Image Gathers Research Articles

Kinematics of reflections in subsurface offset and angle-domain image gathers

Kinematics of reflections in subsurface offset and angle-domain image gathers

Coherence-based time migration velocity analysis by the use of supergathers

Errors in the migration velocity field are perceived as moveouts in common-image gathers (CIGs). These moveouts depend on discrepancies in the velocity field as well as in the dip of the reflectors. We extend previous works into two main aspects. First, we found an accurate description of the residual moveout, considering the reflector dip, whereas only second-order approximations have been provided so far. Our formula for the moveout is exact, at the cost of being implicit. We evaluate an efficient numerical method to compute it accurately. Examples are provided to confirm that dipping angles far beyond those considered by previous approaches are reliable. Second, our moveout description is valid within a range of offsets and CIG positions, meaning that we can handle more than one CIG at once. In other words, instead of describing a moveout curve on a single CIG, we are able to compute a moveout surface across image gathers. From this larger volume of data, numerical experiments determine that more robust estimations are obtained for the velocity correction factors. Finally, the estimation of the best-fit parameters is carried out by a traditional coherence-based analysis, in which a modern derivative-free optimization method is used. We develop a set of numerical tests to validate the description of the residual moveouts, to compare our strategy with previous work from the literature, as well as to demonstrate that just a few image gathers are sufficient to stabilize the estimation of velocity correction factors. As a by-product, we obtained estimations of the reflector as well.

Adaptive Eye Fundus Vessel Classification for Automatic Artery and Vein Diameter Ratio Evaluation

Eye fundus imaging is a useful, non-invasive tool in disease progress tracking, in early detection of disease and other cases. Often, the disease diagnosis is made by an ophthalmologist and automatic analysis systems are used only for support. There are several commonly used features for disease detection, one of them is the artery and vein ratio measured according to the width of the main vessels. Arteries must be separated from veins automatically in order to calculate the ratio, therefore, vessel classification is a vital step. For most analysis methods high quality images are required for correct classification. This paper presents an adaptive algorithm for vessel measurements without the necessity to tune the algorithm for concrete imaging equipment or a specific situation. The main novelty of the proposed method is the extraction of blood vessel features based on vessel width measurement algorithm and vessel spatial dependency. Vessel classification accuracy rates of 0.855 and 0.859 are obtained on publicly available eye fundus image databases used for comparison with another state of the art algorithms for vessel classification in order to evaluate artery-vein ratio ($AVR$). The method is also evaluated with images that represent artery and vein size changes before and after physical load. Optomed OY digital mobile eye fundus camera Smartscope M5 PRO is used for image gathering.

A novel white blood cells segmentation algorithm based on adaptive neutrosophic similarity score.

White blood cells (WBCs) play a crucial role in the diagnosis of many diseases according to their numbers or morphology. The recent digital pathology equipments investigate and analyze the blood smear images automatically. The previous automated segmentation algorithms worked on healthy and non-healthy WBCs separately. Also, such algorithms had employed certain color components which leak adaptively with different datasets. In this paper, a novel segmentation algorithm for WBCs in the blood smear images is proposed using multi-scale similarity measure based on the neutrosophic domain. We employ neutrosophic similarity score to measure the similarity between different color components of the blood smear image. Since we utilize different color components from different color spaces, we modify the neutrosphic score algorithm to be adaptive. Two different segmentation frameworks are proposed: one for the segmentation of nucleus, and the other for the cytoplasm of WBCs. Moreover, our proposed algorithm is applied to both healthy and non-healthy WBCs. in some cases, the single blood smear image gather between healthy and non-healthy WBCs which is considered in our proposed algorithm. Also, our segmentation algorithm is performed without any external morphological binary enhancement methods which may effect on the original shape of the WBC. Different public datasets with different resolutions were used in our experiments. We evaluate the system performance based on both qualitative and quantitative measurements. The quantitative results indicates high precision rates of the segmentation performance measurement A1=96.5% and A2=97.2% of the proposed method. The average segmentation performance results for different WBCs types reach to 97.6%. In this paper, a method based on adaptive neutrosphic sets similarity score is proposed in order to detect WBCs from a blood smear microscopic image and segment its components (nucleus and the cytoplasm). The proposed segmentation algorithm can be utilized for fully-automated classification systems, such systems can be either for the healthy WBCs or even for non-healthy WBCs specially the leukemia cells.

