffusive electromagnetic data from magneto-telluric noise and virtual ground-penetrating radar data from extraterrestrial electromagnetic noise. Cross-correlating seismic with electromagnetic noise observations may result in virtual electroseismic responses, with the potential of obtaining the subsurface’s poroelastic parameters. We will discuss the generalization of the theory for a wider class of linear equations, which allows the retrieval of impulse responses (Green’s functions) from noise correlations in systems ranging from quantum mechanics to mechanical structures like buildings and bridges. In the coming years there are many new applications to be expected in the field of extracting information from ambient noise.

SC2 - Reverse-time migration

Lecturer: Dr. Paul Sava, Colorado School of Mines

Reverse-time migration represents one of the most accurate seismic imaging methods and has seen rapid growth in the past years. This growth is motivated by the complexity of exploration targets which require increasing imaging accuracy in difficult geologic environments. Reverse-time migration can deliver the highest level of accuracy for imaging structures with steeply dipping reflectors and complex geologic models characterized by velocity with rapid spatial variation and anisotropy. Reverse-time migration is not a new methodology, since its first successful demonstrations date back several decades. However, its recent wide-spread adoption is driven by significant advances in high-performance computing and new theoretical developments, like angle-domain imaging, which enable applications like migration velocity analysis and amplitude-versus-angle analysis.

This course provides an overview of reverse-time imaging methodology applied to acoustic wavefield data. The main target audience are practicing geophysicists with a basic understanding of seismic data processing and imaging as well as researchers and graduate students who wish to get familiar with modern imaging techniques available to the industry. Geologists and reservoir engineers can also benefit from this short course, by familiarizing themselves with the underlying imaging concepts, their applicability and limitations.

SC3 - Structural Styles in Petroleum Exploration

Lecturer: Dr. Pedro Zalán, Petrobras

To present the basic concepts of structural styles based on modern findings achieved in the fields of structural geology and seismic interpretation, during the last 25 years.  The huge amount of seismic data available for petroleum exploration revealed previously unknown styles of deformation, in both onshore and offshore sedimentary basins, but especially in the deep and ultra-deep water realms of the continental margins.  The concepts will be heavily illustrated by seismic and field examples, trying to focus on their helpfulness for successful petroleum exploration.

SC4 - Controlled Source Electromagnetic Surveying

Lecturer: Dr. Martin Sinha, University of Southampton

Morning:  Part 1 – Revision and Overview: Electrical conduction in the Earth: mechanisms and variability; Ohm’s Law, current density, potential gradient and electrical resistivity; CSEM surveying: what is it and what is its objective?; CSEM data acquisition – overview; CSEM in practice - what do we measure, and how?; ‘Amplitude’ and ‘Phase’ and Geometric definitions and the Polarization Ellipse

Morning:  Part 2 – Underlying Theory: Starting point 1: Fields from a DC point dipole; Radial fields and Tangential Fields, Fields from an AC point dipole; Longitudinal waves and Transverse waves; Starting point 2: Boundary conditions and behaviours at interfaces; Starting Point 3: Maxwell’s Equations, transverse waves and skin depth; Complex wavenumber, attenuation and phase velocity and Consequences and the limits on ‘useful’ frequencies

Afternoon:  Part 3 – Induction in the real world: the Sea Surface Interaction – nature and consequences; Modes of Induction in a layered earth: VE mode and VM mode; Dissipation, current blocking and current channelling; Sensitivity and ambiguity in CSEM data; Detecting thin, resistivive, buried layers; Resolving parameters – thickness, resistivity, depth of burial

SC5 – Rock Physics

Lecturer: Dr. Amos Nur, University of Stanford

SC6 – Oil Field Applications of Passive Seismic

Lecturer: Dr. Peter Duncan, Microseismic

In a very real way, passive seismic, especially microseismic monitoring, is to conventional seismic as a stethoscope is to a sonograph. It is continuous 4-D. It is accomplished by listening carefully to the sounds emanating from the earth and then diagnosing what is happening down there. Passive seismic techniques can create not only an image of the reservoir and its plumbing, but also shed light on how the fluid is flowing through the pipes.  While interest in passive seismic an E & P tool has grown exponentially over the past decade, the technology is not fundamentally new. Rather it is a re-engineering down to oilfield scales of what researchers have practiced for decades as “solid earth seismology”. The basic elements are seismic event location and travel time tomography.
Grasping the completeness of the passive science, one can see that it provides the opportunity to contribute over the lifetime of an oilfield from discovery to abandonment. Passive seismic can accomplish reconnaissance 3-D exploration at an attractive cost and lead to new discoveries. Microseismic monitoring of a hydrofrac can and does provide valuable information on completion and development strategy. Gas or fluid injection operations for primary or secondary recovery are prime candidates for passive monitoring to prove regulatory compliance, validate reservoir conformance and estimate recovery efficiency.
This one day class will present a brief history of the development of passive seismic techniques, a discussion of state of the art through case histories that illustrate the various applications of the technology and a vision on where this technology will play a role in the smart oil field of the future.

