Kinematic Wavefield Attributes Research Articles

Velocity-estimation improvements and migration/demigration using the common-reflection surface with continuing deconvolution in the time domain

To obtain an image of the earth’s subsurface, time-imaging methods can be applied because they are reasonably fast, are less sensitive to velocity model errors than depth-imaging methods, and are usually easy to parallelize. A powerful tool for time imaging consists of a series of prestack time migrations and demigrations. We have applied multiparameter stacking techniques to obtain an initial time-migration velocity model. The velocity model building proposed here is based on the kinematic wavefield attributes of the common-reflection surface (CRS) method. A subsequent refinement of the velocities uses a coherence filter that is based on a predetermined threshold, followed by an interpolation and smoothing. Then, we perform a migration deconvolution to obtain the final time-migrated image. The migration deconvolution consists of one iteration of least-squares migration with an estimated Hessian. We estimate the Hessian by nonstationary matching filters, i.e., in a data-driven fashion. The model building uses the framework of the CRS, and the migration deconvolution is fully automated. Therefore, minimal user interaction is required to carry out the velocity model refinement and the image update. We apply the velocity refinement and migration deconvolution approaches to complex synthetic and field data.

Velocity-model estimation with NIP-wave tomography inversion – A real data example

The common-reflection-surface (CRS) stack in addition to high signal-to-noise ratio stacked sections creates the curvature and local dip of a reflector. With this information, so-called kinematic wavefield attributes, it is possible to obtain a subsurface velocity model for laterally inhomogeneous media using normal-incidence-point (NIP) wave inversion. The result of CRS provides some location points on the stacked section as input for the inversion. In each iteration, dynamic ray tracing is applied along the central ray according to an input data point. With this technique, the parameter needed for forward modeling will be obtained. By updating the velocity model and minimizing the misfit between input data and the forward model parameter, it is possible to achieve a final velocity model consistent with input data. In this paper, we applied the CRS method on complex structure in the northeast of Iran, and then we performed the NIP-wave tomography inversion on this data set by means of CRS attributes. The result clearly shows the ability of NIP-wave tomography in velocity-model inversion.

Enhancement of Seismic Stacked Section Obtained from a Complex Geological Structure by using Partial CRS-Stack Method

Partial CRS-Stack method is proved as an alternative method that can produce excellent subsurface image, especially if this method is applied to a seismic data that is acquired from complex subsurface structure areas. The application of this method will give a new hope in determining subsurface structures in a better way, especially if it is implemented to seismic data obtained from Indonesian region, which is dominated by complex geological structures. The Partial CRS-stack method is tested by using a seismic dataset, which is acquired from eastern part of Indonesia. Here, the continuity of reflectors cannot be seen clearly. To prove the ability of Partial CRS-stack method, its result will be compared with the result obtained from the conventional sequences. The stacked section resulted from Partial CRS-stack is much better than the result of conventional one. This could be understood, since the Partial CRS-stack method uses the information of reflectors along fresnel zone, instead conventional method that only uses information in a CDP. During its processing sequence, CRS kinematic wavefield attributes, e.g. emergence angle (α), radius curvature of normal ray (RN) and radius curvature of normal incident point ray (RNIP) must be determined previously, which indicates the location and behaviour of reflectors. As a conclusion, the Partial CRS-stack method is proved as a good alternative method to give better seismic sections. Because of this, the interpretation of unclear events that are seen in the conventional stack section can be avoided.

Seismic image enhancement of mud volcano bearing complex structure by the CDS method, a case study in SE of the Caspian Sea shoreline

