Stacking Velocity Research Articles

Seismic Inversion Techniques and Attribute Analysis for Accurate Well Placement in Offshore Niger Delta Basin, Nigeria

Before this study, simple methods like seismic attribute analysis have often been used for reservoir characterization with successes however, there is still the need to reduce exploration uncertainty to a negligible level and boost investors’ confidence. This study integrated seismic inversion with seismic attribute analysis to better characterize the reservoirs in MTW Field in deep-offshore Niger Delta Basin. Five (5) wells with complete suite of petrophysical logs, three-Dimensional (3-D) seismic data, checkshot and other well information were used. The well data were thoroughly quality checked, reservoirs were litho-stratigraphically delineated and used for petrophysical analysis across the wells. This was followed by seismic-to- well-tie, seismic interpretation, and seismic attribute analysis (Root Mean Square-RMS) generated using depth surface maps. 3-D static reservoir model and volumetric evaluation were carried out. Petrophysical properties were derived and distributed across the 3-D static model using sequential gaussian simulation algorithm to ascertain shale volume spread across the model. To improve the seismic resolution and reduce interpretation uncertainty at greater depth, model- based post-stack seismic inversion was performed to obtain acoustic impedance cube. Litho-stratigraphic and petrophysical analysis result revealed five reservoir sands (A, B, C, D, and E). Reservoir-A was seen to be more viable with a thickness of 13.42 m, high effective porosity of 27%, permeability of 3187.53 mD, low water saturation of 34% and low shale volume of 11% which are indication good reservoir quality and producibility. The seismic interpretation revealed thirty-one (31) growth and antithetic faults oriented in the NE-SW and NW-SE directions, respectively. The RMS result revealed high amplitude reflectivity which is a measure of zone of interest. Based on this, seven (7) prospects and three (3) leads were identified. The seismic inversion result shows a high level of accuracy with a correlation coefficient of 0.997; 0.997; 0.995; and 0.996 in MTW-001, MTW-003ST1, MTW-004ST1 and MTW-005 wells, respectively. The acoustic impedance successfully resolved and improved on the resolution of the seismic stacking velocity especially at reservoir layers and at depth deeper than 3600 ms. Acoustic impedance as a layer property has improved on the lateral and vertical resolutions of the data beyond what the usual seismic interval velocity could image thus, validating some of the prospects and leads identified in this study. This demonstrated that uncertainty can be reduced by a blend of RMS and seismic inversion in identifying reservoir for accurate placement of wells. It is therefore recommended that E and P operators should adopt the technique in their future hydrocarbon exploration endeavor in frontier and matured basins.

Crustal thicknesses in Uruguay from joint inversion of receiver functions and surface wave dispersion

The development of a seismic network in Uruguay in recent years has enabled studies of crustal structure in a region with few seismological studies of this type. In this work, we update the crustal thicknesses and Vp/Vs ratios calculated by H-k stack and present S-wave velocity models based on joint inversion of receiver functions and Rayleigh wave group velocity dispersion curves.Some interesting results are the presence of a lower crust with a high S-wave velocity of 4.1 km/s below one of the stations located on the Río de la Plata Craton and the existence of a transitional Moho in Uruguay's northernmost station on the Paraná Basin, perhaps suggesting the presence of localized underplated material. A relatively thick crust, 41.8 km, compared to surrounding stations, was found beneath the Sierra Ballena Shear Zone in the Dom Feliciano Belt. We confirm the decrease in crustal thickness when approaching the oceanic coast, reaching a Moho depth of 36.3 km in SE Uruguay. Finally, the calculated Poisson's ratio allows inferring a crust of felsic to intermediate composition beneath most of Uruguay.

