Conventional Velocity Analysis Research Articles

Horizontal well path design with seismic inversion for a shale oil reservoir in the Ordos Basin, China

The Ordos Basin is located in the western part of the North-China Platform, where China’s largest shale oil field was discovered. Most of the production originates from relatively thin and tight sand bodies within the Chang 7 member of the Triassic Yanchang Formation. This consequently requires accurate and high-resolution inversion data to characterize the reservoirs and define the horizontal well paths. In this paper, we adopt full-waveform inversion (FWI) to obtain the velocity model for time-to-depth inversion. Compared with conventional migration velocity analysis, FWI can produce velocity models with more high-wavenumber variations that reflect thin and localized geologic features. Geologic statistical inversion is also applied to resolve the thin beds beyond seismic resolution. A comprehensive index is then computed with the inverted parameters to evaluate the reservoir and build a sweet-spot map. We define the coordinates, direction, and length of the horizontal well on the maps. The well path is subsequently carefully designed on the sections of the time-to-depth converted inversion data. The effectiveness of the workflow is verified using the application case of the Qingcheng oil field at the Ordos Basin.

An Automatic Velocity Analysis Method for Seismic Data-Containing Multiples

Normal moveout (NMO)-based velocity analysis can provide macro velocity models for prestack data processing and seismic attribute inversion. Datasets with an increasing size require conventional velocity analysis to be transformed to a more automatic mode. The sensitivity to multiple reflections limits the wide application of automatic velocity analysis. Thus, we propose an automatic velocity analysis method for seismic data-containing multiples to overcome the limit of multiple interference. The core idea of the proposed algorithm is to utilize a multi-attribute analysis system to transform the multiple attenuation problem to a multiple identification problem. To solve the identification problem, we introduce the local similarity to attribute the predicted multiples and build a quantitative attribute called multiple similarity. Considering robustness and accuracy, we select two supplementary attributes based on velocity and amplitude difference, i.e., velocity variation with depth and amplitude level. Then we utilize the technique for order preference by similarity to ideal solution (TOPSIS) to balance weights for different attributes in automatic velocity analysis. An RGB system is adopted for multi-attributes fusion in velocity spectra for visualization and quality control. Using both synthetic and field examples to evaluate the effectiveness of the proposed method for data-containing multiples, the results demonstrate the excellent performance in the accuracy of the extracted velocity model.

Reverse Time Migration of Vertical Cable Seismic Data to Image Hydrate-Bearing Sediments With High Resolution

Marine vertical cable seismic (VCS) is a promising survey technique for submarine complex structure imaging and reservoir monitoring, which uses vertical arrays of hydrophones deployed near the seafloor to record seismic wavefields in a quiet environment. Recently, we developed a new type of distributed VCS system for exploration and development of natural gas hydrates preserved in shallow sediments under the seafloor. Using this system and air-gun sources, we accomplished a 3D VCS yield data acquisition for gas hydrates exploration in the Shenhu area, South China Sea. In view of the characteristics of VCS geometry, we implement reverse time migration (RTM) on a common receiver gather to obtain high-resolution images of marine sediments. Due to the unique acquisition method, it is asymmetrical for the reflection path between the sources and the receivers in the VCS survey. Therefore, we apply accurate velocity analysis to common scatter point (CSP) gathers generated from common receiver gathers instead of the conventional velocity analysis based on common depth point gathers. RTM with this reliable velocity model results in high-resolution images of submarine hydrate-bearing sediments in deep water conditions. The RTM imaging section clearly shows the bottom simulating reflector (BSR) and also the reflection characteristics of the hydrate-bearing sediments filled with consolidated hydrates. Moreover, its resolution is relative to that of acoustic logging curves from the nearby borehole, and this imaging section is well consistent with the synthetic seismogram trace generated by the logging data. All these results reveal that VCS is a great potential technology for exploration and production of marine natural gas hydrates.