Improving seismic image quality in complex geological structures remains a challenge in seismic imaging. In complex media, imaging of geological structures such as the boundary of salt diapirs, faults, folding systems, overthrust zones, and unconformities are controversial and challenging tasks. Therefore, new imaging methods such as full waveform inversion, path-integral seismic imaging, reverse time migration, and the optimized common reflection surface stack methods were introduced to face these challenges. The common reflection surface stack method was used frequently to resolve some of the problems in complex structure seismic imaging. However, besides its great advantage in enhancing the quality of seismic section, it faces a problem with conflicting dips. The common reflection surface stack operator is an approximation of the reflection response of a curved interface in an inhomogeneous medium. In this study, a new strategy in the common reflection surface stack is introduced, which completely resolves the problem of conflicting dips in complex structures. Compared to the common reflection surface stack, the new stacking operator is the approximation of diffraction response of a diffraction point in depth. The kinematic wavefield attributes are defined for that diffraction point, whereas curvature of the interface is not fully considered. In the introduced strategy, there would be a stacking operator for each diffraction ray from the diffractor to the surface. Thus, the new operator gathers more energy that might get lost in imaging due to simplified operator in the other methods. The new method was applied to seismic data from a complex geological mud volcano bearing structure from south east of the Caspian Sea shoreline. This area includes numerous mud volcanoes which act as indicators of gas reservoirs. As a natural phenomenon, mud absorbs the seismic energy and deteriorates the quality of the final seismic section. Therefore, obtaining accurate image of the subsurface structures here, in the boundary portion of the mud volcano, is questionable. To overcome this problem, the new method was used to obtain a stacked section with all the possible diffraction energies. Subsequently, the stacked section underwent post stack depth migration. The final depth image proves the advantage of the new stacking operator for imaging in complex structures. Finally it could be concluded that this method could be used for imaging structures with sharp reflector truncations such as faults, diapirs, and unconformities.

NIP tomography inversion, a new improved method for velocity model estimation; synthetic data example

There are varieties of velocity models and velocity estimation methods in seismic data processing, but each has some drawbacks to use specially in complex structures and curved reflectors. NIP tomography inversion method is a new method which works with kinematic wave field attributes. Common-reflection-surface (CRS) stack provides us with three attributes, among them normal-incidence-point wave curvature RNIP will be used for the NIP tomography inversion. The method consists of three steps; automatic picking, modelling and inversion. One of the drawbacks of traditional methods is the huge points need to be picked and the difficulty of hand picking. With NIP tomography, we performed automatic picking on coherency section obtained from CRS stack. Picked data were plotted against other parameter and outlier data were omitted from dataset. These outliers are almost related to multiples which could make instability on inversion process. Then the corrected picked points were used for inversion process. In this step, the information velocity was interpolated between picks and trend of velocity changes was cleared. The traveltime for each point was calculated and the final 2D smooth velocity section was modelled. As it was expected, the velocity model performed good improvement in departing velocity variation in small scale and also in complex structures where it does not let conventional methods to differ two velocity values from each other.

Common reflection surface stack, new method in seismic reflection data processing: A synthetic data example.

The NMO/DMO/stack method is a traditional and well-known method in the oil industry that needs an accurate macro velocity model to image the subsurface structures. Making such a macro velocity model is a time consuming process that is error prone. New introduced common-reflection-surface (CRS) stack is a data driven method which is independent of velocity information apart from the surface velocity. It comes from common reflection point (CRP) trajectory concept for finite offset. In NMO/DMO/stack, the stacked data are obtained from a summation over a curve along the offset coordinate but the principal of CRS stack is to sum along a surface of specular contributions from a segment of a reflector instead of reflection point. The summation over a segment of a coherent reflector drastically improves the signal/noise (S/N) ratio as the stacked data will show. An important aspect of the method is that the estimated parameters provide us with significant information on the subsurface structure. These are three new parameters called kinematic wavefield attributes; a, RN and RNIP. The parameter a is the emergence angle of normal-ray which will be used later for a normal-ray map migration. RN is the curvature of the exploding reflector wavefield measured at the surface and RNIP is the curvature of normal-incidence-point wave which could be used later to yield information on the propagation velocity and inversion NIP tomography. Here we processed a synthetic data to derive zero offset or CRS stacked section with high S/N ratio and better continuity on the reflection events.

Imaging walkaway VSP data using the common-reflection-surface stack

Images from walkaway VSP data are traditionally obtained by using either a VSP-CDP transform or a VSP Kirchhoff migration, which both heavily rely on the knowledge of a velocity model. The need for a velocity model is eliminated by using model-independent imaging methods, such as the common-reflection-surface (CRS) stack. The CRS stack is a data-driven time-domain stacking method that leads to images with a higher signal-to-noise ratio. Moreover, kinematic wavefield attributes (CRS attributes) determined in the process can be used for a variety of applications.