Two‐dimensional SH‐wave and acoustic P‐wave full waveform inversion: A Midland Basin case study

AbstractBuilding a reliable S‐wave velocity model remains challenging from P‐wave land seismic data as multi‐parameter elastic full waveform inversion which updates P‐ and S‐wave velocities simultaneously is not yet widely adopted due to its computational cost, highly nonlinear nature and noise contamination from land seismic data. To overcome this challenge, we propose implementing the SH‐wave full waveform inversion to obtain the S‐wave velocity model. The value of this approach has been examined by applying two‐dimensional time‐domain SH‐ and P‐wave acoustic full waveform inversion to a nine‐component three‐dimensional seismic survey acquired in the Midland Basin. The nine‐component seismic survey was acquired by using both vertical and horizontal component vibrators and receivers, which enables us to apply both SH‐ and P‐wave full waveform inversion to the raw and preprocessed shot gathers along a two‐dimensional line. The SH‐ and P‐wave full waveform inversion applied to the raw shot gathers provide more detailed P‐ and S‐wave velocities compared to the velocities from the stacking velocity analysis. Additionally, there are no problematic artefacts in the inverted S‐wave velocity model, which shows the stability of the SH‐wave inversion. Through the SH‐wave full waveform inversion from the preprocessed shot gathers, we reveal the lateral velocity variations in the Grayburg–San Andres interval, which coincides with the depositional environment changes suggested by the previous regional study mainly based on well log and cores. These variations demonstrate that SH‐wave full waveform inversion can identify additional geological features that are not observed in the inverted P‐wave velocity model. The inverted P‐ and SH‐wave velocities are validated by the flattening of the events observed in the common image gathers after Kirchhoff depth migration. The SH‐wave migration image further reveals the irregular geometries of carbonates in the Spraberry formation. Vp/Vs ratios calculated from the independently inverted P‐ and S‐wave velocity models show strong lateral variations in the Wolfcamp interval (key‐producing interval), which could be caused by the organic content variations between the reservoir and non‐reservoir rocks. The inversion results demonstrate that the SH‐wave full waveform inversion can be used to provide an S‐wave velocity model that is comparable to the P‐wave velocity model derived from acoustic full waveform inversion, which is widely used for P‐wave velocity model building from P‐wave land seismic data.

Automatic stack velocity picking using a semi‐supervised ensemble learning method

AbstractPicking stack velocity from seismic velocity spectra is a fundamental method in seismic stack velocity analysis. With the increase in the scale of seismic data acquisition, manual picking cannot achieve the required efficiency. Therefore, an automatic picking algorithm is urgently needed now. Despite some supervised deep learning–based picking approaches that have been proposed, they heavily rely on sufficient training samples and lack interpretability. In contrast, utilizing physical knowledge to develop semi‐data‐driven methods has the potential to efficiently solve this problem. Thus, we propose a semi‐supervised ensemble learning method to reduce the reliance on manually labelled data and improve interpretability by incorporating the interval velocity constraint. Semi‐supervised ensemble learning fuses the information of the estimated spectrum, nearby velocity spectra and few‐shot manual picking to recognize the velocity picking. Test results of both the synthetic and field datasets indicate that semi‐supervised ensemble learning achieves more reliable and precise picking than traditional clustering‐based techniques and the currently popular convolutional neural network method.

Study Experimental of Honda Astrea Grand Performance Modification Intake Manifold Using Velocity Stack Dimple 1mm with Variation Diameter Inlate 60, 70, and 80mm

The Velocity Stack Intake is a trumpet-shaped device that enhances the combustion process by allowing air to enter the intake manifold at high velocity, reducing turbulence. This study investigated the impact of velocity stack intake on vehicle performance by changing the inlet radius to produce a more focused airflow. The optimization aimed to find the maximum diameter of the velocity stack intake to achieve maximum results. The results showed that the maximum torque, power, and specific fuel consumption occurred at a Diameter of 80mm.

Prediction of Reflection Seismic Low-Frequency Components of Acoustic Impedance Using Deep Learning

The unreliable prediction of the low-frequency components from inverted acoustic impedance causes uncertainty in quantitative seismic interpretation. To address this issue, we first calculate various seismic and geological attributes that contain low-frequency information, such as relative geological age, interval velocity, and integrated instantaneous amplitude. Then, we develop a method to predict the low-frequency content of seismic data using these attributes, their high-frequency components, and recurrent neural networks. Next, we test how to predict the low-frequency components using stacking velocity obtained from velocity analysis. Using all the attributes and seismic data, we propose a supervised deep learning method to predict the low-frequency components of the inverted acoustic impedance. The results obtained in both synthetic and real data cases show that the proposed method can improve the prediction accuracy of the low-frequency components of the inverted acoustic impedance, with the best improvement in a real data example of 57.7% compared with the impedance predicted using well-log interpolation.