Applying full-azimuth depth imaging in the local angle domain to delineate hard-to-recover hydrocarbon reserves

Hard-to-recover hydrocarbon reservoirs lie at great depths, in complex geological conditions. They are characterized by complex structures, low fluid permeability and a low oil and gas recovery ratio. In Russia today, about 60% of the potential oil and gas fields are located in this type of reservoir. These include hydrocarbon deposits in the Paleozoic basement (pre-Jurassic basement) of Western Siberia, subsalt carbonate sediments under salt dome tectonics, and carbonate and terrigenous deposits in the Volga region and Eastern Siberia. The exploration of these reservoirs benefits from a new, full-azimuth angle domain approach to seismic processing and imaging. This new technology can provide a more detailed depth image of the entire structural-tectonic reservoir skeleton, and a more accurate forecast of the main rock properties of the reservoirs. Conventional seismic depth imaging tools, such as ray-based or beam-based Kirchhoff migrations, applied to rich azimuth seismic data, normally generate multi-azimuth offset-domain common image gathers (CIGs). These are further used for anisotropic velocity model determination and for the characterization of reservoir properties, such as fracture systems. In these types of migrations, the input data is first binned into specific surface offset/ azimuth geometrical groups, such as offset vector tiles (OVT), azimuthal sectors or planner spirals, depending on the acquisition pattern. Each set of binned data is then independently migrated, with the final CIGs being simply a collection of individual images. However, in many cases, particularly when studying hydrocarbon reservoirs below complex geological areas and along steep inclined layers, the offset/azimuth CIGs do not provide the required information (in terms of accuracy and resolution, for example) to achieve the above mentioned goals. Unlike subsurface imaged events along the angle domain CIGs, which indicate ‘true’ local reflectivities, the reflection image events along the offset domain CIGs can be only considered a rough approximation of the ‘true’ reflectivities. Obviously, the accuracy and reliability of the offset domain CIGs are strongly compromised when imaging below complex geological areas with complex wave phenomena. One of the main drawbacks of offset domain imaging, especially in complex geological areas, is its inability to deal with the actual multi-pathing waves which are naturally handled within angle domain imaging.

Reverse-time migration and amplitude correction in the angle-domain based on Poynting vector

We propose a method based on the Poynting vector that combines angle-domain imaging and image amplitude correction to overcome the shortcomings of reverse-time migration that cannot handle different angles during wave propagation. First, the local image matrix (LIM) and local illumination matrix are constructed, and the wavefield propagation directions are decomposed. The angle-domain imaging conditions are established in the local imaging matrix to remove low-wavenumber artifacts. Next, the angle-domain common image gathers are extracted and the dip angle is calculated, and the amplitude-corrected factors in the dip angle domain are calculated. The partial images are corrected by factors corresponding to the different angles and then are superimposed to perform the amplitude correction of the final image. Angle-domain imaging based on the Poynting vector improves the computation efficiency compared with local plane-wave decomposition. Finally, numerical simulations based on the SEG/EAGE velocity model are used to validate the proposed method.