Common reflection surface stack using dip decomposition for rugged surface topography

We present an extension of the Common Reflection Surface (CRS) stack that provides support for an arbitrary top surface topography. CRS stacking can be applied to the original prestack data without the need for any elevation statics. The CRS-stacked zero-offset section can be corrected (redatumed) to a given planar level by kinematic wave field attributes. The seismic processing results indicate that the CRS stacked section for rugged surface topography is better than the conventional stacked section for S/N ratio and better continuity of reflection events. Considering the multiple paths of zero-offset rays, the method deals with reflection information coming from different dips and performs the stack using the method of dip decomposition, which improves the kinematic and dynamic character of CRS stacked sections.

3D tomographic velocity model estimation with kinematic wavefield attributes

ABSTRACTA tomographic inversion method is presented that uses kinematic information in the form of zero‐offset traveltimes and kinematic wavefield attributes (first and second spatial traveltime derivatives) to determine smooth, laterally inhomogeneous 3D subsurface velocity models for depth imaging. The kinematic wavefield attributes can be extracted from the seismic prestack data by means of the common reflection surface (CRS) stack. The input for the tomography is then taken from the resulting attribute volumes at a number of pick locations in the CRS stacked zero‐offset volume. As a smooth model description based on B‐splines is used and reflection points are treated independently of each other, only locally coherent events in the stacked volume are required and very few picks are needed. Thus, picking is considerably simplified.During the iterative inversion process, the required forward‐modelled quantities are obtained by dynamic ray tracing along normal rays pertaining to the input data points. Fréchet derivatives for the tomographic matrix are calculated with ray perturbation theory. The inversion algorithm is demonstrated on a 3D synthetic data example, where the kinematic wavefield attributes have directly been obtained by forward modelling.

3D common-reflection-surface stack and kinematic wavefield attributes

Dissatisfaction with the resolution of time-domain images and poststack-migrated sections obtained by conventional processing directed a lot of effort in prestack migration methods and also led to new time-domain imaging techniques (Hubral, 1999). The common-reflection-surface (CRS) stack belongs to these new methods. It has been demonstrated that (a) the CRS stack produces high-resolution time-domain sections (Hubral, 1999) and (b) posstack depth migration of CRS stacked sections may be considered as an alternative to prestack depth migration in difficult areas and, as shown by Trappe et al. (2001), can lead to better results than prestack depth migration. The objective of this article is mainly to show two things. First, we present zero-offset (ZO) sections obtained by the 3D CRS stack from the first ever application of the 3D CRS stack on a real 3D land data set of industrial dimension. Simulated ZO sections for the same data set obtained by NMO/DMO/stack are shown for comparison. Secondly, we introduce the seismic attributes gained by the CRS stack which are extracted from the multicoverage prestack data by coherence analysis. These new “CRS attributes” open the way to many seismic applications, some of which are indicated in this article. In the seismic world, numerous attributes and also a range of classifications for seismic attributes exist. All aim at assisting the interpretation of seismic data. The attributes obtained by the CRS stack are time-derived attributes. In the CRS-related literature, they are also often referred to as kinematic wavefield attributes or wavefront attributes because the CRS attributes are associated with wavefronts of two so-called hypothetical waves. When simulating ZO sections from prestack data, these two wavefronts belong to the normal-incidence-point (NIP) and the normal (N) waves propagating from the bottom to the top along the ZO ray which hits the reflector perpendicularly in case of an …

Seismics and optics: hyperbolae and curvatures

We rederive and generalize hyperbolic moveout formulae for the common-midpoint (CMP) gather and for the zero-offset (ZO) section that can be efficiently used for macro-model-independent reflection imaging in two-dimensional media. The hyperbolic moveout formulae for the common-midpoint gather are obtained from different Taylor series expansions of a particular parametric moveout surface defined in the multicoverage data space. Such a moveout surface involves three kinematic wave-field attributes of two hypothetical waves, which have to be determined by a coherency analysis. By using hyperbolic moveout curves in the CMP gather and in the ZO section one can determine these attributes in two steps. The relationships between the local shapes of the interfaces and the attributes of the hypothetical wave-fields attributes are considered by means of geometrical optics. The determination of these attributes allows to perform a macro-model-independent ZO simulation and a subsequent inversion.