Seismic forward modeling for investigating and interpreting thin beds in a carbonate reservoir in SW Iran

High-frequency contents of reflections are essential in the investigation and interpretation of thin-bed reservoirs. These beds can be even more complicated in carbonate rocks, as pore geometries influence final seismic responses. To address these complexities, we propose a seismic forward modeling workflow to investigate several thin-bed reservoirs in a carbonate oilfield with variable pore geometries. The new workflow enhances the existing forward models for the investigation of thin beds by integrating seismic petrophysics, geological model building, and 2D finite-difference elastic modeling. We used seismic petrophysics to ensure the consistency between petrophysical well logs and seismic data using rock physics modeling. Then, we introduced a new high-resolution workflow for velocity modeling to build a reliable geological model. Finally, the 2D finite-difference elastic modeling is employed to generate synthetic traces based on our geological model to obtain seismic responses for the existing thin-bed reservoirs. The forward models used in this study are a powerful tool for investigating thin layers because they enable high-resolution investigation of the given geological model in distinguishing lateral and vertical lithofacies changes. The new velocity modeling workflow, implemented in this research, is more reliable and effective than the conventional velocity property modeling approaches, which resulted in synthetic seismic sections with increased lateral and vertical resolutions and enhanced data from a thin bed. The main features of this workflow are the incorporation of well-log data into geological model building, combining the high-resolution data of horizontal seismic stacking velocity with vertical well logging, and the incorporation of a residual model to improve the seismic stacking velocity. We produced a more coherent section resembling the acquired 3D seismic data by applying the proposed workflow to data from an oil carbonate reservoir in the Fahliyan Formation within the Abadan Plain in SW Iran. It is concluded that the higher frequency synthetic sections from the proposed workflow can assist in resolving the seismic interpretation challenges. By applying the proposed workflow to the current data set, four thin-bed carbonate reservoirs were investigated with corresponding thicknesses of approximately 25, and 17 m at peak frequencies of 60, and 90 Hz, respectively.

Detection of Interstellar E-1-cyano-1,3-butadiene in GOTHAM Observations of TMC-1

We report the detection of the lowest-energy conformer of E-1-cyano-1,3-butadiene (E-1-), a linear isomer of pyridine, using the fourth data reduction of the GBT Observations of TMC-1: Hunting for Aromatic Molecules (GOTHAM) deep spectral survey toward TMC-1 with the 100 m Green Bank Telescope. We perform velocity stacking and matched-filter analyses using Markov chain Monte Carlo simulations and find evidence for the presence of this molecule at the 5.1σ level. We derive a total column density of cm−2, which is predominantly found toward two of the four velocity components we observe toward TMC-1. We use this molecule as a proxy for constraining the gas-phase abundance of the apolar hydrocarbon 1,3-butadiene. Based on the three-phase astrochemical modeling code NAUTILUS and an expanded chemical network, our model underestimates the abundance of cyano-1,3-butadiene by a factor of 19, with a peak column density of 2.34 × 1010 cm−2 for 1,3-butadiene. Compared to the modeling results obtained in previous GOTHAM analyses, the abundance of 1,3-butadiene is increased by about two orders of magnitude. Despite this increase, the modeled abundances of aromatic species do not appear to change and remain underestimated by one to four orders of magnitude. Meanwhile, the abundances of the five-membered ring molecules increase proportionally with 1,3-butadiene by two orders of magnitude. We discuss the implications for bottom-up formation routes to aromatic and polycyclic aromatic molecules.