Prestack time migration of nonplanar data: Improving topography prestack time migration with dip-angle domain stationary-phase filtering and effective velocity inversion

We have developed a modified prestack time migration (PSTM) approach that can directly image nonplanar data by using two effective velocity parameters above and below a datum. The proposed extension improves the so-called topography PSTM by introducing a dip-angle domain stationary-phase migration (or filtering) and combining effective velocity inversion with the residual static corrections. The stationary-phase migration to constrain the imaging aperture within Fresnel zones significantly improves the signal-to-noise ratio (S/N) of the image gathers, especially in the presence of steeply dipping structures. This helps to extract an accurate residual moveout from the common shot and receiver image gathers, and the surface-consistent residual statics hidden in these image gathers can be simultaneously obtained from an inversion process. As a result, the final migrated images show higher S/N and are better focused than the conventional topography PSTM. The proposed technique can handle rugged topography, especially in the presence of high near-surface velocities, without the need for prior elevation static corrections. The SEG foothills overthrust model and a real data set acquired on a piedmont zone are used to validate the modified topography PSTM. Synthetic and field data examples are obtained with good results.

RoboWeedSupport-Semi-Automated Unmanned Aerial System for Cost Efficient High Resolution in Sub-Millimeter Scale Acquisition of Weed Images

Recent advances in the Unmanned Aerial System (UAS) safety and perception systems enable safe low altitude autonomous terrain following flights recently demonstrated by the consumer DJI Mavic PRO and Phamtom 4 Pro drones. This paper presents the first prototype system utilizing this functionality in form of semi-automated UAS based collection of crop/weed images where the embedded perception system ensures a significantly safer and faster gathering of weed images with sub-millimeter resolution. The system is to be used when the weeds are at cotyledon stage and prior to the harvest recognizing the grass weed species, which cannot be discriminated at the cotyledon stage.

ADCIGs extraction and reflection tomography modeling for elastic wave

Based on the theory of elastic wave, we derive the migration angle formula of P- and S-wave in the Gaussian beam migration and implement the ADCIGs (angle domain common imaging gathers) extraction for Gaussian beam of PP- and PS-wave firstly. Then, we derive the reflection tomography equations for elastic wave velocity analysis. They are used for the tomography velocity modeling base on the Gaussian beam ADCIGs. Making reflection tomography and depth migration into the same velocity modeling process, this method can not only use ADCIGs of elastic wave to update the velocities, but also can apply the migration results of tomography in each iteration as quality control, until the end of whole process in velocity modeling and finally we can get the prestack depth migration results after tomography. Synthetic and field examples validate the correctness and practicability of this method.

Applying full-azimuth angle domain imaging to study carbonate reefs at great depths

The main goal of the seismic surveys conducted in the target area in Kazakhstan was to image and detect a major Devonian carbonate barrier reef and to characterize the density and orientation of its main fracture zones. This area is unique in that the carbonate layers occur at great depths, from 5700 to 8500 m, with a complex structure of overburden layers of interbedded clay, sandstone, salt and others (Table 1). These different lithology plays and morphology rocks create strong vertical and lateral velocity variations, resulting in a complex seismic wave phenomenon. In addition, the target carbonate structures contain heterogeneous objects and require high-quality processing of the recorded data. Under such conditions, it is crucial to use full-azimuth, long-offset and dense (high fold) acquisition patterns. Advanced processing sequence tools and high-end depth migrations are required to handle both strong heterogeneity and azimuthal anisotropy effects. Traditional Kirchhoff migrations, even the most accurate ones (wavefront reconstruction, beam), have not been able to provide the required image quality and level of detail required at the target zones (Figure 1). Conventional Kirchhoff migrations generate surface offset-azimuth/offset domain common image gathers (CIG). In this particularly complex area, the correlation between the surface offset-azimuths and the actual, in situ, subsurface slowness-azimuths (azimuth of the incidence/reflected ray pairs at the image points) is relatively poor, leading to significant errors in the estimation of fracture orientation. Additionally, Kirchhoff migrations do not account for multi-pathing (multi-wave path solutions between image points and surface source/receiver locations), which is essential when imaging in areas involving complex wave phenomena. Kirchhoff beam migrations map surface beams with given directions backward to the subsurface. Since they account for the multi-pathing, they provide better results. However, they normally generate the same type of surface offset-azimuth/offset CIGs and therefore cannot be accurately used for azimuthal studies. They also cannot ensure sufficient subsurface illumination, especially at the complex target subsurface regions.