SC7 - Mathematics of Modeling, Migration and
Inversion with Gaussian Beams

Lecturer: Dr. Norman Bleistein, Colorado School of Mines

Gaussian beams are asymptotic solutions of a wave equation with complex-valued traveltimes and amplitudes. They generate better quality forward modeling and migration output than can be obtained from classical ray theory. Furthermore output–modeled or imaged seismic data—is generated at a cost that is favorable compared to even better quality modeling techniques such as one-way or two-way wave equation modeling. To date, there are no examples in the open literature of inversion—true amplitude migration—using Gaussian beams. To this author, the interchangeable terms “inversion” and “true amplitude migration” mean producing an output where the peak amplitude on each reflector is asymptotically proportional to the ray-theoretic reflection coefficient at a determinable incidence angle, consistent with the model wave equation and background wave speed.  Classical ray-theoretic modeling fails in the neighborhood of caustics (envelopes of rays), whereas Gaussian beam solutions do not. Furthermore, Gaussian beam representations of wave fields employ integration over a suite of beams around the output point. Thus, Gaussian beams are affected by the wave speed in a neighborhood of the ray through the output point, whereas classical ray solutions depend only on medium parameters along the single ray through the output point. Stated differently, a Gaussian beam can sense the velocity structure for some distance away from the central ray, while a classical ray cannot.  In developing this theory, I have come to the conclusion that some elementary ideas in the development of Gaussian beams seem to have been forgotten (lost?) in the current dominant literature, making it a challenge for initiates to learn this important methodology. This course is my attempt to resurrect these ideas from the early literature of Gaussian beams to facilitate better understanding and more expanded capability for implementation.       Current literature derives the complex traveltime via a boundary layer method. However, ray theory supports complex exponents as solutions of the eikonal equation without resorting to boundary layers. Furthermore, using complex exponents, the solution of the transport equation for amplitude propagation along rays is more straightforward than through the boundary layer approach. In the modeling portion of this course, I propose to treat ray theory for Gaussian beams as the third step in a hierarchy of methods, starting from classical ray theory in Cartesian coordinates, followed by ray theory in ray-centered coordinates. Here, we particularly focus on real solutions of the eikonal equation as traveltime along the central ray plus a correction up to quadratic order in variable(s) normal to the central ray. Following that, we examine the consequences of allowing the quadratic correction to be complex-valued. Those solutions are Gaussian beams. These new solutions are best derived in ray-centered coordinates as I propose here because of the important role that the central ray plays in the power series expansion of the traveltime.  We apply the method to modeling the propagation from point sources (Green’s functions) and from initially planar waves.  For Green’s functions in 3D, the domain of integration is conical, with all of the beams initiated at the apex of the cone. The representation of the Green’s function, when its source point is not at the apex of the cone, is more challenging than when the source point is the apex of the cone.  Following this discussion of modeling, I discuss migration/inversion.  I treat several cases including common-shot inversion; inversion of plane wave data synthesized from common-shot data; common-offset data in 2.5D; common-angle inversion. "Common-angle" refers to opening and azimuth angles from sources and receivers at image locations. This last method separates multiple arrivals into different common-angle outputs. The output of common-angle inversion allows for direct AVA analysis.  Although it is derived as an integral over migration dip and azimuth at an image point, it is transformed to an integral over all source/receiver pairs, allowing more straightforward data-access than is possible when integrating over angles at the image point.  Finally, describe the modification of the standard Kirchhoff-type inversion formulas using Green’s function representations by Gaussian beams.

SC8 - Fundamentals of the Seismic Method
applied to Petroleum Exploration

Lecturer: Eduardo Filpo, Petrobras

Summary:

• Basic Principles of Wave Theory

• Fundamentals of Elasticity Theory
  

• Seismic Wave Propagation
  

• Energy Partition of Seismic waves
  

• Seismic Velocities
  

• Fundamentals of Seismic Processing
  

• Introduction to Seismic Imaging
  

SC9 - Understanding Multicomponent Seismic Data

Lecturer: Dr. Peter W. Cary, Sensor Geophysical

This course provides an overview of the methods of multicomponent seismic exploration and is appropriate for interpretation and processing geophysicists who want a deeper understanding of their 3-C or 4-C multicomponent surface seismic data. Most of the course focuses on multicomponent seismic processing, but basic aspects of vector wave theory, P-P and P-S synthetic seismograms, survey design, acquisition and interpretation are also included. Aspects of 2-D, 3-D and 4-D land and marine surveys are discussed.

Topics discussed in the course include:
Elastic Wave Theory: vector wave equation: P-wave and S-wave solutions, Interface mode conversion: P to S, amplitudes, velocities, polarization,   Anisotropy: VTI, HTI, shear-wave splitting.

Planning and Acquiring Converted-Wave Surveys: P-S synthetic seismograms, P-S survey design, Acquisition with MEMS sensors

Processing: Coordinate definitions and rotations -  Polarization filtering, Statics, binning, NMO, DMO and velocities, Vp/Vs ratios and anisotropy, Stacking, migration Shear-wave splitting analysis and compensation, Resolution and S/N

Interpretation: Interpretation tools and methods, Inversion and attributes