Automatic velocity analysis with physics-constrained optimal surface picking

Stacking velocity is generally obtained by picking the energy peaks in velocity semblance which can be time consuming when performed manually. Numerous automatic methods have been proposed for accelerating the velocity picking but often generate physically unreasonable picking results when strong and spatially consistent energy anomalies (due to noise and multiples) appear in the semblance map. We develop a constrained optimal surface picking method to automatically pick a 2D velocity field from a 3D semblance volume with high efficiency and robustness. This method is improved from the 2D dynamic programming algorithm by incorporating vertical physical constraints in the time direction and lateral smoothness constraints in the common-midpoint (CMP) direction. The time-direction physical constraint ensures that the picked velocity is positive when converted to an interval velocity, whereas the CMP-direction smoothness constraint ensures that the picked 2D velocity field is laterally continuous. Tests on the Marmousi-2 model indicate that our constrained optimal surface picking algorithm improves the spatial structure consistency of the picked velocity field and is able to robustly avoid picking the strong and consistent energy features generated in the semblance volume by multiples. We further determine the robustness of our method in a 2D real data example by comparing our automatic picking from a 3D semblance volume with a result that is manually picked from individual 2D semblance slices. The comparison indicates that the general trend of our result is consistent with the manual picking and our result looks geologically more reasonable in detail and generates a better stacking image with improved, focused, and more continuous reflections.

Characterization of the turbulent field behavior of an elevated jet-in crossflow investigated using direct numerical simulation

Direct numerical simulation (DNS) of a turbulent flow in an elevated jet in crossflow has been carried out at a Reynolds number (Re) of 3500 based on the outer width of the stack and crossflow velocity. The jet to crossflow velocity ratio is kept constant at VR=2. Second order spatial and temporal discretization have been used to solve the Navier–Stokes equations employing a high-resolution grid to determine the essential characteristics of the coherent and the incoherent flow fields accurately. The large-scale coherent and small-scale incoherent flow fields are extracted using a reference signal-based phase-averaged method that uses a reference signal against which the phases are identified in each cycle to minimize the phase jitter. The rate of decay of circulation of the stack-wake vortices is observed to be more than that of the jet-wake which has a lower circulation value. The contribution of the incoherent fluctuations to the total turbulent kinetic energy is more compared to its coherent counterpart in the wake as well as jet region, except for the near-wake of the stack. The normal and shear stresses of both coherent and incoherent fields reveal a relatively higher contribution in the near-wake of both stack-wake and jet-wake, while the far-wake shows the opposite trend. The anisotropy factor of both the large-scale coherent and the small-scale fluctuating fields provides the evidence of total anisotropy of the stack-wake. The characterization of both types of fluctuating fields is also carried out using the anisotropy-invariant-map which displays the one-component limit for the coherent fluctuating field in most of the regions, but the anisotropy state of the incoherent fluctuating field is found to switch among various limits, namely, the axisymmetric contraction, the axisymmetric expansion, and isotropic limits.

Investigation of fractured carbonate reservoirs by applying shear-wave splitting concept

In this study, fracture orientations in carbonate reservoirs were determined using a multicomponent velocity analysis based on shear wave splitting. The analysis is based on the estimated velocities of large seismic events with different polarizations. In a fractured zone with a dominant orientation, weak amplitude split shear events, including shear noise, result in shear waves that are polarized toward the symmetry and anisotropy axes and propagate with a common fast and slow velocity, respectively. Thus, a velocity stack should show high coherency anomalies in directions parallel and orthogonal to the fracture strike. Furthermore, because the analysis is applied locally at a specific depth range, it is less susceptible to the effects of overburden anisotropy and noise. The dominant fracture orientations from carbonate reservoirs of four oilfields were compared to those interpreted from fullbore microimager and core data. Fractures in two offshore reservoirs strike NNE-SSW and NW-SE, which are related to Zagros stress. Fractures in two onshore reservoir strikes NE-SW, while in deeper onshore reservoir fractures are aligned with N-S direction. The findings of this study are promising, particularly for the fractured reservoirs especially those located in Abu Dhabi, which are characterized by high heterogeneity and complex fracture network related to complex tectonic history. In order to obtain geometrical parameters of fractures at seismic scale, it is recommended to implement the analysis adapted in this study after acquiring three component zero-offset vertical seismic profiling. Cited as: Diaz-Acosta, A., Bouchaala, F., Kishida, T., Jouini, M. S., Ali, M. Y. Investigation of fractured carbonate reservoirs by applying shear-wave splitting concept. Advances in Geo-Energy Research, 2023, 7(2): 99-110. https://doi.org/10.46690/ager.2023.02.04