Double plane‐wave reverse‐time migration

ABSTRACTWe develop a new time‐domain reverse‐time migration method called double plane‐wave reverse‐time migration that uses plane‐wave transformed gathers. Original shot gathers with appropriate data acquisition geometry are double slant stacked into the double plane‐wave domain with minimal slant stacking artefacts. The range of plane‐wave components needed for migration can be determined by estimating the maximum time dips present in shot gathers. This reduces the total number of input traces for migration and increases migration efficiency. Unlike the pre‐stack shot‐profile reverse‐time migration where the number of forward propagations is proportional to the number of shots, the number of forward propagations needed for the proposed method remains constant and is relatively small even for large seismic datasets. Therefore, the proposed method can improve the efficiency of the migration and be suitable for migrating large datasets. Double plane‐wave reverse‐time migration can be performed for selected plane‐wave components to obtain subsurface interfaces with different dips, which makes the migration method target oriented. This feature also makes the method a useful tool for migration velocity analysis. For example, we are able to promptly obtain trial images with nearly horizontal interfaces and adjust velocity models according to common image gathers. Seismic signal coming from steeply dipping interfaces can be included into the migration to build images with more detailed structures and higher spatial resolution as better velocity models become available. Illumination compensation imaging conditions for the proposed method are also introduced to obtain images with balanced amplitudes.

234Compositor: A flexible parallel image compositing framework for massively parallel visualization environments

Leading-edge HPC systems have already been generating a vast amount of time-varying complex data sets, and future-generation HPC systems are expected to produce much higher amounts of such data, thus making their visualization and analysis a much more challenging task. In such scenario, the In-situ visualization approach, where the same HPC system is used for both numerical simulation and visualization, is expected to become more a necessity than an option. On massively parallel environments, the Sort-last approach, which requires final image compositing, has become the de facto standard for parallel rendering. In this work, we present the 234Compositor, a scalable and flexible parallel image compositor framework for massively parallel rendering applications. It is composed of a single-stage power-of-two conversion mechanism based on 234 Scheduling of 3-2 and 2-1 Eliminations, and a final image gathering mechanism based on Data Padding and MPI Rank Reordering for enabling the use of MPI_Gather collective operation. In addition, the hybrid MPI/OpenMP parallelism can also be applied to take advantage of current multi-node, multi-core architecture of modern HPC systems. We confirmed the scalability of the proposed approach by evaluating a Binary-Swap implementation of 234Compositor on the K computer, a Japanese leading-edge supercomputer installed at RIKEN AICS. We also evaluated an integration with HIVE (Heterogeneously Integrated Visual-analytic Environment) in order to verify a real-world usage. From the encouraging scalability results, we expect that this approach can also be useful even on the next-generation HPC systems which may demand higher level of parallelism.

High resolution diffraction imaging for reliable interpretation of fracture systems

Small-scale subsurface features, such as natural fractures, act as scattering sources for seismic waves propagating through the subsurface. The wavefield generated by those source points is identified as diffraction energy. The amplitude of this type of energy is much smaller than the recorded events reflected from actual interfaces between different geological layers. Moreover, diffraction energy is normally suppressed by conventional processing and standard imaging algorithms, where summations and averaging processes are applied. The common objective in such processing workflows is to focus on the high specular amplitudes in order to enhance the continuity of seismic reflection events for improving the structural mapping of the subsurface. Our goal is to complement the traditional seismic interpretation workflow by integrating information relative to diffraction energy as another seismic attribute to be interpreted. The technique applied in this paper is based on a depth imaging algorithm that maps and bins the recorded surface information into multi-dimensional, local angle domain (LAD) common image gathers. The advantage of this system is its unique ability to decompose the wavefield into reflection and diffraction energy directly at the image locations. This paper provides a brief overview of the technology and illustrates its benefits when applied to the Eagle Ford and Barnett shale reservoirs, where seismic data can be of moderate quality, leading to accurate, high-resolution, and highcertainty seismic interpretation for risk-managed field development.