Seismic velocity analysis in the presence of amplitude variations using local semblance

ABSTRACTObtaining accurate velocity models plays a crucial role in many routine seismic imaging algorithms. Seismic velocity models are normally made through seismic velocity analysis workflows. The routine workflows are not capable of dealing with polarity variations across moveout curves. We address this limitation by proposing a straight‐forward and robust semblance‐based workflow, which is a modified version of the conventional semblance function. The coherency function applies semblance analysis on separate clusters of receivers followed by averaging the corresponding coherency measures from all the clusters. The proposed approach is suitable for any case of amplitude variations including attenuation and any class of amplitude‐versus‐offset effects. The ability of the proposed workflow is demonstrated to two synthetic data as well as two field‐recorded common‐midpoint gathers. We perform accuracy analysis by comparing the results from the proposed approach with the results achieved from conventional velocity analysis, and another semblance‐based algorithm that is developed to address the polarity variation task. We also studied noise sensitivity analysis by computing and comparing mathematical expectations between theory and practice.

Direct Velocity Inversion of Ground Penetrating Radar Data Using GPRNet

AbstractGround penetrating radar (GPR) is used to image the shallow subsurface as evident in earth and planetary exploration. Electromagnetic (EM) velocity (permittivity) models are inverted from GPR data for accurate migration. While conventional velocity analysis methods are designed for multioffset GPR data, to our knowledge, the velocity analysis for zero‐offset GPR has been underexplored. Inspired by recent deep learning seismic impedance inversion, we propose a deep learning guided technique, GPRNet, that is based on convolutional neural networks to directly learn the intrinsic relationship between GPR data and EM velocity. GPRNet takes in GPR data and outputs the corresponding EM velocity. We simulate numerous GPR data from a range of pseudo‐random velocity models and feed the datasets into GPRNet for training. Each training data set comprises of a pair of one‐dimensional GPR data and EM velocity. During training phase, the neural network's weights are updated iteratively until convergence. This process is analogous to full‐waveform inversion in which the best model is found by iterative optimization until simulated data matches observed data. We test GPRNet on synthetic testing datasets and the predicted velocity models are accurate. A case study is presented where this method is applied on a GPR data collected at the former Wurtsmith Air Force Base in Michigan. The inversion results agree with velocity models established by previous GPR inversion studies of the similar area. We expect the GPRNet open‐source software to be useful in imaging the subsurface for earth and planetary exploration.

Study on the Velocity Analysis Method of Low SNR Seismic Data

When the signal to noise ratio of seismic data is very low, velocity spectrum focusing will be poor., the velocity model obtained by conventional velocity analysis methods is not accurate enough, which results in inaccurate migration. For the low signal noise ratio (SNR) data, this paper proposes to use partial Common Reflection Surface (CRS) stack to build CRS gathers, making full use of all of the reflection information of the first Fresnel zone, and improves the signal to noise ratio of pre-stack gathers by increasing the number of folds. In consideration of the CRS parameters of the zero-offset rays emitted angle and normal wave front curvature radius are searched on zero offset profile, we use ellipse evolving stacking to improve the zero offset section quality, in order to improve the reliability of CRS parameters. After CRS gathers are obtained, we use principal component analysis (PCA) approach to do velocity analysis, which improves the noise immunity of velocity analysis. Models and actual data results demonstrate the effectiveness of this method.

When There Is No Offset: A Demonstration of Seismic Diffraction Imaging and Depth‐Velocity Model Building in the Southern Aegean Sea

AbstractA vast majority of marine geological research is based on academic seismic data collected with single‐channel systems or short‐offset multichannel seismic cables, which often lack reflection moveout for conventional velocity analysis. Consequently, our understanding of Earth processes often relies on seismic time sections, which hampers quantitative analysis in terms of depth, formation thicknesses, or dip angles of faults. In order to overcome these limitations, we present a robust diffraction extraction scheme that models and adaptively subtracts the reflected wavefield from the data. We use diffractions to estimate insightful wavefront attributes and perform wavefront tomography to obtain laterally resolved seismic velocity information in depth. Using diffraction focusing as a quality control tool, we perform an interpretation‐driven refinement to derive a geologically plausible depth‐velocity model. In a final step, we perform depth migration to arrive at a spatial reconstruction of the shallow crust. Further, we focus the diffracted wavefield to demonstrate how these diffraction images can be used as physics‐guided attribute maps to support the identification of faults and unconformities. We demonstrate the potential of this processing scheme by its application to a seismic line from the Santorini Amorgos Tectonic Zone, located on the Hellenic Volcanic Arc, which is notorious for its catastrophic volcanic eruptions, earthquakes, and tsunamis. The resulting depth image allows a refined fault pattern delineation and, for the first time, a quantitative analysis of the basin stratigraphy. We conclude that diffraction‐based data analysis has a high potential, especially when the acquisition geometry of seismic data does not allow conventional velocity analysis.