Feasibility of Using Isokinetic Sampling Techniques to Extract a Representative Sample from Processes in the United Kingdom

The requirement to monitor and control particulate emissions from industrial processes using continuous emission monitoring systems (CEMS) has significantly increased over recent years. Under current legislation, CEMS equipment requires calibration against the standard reference method (SRM) using isokinetic sampling and gravimetric analysis under controlled conditions as detailed through BS EN 13284-1 “Stationary source emissions–Determination of low range mass concentration of dust. Manual gravimetric method”. This process includes pumping a known volume of gas through a filter, which is weighed before and after sampling, and the total mass of dust per m3 can then be calculated to output results in mg/m3. As tougher legislation is introduced and stringent emission limit values (ELVs) are imposed on emissions processes in the United Kingdom (UK), the calibration of CEMS is increasingly more difficult due to the reliability of the SRM at low concentrations. The accuracy of results from the SRM and therefore CEMS equipment must be questioned when the uncertainty of measurement is higher than process ELVs. This research analyses data taken from an industrial survey and 21 UK processes where the standard reference method, in accordance with the procedure in BS EN 13284-1 has been used for particulate measurement. Investigating the reliability of isokinetic sampling when used as a method to extract a representative sample from a stack process when used in conjunction with innovative, alternative methods of sample analysis. In processes with particulate emissions <5 mg/m3, 80.7% of the total sample was collected in the rinse, and for processes >5 mg/m3, 56.4% of the sample was collected in the rinse. The data does not suggest any correlation between any of the measured parameters and the percentage of particulate in the rinse, including the stack velocity, isokinetic percentage, sample volume, and total mass concentration.

The effects of receiver arrangement on velocity analysis with multi‐concurrent receiver GPR data

AbstractDetermining subsurface electromagnetic (EM) wave velocity is critical for ground‐penetrating radar (GPR) data analysis, as velocity is used for the time‐to‐depth conversion, and hence leads to obtaining the precise location of the objects of interest. Currently, the way to acquire detailed subsurface EM wave velocity models involves employing multi‐offset GPR surveys, such as wide‐angle reflection‐refraction (WARR), in conjunction with normal moveout (NMO) based velocity analysis. Traditionally, these surveys are carried out using two separate transducers and were, therefore, time‐consuming and had limited uptake. Recent advances in GPR hardware have allowed the development of novel systems with multi‐concurrent sampling receivers, which enable rapid and dense acquisition of WARR data. These additional receivers increase the overall size, weight and cost of the system. Therefore, we investigated the effects of receiver arrangement on NMO‐based velocity analysis and considered reducing the overall number of transducers, whilst maintaining satisfactory velocity spectra resolution and, hence, obtaining detailed stacking velocity models as well as improved stacked reflection sections. We used both simulated data from complex three‐dimensional models as well as field data and examined different numbers and positions of receivers in different environments. Our results show that velocity spectra resolution can be maintained within acceptable limits whilst reducing the number of receivers from a configuration with seven equally spaced receivers, to a sparse configuration of four receivers. Thus, being able to decrease the number of receivers used by these new GPR systems will reduce both the total system weight and cost and, hopefully, increase their adoption for GPR surveys.

Application of High-Resolution Face Recognition and EDF Image Reconstruction in English Classroom Teaching

This study examines classroom monitoring in order to increase the effectiveness of English classroom instruction. This article uses high-resolution algorithms and EDF image reconstruction technology in the English classroom education system to improve the high resolution of students’ faces. This work presents a fast pixel capture function to enhance the rapid video capture function. The stack velocity picking of the speed spectrum is the most important aspect of velocity analysis. To create successful changes to the algorithm, this method often employs optimization algorithms as a way of stack velocity choosing speed. Finally, based on algorithm improvements, this study builds the system structure and develops simulation tests to validate system performance. The English classroom teaching system created in this work can properly determine the real-time status of students by facial recognition and has excellent user satisfaction, indicating that it may effectively increase the teaching impact, according to experimental research.