Geometric model for an independently tilted lens and sensor with application for omnifocus imaging.

Optical imaging systems in which the lens and sensor are free to rotate about independent pivots offer greater degrees of freedom for controlling and optimizing the process of image gathering. However, to benefit from the expanded possibilities, we need an imaging model that directly incorporates the essential parameters. In this work, we propose a model of imaging which can accurately predict the geometric properties of the image in such systems. Furthermore, we introduce a new method for synthesizing an omnifocus (all-in-focus) image from a sequence of images captured while rotating a lens. The crux of our approach lies in insights gained from the new model.

Scalar and vector imaging based on wave mode decoupling for elastic reverse time migration in isotropic and transversely isotropic media

Recording P- and S-wave modes acquires more information related to rock properties of the earth’s interior. Elastic migration, as a part of multicomponent seismic data processing, potentially offers a great improvement over conventional acoustic migration to create a spatial image of some medium properties. In the framework of elastic reverse time migration, we have developed new scalar and vector imaging conditions assisted by efficient polarization-based mode decoupling to avoid crosstalk among the different wave modes for isotropic and transversely isotropic media. For the scalar imaging, we corrected polarity reversal of zero-lag PS images using the local angular attributes on the fly of angle-domain imaging. For the vector imaging, we naturally used the polarization information in the decoupled single-mode vector fields to automatically avoid the polarity reversal and to estimate the local angular attributes for angle-domain imaging. Examples of increasing complexity in 2D and 3D cases found that the proposed approaches can be used to obtain a physically interpretable image and angle-domain common-image gather at an acceptable computational cost. Decoupling and imaging the 3D S-waves involves some complexity, which has not been addressed in the literature. For this reason, we also attempted at illustrating the physical contents of the two separated S-wave modes and their contribution to seismic full-wave imaging.

Enabling affordable omnidirectional subsurface extended image volumes via probing

ABSTRACTImage gathers as a function of subsurface offset are an important tool for the inference of rock properties and velocity analysis in areas of complex geology. Traditionally, these gathers are thought of as multidimensional correlations of the source and receiver wavefields. The bottleneck in computing these gathers lies in the fact that one needs to store, compute, and correlate these wavefields for all shots in order to obtain the desired image gathers. Therefore, the image gathers are typically only computed for a limited number of subsurface points and for a limited range of subsurface offsets, which may cause problems in complex geological areas with large geologic dips. We overcome increasing computational and storage costs of extended image volumes by introducing a formulation that avoids explicit storage and removes the customary and expensive loop over shots found in conventional extended imaging. As a result, we end up with a matrix–vector formulation from which different image gathers can be formed and with which amplitude‐versus‐angle and wave‐equation migration velocity analysis can be performed without requiring prior information on the geologic dips. Aside from demonstrating the formation of two‐way extended image gathers for different purposes and at greatly reduced costs, we also present a new approach to conduct automatic wave‐equation‐based migration‐velocity analysis. Instead of focusing in particular offset directions and preselected subsets of subsurface points, our method focuses every subsurface point for all subsurface offset directions using a randomized probing technique. As a consequence, we obtain good velocity models at low cost for complex models without the need to provide information on the geologic dips.

Polarized wavefield magnitudes with optical flow for elastic angle-domain common-image gathers

We have developed a polarized wavefield magnitude (PWM) approach to determine the polarity of an elastic vector wavefield magnitude, for elastic prestack reverse time migration imaging and common-image gather generation. Explicit decomposition of the coupled elastic wavefield into separate P-waves and converted S-waves is performed by using decoupled elastodynamic wavefield propagation. Stable source and receiver wavefield propagation angles are determined by an optical flow method for elastic media. The sign ambiguity in the propagation directions for incident P- and reflected P- and S-wavefield vector magnitudes is resolved by establishing a relation between the propagation and particle velocity vectors. From the computed propagation angles, PP- and PS-wavefields are imaged using source-normalized crosscorrelation followed by sorting into common-image gathers. Modeling of amplitude variations with angle (AVA) from single-shot migrations and from elastic angle-domain common-image gathers demonstrates that the amplitude fidelity is maintained. Mode-converted PS reflectivities also give an independent set of accurate AVA information. Numerical results for the elastic Marmousi2 model confirm PWM as a physically valid and robust method for elastic wavefield imaging in arbitrarily complicated media.