Method for obtaining high-resolution velocity spectrum based on weighted similarity

Seismic wave velocity is one of the most important processing parameters of seismic data, which also determines the accuracy of imaging. The conventional method of velocity analysis involves scanning through a series of equal intervals of velocity, producing the velocity spectrum by superposing energy or similarity coefficients. In this method, however, the sensitivity of the semblance spectrum to change of velocity is weak, so the resolution is poor. In this paper, to solve the above deficiencies of conventional velocity analysis, a method for obtaining a high-resolution velocity spectrum based on weighted similarity is proposed. By introducing two weighting functions, the resolution of the similarity spectrum in time and velocity is improved. Numerical examples and real seismic data indicate that the proposed method provides a velocity spectrum with higher resolution than conventional methods and can separate cross reflectors which are aliased in conventional semblance spectrums; at the same time, the method shows good noise-resistibility.

Mirror reverse time migration using vertical cable seismic data for methane hydrate exploration

Gas hydrates are located in the permafrost and in deepwater shallow sediments, where low temperature and high pressure satisfy the stability conditions of methane clathrates to remain as solid compounds. Hydrates are found in a form of fine-layered or altered-layered structure with hiatuses and necessitate high-resolution surveys, which may not be achieved by conventional marine acquisition using towed streamers. We have developed a recent case study in which the vertical cable seismic (VCS) method has been used for high-resolution subseafloor imaging using a set of buoyed vertical-arrayed receivers that are anchored to the seafloor. The observation close to the target in the deepwater environment provides a higher signal-to-noise ratio and higher resolution. The primary reflections, however, could not achieve reliable depth images in the data processing due to their limited subsurface coverage. We used a reverse time migration (RTM) implementation of mirror imaging to extend the spatial subsurface coverage by using receiver ghost reflections. Because conventional velocity analysis methods are not applicable to the VCS survey due to the asymmetrical reflection path between the source and receiver, we implemented seismic interferometry and generated virtual surface seismic data from VCS data for velocity analysis. To preserve the resolution, amplitudes, and phase characteristics, we applied mirror RTM on the ghost reflections in the original VCS data rather than imaging the virtual data. The introduced case study using a VCS survey for identifying the methane hydrate system of the Umitaka Spur in the Sea of Japan led to high-resolution images, which suggest that a large gas chimney exists beneath a pockmark and is responsible for transferring methane gas from a deep hydrocarbon source to the shallow sediments. A bottom-simulating reflector as the base of the gas hydrate stability zone was also imaged.

Automated static and moveout corrections of high‐resolution seismic data from the Baltic Sea

ABSTRACTHigh‐frequency multichannel seismic systems provide detailed images of the shallow marine subsurface. In order to exploit the redundancy inherent in such data optimally, traveltime corrections need to account for normal moveout and static effects due to vertical source and receiver variations. Misalignment of reflections in common‐midpoint gathers will significantly lower the frequency content in the final stack, making this correction particularly important for very high‐frequency seismic data. Traditionally, normal moveout correction involves labour‐intensive picking of stacking velocities, while static corrections can be, by some techniques, performed automatically. In this paper, we present a high‐frequency seismic case study from the Baltic Sea, using seismic image matching as a novel, fully automated technique to perform joint moveout and static corrections. Our multichannel test profiles were acquired offshore Rügen island for wind farm development. Owing to the regular passage of up to 1.5 m high ocean waves during data acquisition, these boomer profiles suffer from strong static effects. We perform joint normal moveout and static corrections by defining the nearest common offset section as a fixed reference frame and minimizing its difference in traveltime with respect to all available common offset sections. Time shifts are computed independent of a pre‐defined traveltime curve, using the normalized cross‐correlation as a measure of data similarity while penalizing irregular displacements by a regularization term. Time shifts are converted to stacking velocities based on the traditional hyperbolic traveltime equation. Our results are compared with those derived by conventional manual velocity analysis and subsequent trim static corrections. We find that image matching produces stacks of similar quality and stacking velocity models of similar to slightly better quality compared with the conventionally derived ones, revealing the potential of this technique to automatize and significantly speed up this first part of the seismic processing chain.