Development of a workflow for processing ground-penetrating radar data from multiconcurrent receivers

Ground-penetrating radar (GPR) systems with multiconcurrent sampling receivers can rapidly acquire dense multioffset GPR data, which are not feasible using typical common-offset (CO) GPR systems with a single fixed offset transmitter-receiver pair. Multioffset GPR data from these new multiconcurrent receiver systems have the potential to be used to create detailed subsurface velocity models and enhanced reflection sections. These are important features that can improve qualitative and quantitative interpretation of GPR data. To realize these benefits and to deal with the large amount of multioffset data generated by these new systems, we have developed an automated and customized data processing workflow. There are three key algorithms that we have developed as part of our workflow, which is crucial for processing large volume, multioffset GPR data so as: first, to efficiently correct and manage time misalignments from multiconcurrent receivers; second, to carry out trace balancing of common-midpoint data for semblance analysis; and third, to automate the velocity analysis step. We showcase our processing workflow using two field data sets acquired using a multiconcurrent sampling receiver GPR system consisting of one transmitter and seven receivers. The field data were collected at two different locations: a site using a system with a 500 MHz center frequency and another site using a system with a 1000 MHz center frequency. We have determined, with both data sets, that our processing workflow could produce automated stacking velocity fields and enhanced zero-offset reflection cross sections. These benefits increase the information that can be used for interpretation (compared with conventional CO data) and can form the basis of further processing steps such as migration. As the cost of these multiconcurrent sampling receiver systems decreases over time, we anticipate their use, and the acquisition of dense multioffset GPR data, to become much more commonplace.

Automatic Velocity Picking Using a Multi-Information Fusion Deep Semantic Segmentation Network

Velocity picking, a critical step in seismic data processing, has been studied for decades. Although manual picking can produce accurate normal moveout (NMO) velocities from the velocity spectra of prestack gathers, it is time-consuming and becomes infeasible with the emergence of large amount of seismic data. Numerous automatic velocity picking methods have thus been developed. In recent years, deep learning (DL) methods have produced good results on the seismic data with medium and high signal-to-noise ratios (SNR). Unfortunately, it still lacks a picking method to automatically generate accurate velocities in the situations of low SNR. In this paper, we propose a multi-information fusion network (MIFN) to estimate stacking velocity from the fusion information of velocity spectra and stack gather segments (SGS). In particular, we transform the velocity picking problem into a semantic segmentation problem based on the velocity spectrum images. Meanwhile, the information provided by SGS is used as a prior in the network to assist segmentation. The experimental results on two field datasets show that the picking results of MIFN are stable and accurate for the scenarios with medium and high SNR, and it also performs well in low SNR scenarios.

Detecting and locating microseismic events with stacking velocity analysis for surface monitoring

Microseismic surface monitoring may suffer from the signal-to-noise ratio (SNR) in the data and lack of datasets to constrain a realistic velocity model. Therefore, an 1D depth velocity, which is derived from the well log and calibrated with perforation shot, is commonly utilized in microseismic monitoring. In this study, we simultaneously detect and locate microseismic events by applying a stacking method without using a depth velocity model. Since the 1D layered velocity model could be approximately equivalent to a RMS velocity, we borrow the velocity analysis concept in traditional exploration seismic data processing and apply it on mocroseismic surface monitoring. We stack the perforation shot waveform along a hyperbolic curve and pick the maximum stacking energy to obtain a stacking velocity above the target zone. The microseismic events are automatically detected and located by a stacking procedure with the known stacking velocity in time domain. The events are then converted from time to depth using the average velocity calculated from the perforation shot. Synthetic examples show that our approach can successfully recover the true locations of events with a large amount of noises added to the data. The real data results also suggest that this method is applicable for effectively detecting and locating events with low SNR. Although the approach with stacking velocity is limited to the layered media, this restriction is acceptable for many unconventional reservoirs.