A new parameter set for anisotropic multiparameter full-waveform inversion and application to a North Sea data set

Parameterization lies at the center of anisotropic full-waveform inversion (FWI) with multiparameter updates. This is because FWI aims to update the long and short wavelengths of the perturbations. Thus, it is important that the parameterization accommodates this. Recently, there has been an intensive effort to determine the optimal parameterization, centering the fundamental discussion mainly on the analysis of radiation patterns for each one of these parameterizations, and aiming to determine which is best suited for multiparameter inversion. We have developed a new parameterization in the scope of FWI, based on the concept of kinematically equivalent media, as originally proposed in other areas of seismic data analysis. Our analysis is also based on radiation patterns, as well as the relation between the perturbation of this set of parameters and perturbation in traveltime. The radiation pattern reveals that this parameterization combines some of the characteristics of parameterizations with one velocity and two Thomsen’s parameters and parameterizations using two velocities and one Thomsen’s parameter. The study of perturbation of traveltime with perturbation of model parameters shows that the new parameterization is less ambiguous when relating these quantities in comparison with other more commonly used parameterizations. We have concluded that our new parameterization is well-suited for inverting diving waves, which are of paramount importance to carry out practical FWI successfully. We have demonstrated that the new parameterization produces good inversion results with synthetic and real data examples. In the latter case of the real data example from the Central North Sea, the inverted models show good agreement with the geologic structures, leading to an improvement of the seismic image and flatness of the common image gathers.

Separating a wavefield by propagation direction

Determining the propagation direction of waves in a wavefield is important in several seismic imaging techniques and applications, including velocity analysis, amplitude variation with angle analysis, survey design, and illumination compensation. This can be achieved using the Poynting vector method, but this method performs poorly when waves overlap, returning incorrect wave amplitude and direction. An alternative, the local slowness method, is capable of separating overlapping waves, but it suffers from low angular resolution. We have developed modifications of these two approaches that improve the ability to extract the wave amplitude propagating in different directions. The primary modification is the addition of a wavefront orientation separation step. We have evaluated the methods’ ability to separate six overlapping waves with different phases in a constant velocity model, to accurately determine scattering angles in the construction of an angle domain image gather, and to determine the propagation directions of the back-propagated receiver wavefield for one shot in a 2D slice of the SEAM model. We have determined that in these examples, the proposed methods produce results that are generally superior to those of the Poynting vector and local slowness methods.

Prestack Depth Migration by a Parallel 3D PSPI

Prestack depth migration for seismic reflection data is commonly used tool for imaging complex geological structures such as salt domes, faults, thrust belts, and stratigraphic structures. Phase shift plus interpolation (PSPI) algorithm is a useful tool to directly solve a wave equation and the results have natural properties of the wave equation. Amplitude and phase characteristics, in particular, are better preserved. The PSPI algorithm is widely used in hydrocarbon exploration because of its simplicity, efficiency, and reduced efforts for computation. However, meaningful depth image of 3D subsurface requires parallel computing to handle heavy computing time and great amount of input data. We implemented a parallelized version of 3D PSPI for prestack depth migration using Open-Multi-Processing (Open MP) library. We verified its performance through applications to 3D SEG/EAGE salt model with a small scale Linux cluster. Phase-shift was performed in the vertical and horizontal directions, respectively, and then interpolated at each node. This gave a single image gather according to shot gather. After summation of each single image gather, we got a 3D stacked image in the depth domain. The numerical model example shows good agree- ment with the original geological model.