Joint PP and PS plane-wave wave-equation migration-velocity analysis

Conventional joint PP and PS velocity analysis is based on ray tomography. We develop a joint PP and PS wave-equation migration-velocity-analysis method using plane-wave common-image gathers (CIGs) to produce accurate P- and S-wave velocity models. The objective function of our new method consists of three terms: The first and second terms penalize the moveout residuals computed from PP and PS plane-wave CIGs, respectively, and the third term constrains the nonzero relative depth shifts between the PP and PS migration images. The moveout of plane-wave CIGs is automatically picked using a semblance analysis method, and the relative depth shifts between the PP and PS images are automatically computed using dynamic warping or manually picking the depths of certain primary reflectors. The moveout residuals and the relative depth shifts are transformed into weighted image perturbations, and they are then projected into the velocity models to update the P- and S-wave velocity models using the scalar-wave equations and their linearized forms. Numerical tests with synthetic and multicomponent field data demonstrate that our method can simultaneously invert for accurate P- and S-wave velocity models for elastic migration.

Automatic migration velocity estimation for prestack time migration

Migration velocity analysis is a labor-intensive part of the iterative prestack time migration (PSTM) process. We have developed a velocity estimation scheme to improve the efficiency of the velocity analysis process using an automatic approach. Our scheme is the numerical implementation of the conventional velocity analysis process based on residual moveout analysis. The key aspect of this scheme is the automatic event picking in the common-reflection point (CRP) gathers, which is implemented by semblance scanning trace by trace. With the picked traveltime curves, we estimate the velocities at discrete grids in the velocity model using the least-squares method, and build the final root-mean-square (rms) velocity model by spatial interpolation. The main advantage of our method is that it can generate an appropriate rms velocity model for PSTM in just a few iterations without manual manipulations. In addition, using the fitting curves of the picked events in a range of offsets to estimate the velocity model, which is fitting to a normal moveout correction, can prevent our scheme from the local minima issue. The Sigsbee2B model and a field data set are used to verify the feasibility of our scheme. High-quality velocity model and imaging results are obtained. Compared with the computational cost to generate the CRP gathers, the cost of our scheme can be neglected, and the quality of the initial velocity is not critical.

High-resolution velocity analysis and program design based on Bootstrap algorithm

Seismic wave velocity is applied in all processes of seismic data processing and interpretation, and it is one of the most important parameters in seismic exploration. How to obtain high-resolution stack velocity spectrum [1], and then understand accurate velocity distribution of underground media is the key to seismic data processing. Conventional velocity analysis is based on multi-track cross-correlation within a time window defined along a hyperbola on a CDP gather, so it reflects the changes in signal stack energy within the window. The Bootstrap method is derived from mathematical statistics and is a mathematical method based on matrix transformation, which can accurately estimate the statistical distribution of given data. Based on conventional velocity analysis, this paper introduces how to use the Bootstrap method [2] to greatly improve the resolution of stack velocity spectrum, especially in processing data of shallow layers, large offsets and thin layers, based on old data and without additional investment. The application has provided high-resolution results and can effectively compensate many shortcomings of conventional methods. Based on theoretical derivation and process design, this paper presents the software designing process based on the data structure of an orthogonal list, then verifies the results using model and actual data, and finally compares the results with those from popular commercial software to verify the stability of the program and the reliability of the method.

CSEM-regularized seismic velocity inversion: A multiscale, hierarchical workflow for subsalt imaging

