# Browsing by Subject "Seismic imaging"

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Item Depth-registration of 9-component 3-dimensional seismic data in Stephens County, Oklahoma(2014-05) Al-Waily, Mustafa Badieh; Hardage, Bob Adrian, 1939-Show more Multicomponent seismic imaging techniques improve geological interpretation by providing crucial information about subsurface characteristics. These techniques deliver different images of the same subsurface using multiple waveforms. Compressional (P) and shear (S) waves respond to lithology and fluid variations differently, providing independent measurements of rock and fluid properties. Joint interpretation of multicomponent images requires P-wave and S-wave events to be aligned in depth. The process of identifying P and S events from the same reflector is called depth-registration. The purpose of this investigation is to illustrate procedures for depth-registering P and S seismic data when the most fundamental information needed for depth-registration – reliable velocity data – are not available. This work will focus on the depth-registration of a 9-component 3-dimensional seismic dataset targeting the Sycamore formation in Stephens County, Oklahoma. The survey area – 16 square miles – is located in Sho-Vel-Tum oilfield. Processed P-P, SV-SV, and SH-SH wave data are available for post-stack analysis. However, the SV-data volume will not be interpreted because of its inferior data-quality compared to the SH-data volume. Velocity data are essential in most depth-registration techniques: they can be used to convert the seismic data from the time domain to the depth domain. However, velocity data are not available within the boundaries of the 9C/3D seismic survey. The data are located in a complex area that is folded and faulted in the northwest part of the Ardmore basin, between the eastern Arbuckle Mountains and the western Wichita Mountains. Large hydrocarbon volumes are produced from stratigraphic traps, fault closures, anticlines, and combination traps. Sho-Vel-Tum was ranked 31st in terms of proved oil reserves among U.S. oil fields by a 2009 survey. I will interpret different depth-registered horizons on the P-wave and S-wave seismic data volumes. Then, I will present several methods to verify the accuracy of event-registration. Seven depth-registered horizons are mapped through the P-P and SH-SH seismic data. These horizons show the structural complexity that imposes serious challenges on well drilling within the Sho-Vel-Tum oil field. Interval Vp/Vs – a seismic attribute often used as lithological indicator – was mapped to constrain horizon picking and to characterize lateral stratigraphic variations.Show more Item Phase-space imaging of reflection seismic data(2014-08) Bashkardin, Vladimir; Fomel, Sergey B.; Stoffa, Paul L., 1948-Show more Modern oil and gas exploration depends on a variety of geophysical prospect tools. One of them is reflection seismology that allows to obtain interwell information of sufficient resolution economically. This exploration method collects reflection seismic data on the surface of an area of prospect interest and then uses them to build seismic images of the subsurface. All imaging approaches can be divided into two groups: wave equation-based methods and integral schemes. Kirchhoff migration, which belongs to the second group, is an indispensable tool in seismic imaging due to its flexibility and relatively low computational cost. Unfortunately, the classic formulation of this method images only a part of the surface data, if so-called multipathing is present in it. That phenomenon occurs in complex geologic settings, such as subsalt areas, when seismic waves travel between a subsurface point and a surface location through more than one path. The quality of imaging with Kirchhoff migration in complex geological areas can be improved if multiple paths of ray propagation are included in the integral. Multiple arrivals can be naturally incorporated into the imaging operator if it is expressed as an integral over subsurface take-off angles. In this form, the migration operator involves escape functions that connect subsurface locations with surface seismic data values through escape traveltime and escape positions. These escape quantities are functions of phase space coordinates that are simply related to the subsurface reflection system. The angle-domain integral operator produces output scattering- and dip-angle image gathers, which represent a convenient domain for subsurface analysis. Escape functions for angle-domain imaging can be simply computed with initial-value ray tracing, a Lagrangian computational technique. However, the computational cost of such a bottom-up approach can be prohibitive in practice. The goal of this work was to construct a computationally efficient phase space imaging framework. I designed several approaches to computing escape functions directly in phase space for mapping surface seismic reflection data to the subsurface angle domain. Escape equations have been introduced previously to describe distribution of escape functions in the phase space. Initially, I employed these equations as a basis for building an Eulerian numerical scheme using finite-difference method in the 2-D case. I show its accuracy constraints and suggest a modification of the algorithm to overcome them. Next, I formulate a semi-Lagrangian approach to computing escape functions in 3-D. The second method relies on the fundamental property of continuity of these functions in the phase space. I define locally constrained escape functions and show that a global escape solution can be reconstructed from local solutions iteratively. I validate the accuracy of the proposed methods by imaging synthetic seismic data in several complex 2-D and 3-D models. I draw conclusions about efficiency by comparing the compute time of the imaging tests with the compute time of a well-optimized conventional initial-value ray tracing.Show more Item Seismic imaging and velocity model building with the linearized eikonal equation and upwind finite-differences(2014-05) Li, Siwei, 1987-; Fomel, Sergey B.Show more Ray theory plays an important role in seismic imaging and velocity model building. Although rays are the high-frequency asymptotic solutions of the wave equation and therefore do not usually capture all details of the wave physics, they provide a convenient and effective tool for a wide range of geophysical applications. Especially, ray theory gives rise to traveltimes. Even though wave-based methods for imaging and model building had attracted significant attentions in recent years, traveltime-based methods are still indispensable and should be further developed for improved accuracy and efficiency. Moreover, there are possibilities for new ray theoretical methods that might address the difficulties faced by conventional traveltime-based approaches. My thesis consists of mainly four parts. In the first part, starting from the linearized eikonal equation, I derive and implement a set of linear operators by upwind finite differences. These operators are not only consistent with fast-marching eikonal solver that I use for traveltime computation but also computationally efficient. They are fundamental elements in the numerical implementations of my other works. Next, I investigate feasibility of using the double-square-root eikonal equation for near surface first-break traveltime tomography. Compared with traditional eikonal-based approach, where the gradient in its adjoint-state tomography neglects information along the shot dimension, my method handles all shots together. I show that the double-square-root eikonal equation can be solved efficiently by a causal discretization scheme. The associated adjoint-state tomography is then realized by linearization and upwind finite-differences. My implementation does not need adjoint state as an intermediate parameter for the gradient and therefore the overall cost for one linearization update is relatively inexpensive. Numerical examples demonstrate stable and fast convergence of the proposed method. Then, I develop a strategy for compressing traveltime tables in Kirchhoff depth migration. The method is based on differentiating the eikonal equation in the source position, which can be easily implemented along with the fast-marching method. The resulting eikonal-based traveltime source-derivative relies on solving a version of the linearized eikonal equation, which is carried out by the upwind finite-differences operator. The source-derivative enables an accurate Hermite interpolation. I also show how the method can be straightforwardly integrated in anti-aliasing and Kirchhoff redatuming. Finally, I revisit the classical problem of time-to-depth conversion. In the presence of lateral velocity variations, the conversion requires recovering geometrical spreading of the image rays. I recast the governing ill-posed problem in an optimization framework and solve it iteratively. Several upwind finite-differences linear operators are combined to implement the algorithm. The major advantage of my optimization-based time-to-depth conversion is its numerical stability. Synthetic and field data examples demonstrate practical applicability of the new approach.Show more