An Investigation of Seismic Velocity Variation through a Tectonic Boundaries-Case Study in Central Iraq

A 3D velocity model was created by using stacking velocity of 9 seismic lines and average velocity of 6 wells drilled in Iraq. The model was achieved by creating a time model to 25 surfaces with an interval time between each two successive surfaces of about 100 msec. The summation time of all surfaces reached about 2400 msec, that was adopted according to West Kifl-1 well, which penetrated to a depth of 6000 m, representing the deepest well in the study area. The seismic lines and well data were converted to build a 3D cube time model and the velocity was spread on the model. The seismic inversion modeling of the elastic properties of the horizon and well data was applied to achieve a corrected velocity cube. Then, the velocity cube was converted to a time model and, finally, a corrected 3D depth model was obtained. This model shows that the western side of the study area, which is a part of the stable shelf, is characterized by relatively low thickness and high velocity layers. While the eastern side of the study area, which is a part of the Mesopotamian, is characterized by high thickness and low velocity of the Cretaceous succession. The Abu Jir fault is considered as a boundary between the stable and unstable shelves in Iraq, situated at the extreme west part of the study area. The area of relatively high velocity gradient is considered as the limit of the western side of the Mesopotamian basin. This area extends from Najaf-Karbala axis in the west to the Euphrates River in the east. It is found that the 3D stacking velocity model can be used to obtain good results concerning the tectonic boundary.

Geometry of the Décollement Below Eastern Bangladesh and Implications for Seismic Hazard

AbstractEastern Bangladesh sits on the seismically active Chittagong‐Myanmar fold and thrust belt (CMFB), a north‐trending accretionary wedge on the eastern side of the India‐Eurasia collision. Earthquakes on the basal décollement and associated thrusts within the CMFB present a hazard to this densely populated region. In this study, we interpret 28 seismic reflection profiles from both published and unpublished sources to constrain the depth of the basal décollement. To convert profiles from the time domain to the depth domain, we integrate sonic log and seismic stacking velocity data to generate time‐velocity relationships for different parts of the CMFB. Our analysis reveals that the décollement is ∼9 km deep in northeast and southeast Bangladesh, but shallows to ∼5 km in east‐central Bangladesh. The décollement has an area of 7.25 × 104 km2 (∼150 × 450 km), making it capable of an Mw 8.5 earthquake. However, the warped geometry of this fault might act as a rupture barrier were a large earthquake to occur on the décollement. Our combined velocity and fault model lay the groundwork for future studies to address seismic segmentation, ground shaking, and rupture modeling in the CMFB. Finally, we use our compiled data set to analyze the evolution of fold kinematics in the CMFB. We observe that folding style and failure mode varies, from mainly ductile deformation in the foreland to mainly brittle in the hinterland. The dual‐failure modes within the CMFB support the hypothesis that a region with ductile deformation may still be capable of seismic behavior.

Comparison of velocity models computed using different velocity variants and algorithms on a 2D seismic profile for poststack time migration

This article presents a construction method of the velocity field for poststack time migration for 2D seismic calculated on the basis of interval velocities in boreholes and structural interpretation, as well as the results of poststack time migration based on this solution. Three velocity field models have been developed. The models used differ in the way of spatial interpolation and extrapolation in the adopted calculation grid in the depth domain, which was created on the basis of a structural interpretation of 2D seismic profiles. Three methods of interpolation and extrapolation were used: Gaussian distribution, kriging and moving average. The spatial distribution of the interval velocities in the boreholes was made using the Petrel software by Schlumberger. The interval velocities along the analyzed seismic profile were extracted from the computed spatial interval velocity models, and after conversion from the depth to the time domain, they were used for the poststack time migration. For comparison, poststack time migration was calculated for the same seismic profile based on the stacking velocities obtained in the seismic processing data as a result of velocity analyzes. The velocity field calculated on the basis of interval velocities and structural interpretation was used for the poststack time migration procedure performed with the Implicit FD Time Migration algorithm (finite difference), while the stacking velocities were used for the poststack time migration procedure performed with the Stolt and Kirchhoff algorithms in accordance with the technical conditions of correct operation of these algorithms. The selected percentage ranges of 60%, 100%, and 140% have been used for all velocity fields. Application of the element of directional velocity variation resulting from the spatial distribution of interval velocities in the boreholes to the velocity field for the poststack time migration allowed to obtain a better seismic image in relation to the one obtained as a result of applying the stacking velocities. The most reliable seismic image after poststack time migration was obtained for the velocity field calculated on the basis of the interval velocities with Gaussian distribution, using the finite difference algorithm with 60 percent value of the velocity field.