Seismic imaging in salt geology is complicated by highly contrasted velocity fields and irregular salt geometries, which cause complex seismic wavefield scattering. Although the imaging challenges can be addressed by advanced imaging algorithms, a fundamental problem remains in the determination of robust velocity fields in high-noise conditions. Conventional migration velocity analysis is often ineffective, and even the most advanced methods for depth-domain velocity analysis, such as full-waveform inversion, require starting from a good initial estimate of the velocity model to converge to a correct result. Nonseismic methods, such as electromagnetics, can help guide the generation of robust velocity models to be used for further processing. Using the multiphysics data acquired in the deepwater section of the Red Sea, we apply a controlled-source electromagnetic (CSEM) resistivity-regularized seismic velocity inversion for enhancing the velocity model in a complex area dominated by nappe-style salt tectonics. The integration is achieved by a rigorous approach of multiscaled inversions looping over model dimensions (1D first, followed by 3D), variable offsets and increasing frequencies, data-driven and interpretation-supported approaches, leading to a hierarchical inversion guided by a parameter sensitivity analysis. The final step of the integration consists of the inversion of seismic traveltimes subject to CSEM model constraints in which a common-structure coupling mechanism is used. Minimization is performed over the seismic data residuals and cross-gradient objective functions without inverting for the resistivity model, which is used as a reference for the seismic inversion (hierarchical approach). Results are demonstrated through depth imaging in which the velocity model derived through CSEM-regularized hierarchical inversion outperforms the results of a seismic-only derived velocity model.

High-Resolution Velocity Analysis Method Using the ℓ-1 Norm Regularized Least-Squares Method for Pavement Inspection

We propose a high-resolution velocity analysis method to estimate the electromagnetic wave propagation velocity in subsurface medium. The estimation is achieved by applying the l-1 norm regularized least-squares method to the conventional common-midpoint (CMP) velocity analysis algorithm. The proposed method can provide not only higher resolution than the conventional velocity analysis method, but can also be applied with a coarse sampling array system, such as our array ground penetrating radar YAKUMO, which returns eight CMP traces within a two meter width. The main purpose of this approach is for precise pavement inspection at shallow depths. We applied this method to both a simulated dataset and real data acquired by YAKUMO at a model airport taxiway to detect the slight velocity changes caused by millimeter-thin cracks filled with air or water within the 15 cm-thick asphalt pavement. In both cases slight velocity changes of about 0.005 m/ns can be detected, and the difference between air- and water-filled cracks can be distinguished. Also, this method is applied to a data acquired at airport taxi-way, the damaged parts are detected successfully and shows good agreement with the corning results. The results indicate that the proposed method is effective for pavement inspection, especially in the presence of thin cracks that cannot be seen directly with the reflected signal.

AUTOMATIC ESTIMATION OF STACKING VELOCITY BASED ON SPARSE INVERSION

AbstractStacking velocity analysis is a routine procedure in seismic data processing, and is also a classical method for initial velocity model building. Usually, stacking velocity analysis is divided into two steps: calculating stacking velocity spectra and picking spectra maximums. Until now, many researchers are trying to improve the stacking velocity spectra by computing a better semblance, considering the AVO effect or improving the anti‐noise ability of algorithm. However, it is seldom discussed on how to calculate the stacking velocity automatically. In this paper, we try to solve this problem by combining the velocity spectra calculation and picking procedure into a model parameter estimation under the framework of sparse inversion. Therefore, it is possible to invert the stacking velocity automatically and shorten the turn‐around time of initial velocity model building and reduce human costs considerably. To solve this problem, first we give the definition of forward problem, which is the prediction model for CMP gather using stacking velocity and t0 time as model parameters. Then, the inverse problem is defined as finding the sparse model parameters with the given CMP gather. Using the sparsity of model parameters as model constraint, we reformulate the conventional stacking velocity analysis problem as a new sparse inverse problem, and present an adaptive matching pursuit (MP) algorithm to solve it. The proposed method is quite promising for automatic initial model building, and can provide a good initial model for subsequent high‐resolution velocity inversion methods. Numerical and field data tests demonstrate the effectiveness of the proposed method.

A generalized view on normal moveout

Although in the past, in the context of stacking, traveltime moveout was only formulated in individual common-midpoint (CMP) gathers, multiparameter stacking uses normal moveout (NMO) approximations that span several neighboring CMPs. Multiparameter expressions such as the common reflection surface (CRS) or multifocusing are parameterized in terms of local slopes and curvatures of emerging wavefronts rather than effective velocities, which makes these approaches appear conceptually different from conventional velocity analysis. As a consequence, the unifying nature of multiparameter NMO is still not well-appreciated. In addition, CRS and multifocusing show distinctly different behavior in that they respond differently to the overburden heterogeneity and curvature of the target interface, and they either are or are not susceptible to moveout stretch. In our work, we seek to demystify the wavefront picture by demonstrating that the conventional and multidimensional NMO operators can conveniently be derived from the same auxiliary straight-ray geometry, either representing the optical projection or formulated in an effective replacement medium. Following the early work of de Bazelaire, we suggest a simple transformation between both domains and introduce generalized dual representations of the hyperbolic CRS, multifocusing, and the two recently introduced double-square-root expressions implicit CRS and nonhyperbolic CRS. In addition, we evaluate a generalized finite-offset NMO expression that can likewise be applied to active-source diffraction data and passive seismic events. Synthetic examples suggest unification, conveniently explain the origin of moveout stretch, and indicate that the joint use of different NMO approximations offers new insight into the character and origin of different wavefield components.

Imaging Subsurface Fracture and Void using Wide-Band Inversion of Fresnel Interpolated Wavepath Seismic Tomography

Studying existence of fracture, void as well as fault in subsurface are important and it has wide applications. In addition, fracture and void play important role in reservoir productivity as well as in geotechnical application. The problem in imaging fracture and void in subsurface, however, is resolution. It needs high-resolution imaging method laterally as well as vertically. The seismic velocity imaging, however, usually has poor lateral resolution. Seismic tomography provides better resolution than conventional velocity analysis methods. Conventional raypath seismic tomography, however, needs dense as well as high angle and wide measurement configuration that is high cost in field data acquisition. I propose to use Fresnel interpolated wavepath (FIW) wide-band inversion. FIW is an interpolation between imaginary part of Rhytov scattering wavepath and raypath. Then, FIW is combined with wide band inversion procedure to handle sparseness configuration of measurement. By this method, smooth constraint is implemented more naturally by based on wave's spectrum. Furthermore, it can produce more stable inversion procedure. In this paper, Wide-band inversion of FIW tomography is tested into various seismic field data in order to image void, fault and fracture. The results showed that tomography based on FIW could handle the limitation of configuration angle, sparseness configuration and resulting good image. We use many difficult cases of field data such as: subsurface tunnel imaging and also void-fracture imaging in volcanic rock

High-resolution seismic velocity analysis as a tool for exploring gas hydrate systems: An example from New Zealand’s southern Hikurangi margin

The existence of free gas and gas hydrate in the pore spaces of marine sediments causes changes in acoustic velocities that overprint the background lithological velocities of the sediments themselves. Much previous work has determined that such velocity overprinting, if sufficiently pronounced, can be resolved with conventional velocity analysis from long-offset, multichannel seismic data. We used 2D seismic data from a gas hydrate province at the southern end of New Zealand’s Hikurangi subduction margin to describe a workflow for high-resolution velocity analysis that delivered detailed velocity models of shallow marine sediments and their coincident gas hydrate systems. The results showed examples of pronounced low-velocity zones caused by free gas ponding beneath the hydrate layer, as well as high-velocity zones related to gas hydrate deposits. For the seismic interpreter of a gas hydrate system, the velocity results represent an extra “layer” for interpretation that provides important information about the distribution of free gas and gas hydrate. By combining the velocity information from the seismic transect with geologic samples of the seafloor and an understanding of sedimentary processes, we have determined that high gas hydrate concentrations preferentially form within coarse-grained sediments at the proximal end of the Hikurangi Channel. Finer grained sediments expected elsewhere along the seismic transect might preclude the deposition of similarly high gas hydrate concentrations away from the channel.

Research on improving conventional marine seismic streamer data imaging quality using OBS data from Northern South China Sea

It is very important to convert the seismic data from the time domain to the depth domain. Here we discuss the approaches of inverse modeling of travel times for determination of the P-wave velocity (Vp) using OBS data, and also using the inverted velocity to improve the conventional marine seismic streamer data imaging quality. The migration section of the single channel seismic data is used to define the model horizons and help to control their geometry. Wide angle hydrophone data of OBS are used to determine P-wave travel times. The picked travel times from various shots are inverted for P-wave interval velocities using RayInvr, which calculated theoretical travel times via ray tracing. Damped least squares optimization is performed to fine tune the fits between observed and calculated travel times. In the end, two conventional marine seismic streamer data's migration sections are compared and the result shows that the section using the inverted velocity of OBS data is much better than that using the velocity of conventional velocity analysis method to the streamer data.