Seismicity Pattern, Reference Velocity Model, and Earthquake Mechanics of South India

Image-wave propagation or velocity continuation describes the variation of the migrated position of a seismic event as a function of migration velocity. Image-wave propagation in the common-image gather (CIG) domain can be combined with residual-moveout analysis for iterative migration velocity analysis (MVA). Velocity continuation of CIGs leads to a detection of those velocities in which events flatten. Although image-wave continuation is based on the assumption of a constant migration velocity, the procedure can be applied in inhomogeneous media. For this purpose, CIGs obtained by migration with an inhomogeneous macrovelocity model are continued starting from a constant reference velocity. The interpretation of continued CIGs, as if they were obtained from residual migrations, leads to a correction formula that translates residual flattening velocities into absolute time-migration velocities. In this way, the migration velocity model can be improved iteratively until a satisfactory result is reached. With a numerical example, we found that MVA with iterative image continuation applied exclusively to selected CIGs can construct a reasonable migration velocity model from scratch, without the need to build an initial model from a previous conventional normal-moveout/dip-moveout velocity analysis.

Download Full-text

Nonlinear velocity inversion by a two‐step Monte Carlo method.

Geophysics ◽

10.1190/1.1443618 ◽

1994 ◽

Vol 59 (4) ◽

pp. 577-590 ◽

Cited By ~ 38

Author(s):

Side Jin ◽

Raul Madariaga

Keyword(s):

Monte Carlo ◽

Velocity Model ◽

Small Scale ◽

Inversion Method ◽

Nonlinear Inversion ◽

Ray Theory ◽

Data Set ◽

Seismic Reflection Data ◽

Velocity Models ◽

Reference Velocity

Seismic reflection data contain information on small‐scale impedance variations and a smooth reference velocity model. Given a reference velocity model, the reflectors can be obtained by linearized migration‐inversion. If the reference velocity is incorrect, the reflectors obtained by inverting different subsets of the data will be incoherent. We propose to use the coherency of these images to invert for the background velocity distribution. We have developed a two‐step iterative inversion method in which we separate the retrieval of small‐scale variations of the seismic velocity from the longer‐period reference velocity model. Given an initial background velocity model, we use a waveform misfit‐functional for the inversion of small‐scale velocity variations. For this linear step we use the linearized migration‐inversion method based on ray theory that we have recently developed with Lambaré and Virieux. The reference velocity model is then updated by a Monte Carlo inversion method. For the nonlinear inversion of the velocity background, we introduce an objective functional that measures the coherency of the short wavelength components obtained by inverting different common shot gathers at the same locations. The nonlinear functional is calculated directly in migrated data space to avoid expensive numerical forward modeling by finite differences or ray theory. Our method is somewhat similar to an iterative migration velocity analysis, but we do an automatic search for relatively large‐scale 1-D reference velocity models. We apply the nonlinear inversion method to a marine data set from the North Sea and also show that nonlinear inversion can be applied to realistic scale data sets to obtain a laterally heterogeneous velocity model with a reasonable amount of computer time.

Download Full-text

Reference P-wave velocity in coal seams at great depths in Jastrzebie coal mine

E3S Web of Conferences ◽

10.1051/e3sconf/201913301011 ◽

2019 ◽

Vol 133 ◽

pp. 01011

Author(s):

Jakub Kokowski ◽

Zbigniew Szreder ◽

Elżbieta Pilecka

Keyword(s):

Wave Velocity ◽

Coal Mine ◽

Velocity Model ◽

P Wave ◽

Coal Seams ◽

Data Set ◽

Seismic Profiling ◽

Reference Velocity ◽

P Wave Velocity ◽

Geological Conditions

In the study, the determining of the reference velocity of the P-wave in coal seams used in seismic profiling to assess increases and decreases in relative stresses at large depths has been presented. The seismic profiling method proposed by Dubinski in 1989 covers a range of depth up to 970 m. At present, coal seams exploitation in Polish coal mines is conducted at greater depths, even exceeding 1200 m, which creates the necessity for a new reference velocity model. The study presents an empirical mathematical model of the change of the P-wave velocity in coal seams in the geological conditions of the Jastrzebie coal mine. A power model analogous to the Dubinski’s one was elaborated with new constants. The calculations included the results from 35 measurements of seismic profiling carried out in various coal seams of the Jastrzebie mine at depths from 640 to 1200 m. The results obtained cause changes in the result of calculations of seismic anomalies. Future validation of the proposed model with larger data set will be required.

Download Full-text

Relocation of seismicity of the Pannonian Basin using the Bayesloc multiple event location algorithm between 1996 and 2019

10.5194/egusphere-egu2020-16663 ◽

2020 ◽

Author(s):

Barbara Czecze ◽

István Bondár

Keyword(s):

Pannonian Basin ◽

Ground Truth ◽

Velocity Model ◽

Measure Data ◽

Seismic Events ◽

Seismicity Pattern ◽

Statistical Framework ◽

Event Location ◽

Location Algorithm ◽

Location Methods

The objective of this work was to relocate the entire seismicity of the Pannonian Basin with the Bayesloc algorithm, a Markov-Chain Monte Carlo inversion scheme using a Bayesian statistical framework.In the Hungarian National Seismological Bulletin the magnitudes and event locations are determined with the iLoc location algorithm using the 3D global RSTT velocity model, and we used these locations as initial coordinates. In our work, we have used all of the instrumentally registered seismic events between 1996 and 2019 in the Pannonian Basin.During data preprocessing we used graph theory to measure data connectivity. Similar to all multiple-event location methods, Bayesloc performs better when events are recorded on a common network. We used several hundreds of ground truth events (quarry blasts, mine explosions, earthquakes) to tie down the seismicity pattern to known ground truth locations by giving them tighter prior distributions.Based on the day-time peak on the origin-hour distribution of the bulletin earthquakes we assume that there are anthropogenic events labeled as earthquakes in the catalog, therefore we created a &#8222;Suspected explosions (SX)&#8221; group to set prior constrains.The results show that the events around the mines are dramatically better clustered. The prior constraints contributed remarkably to the outcome of the relocation. We show that the results present an improved view of the seismicity of the region.

Download Full-text

Reconstructing the primary reflections in seismic data by Marchenko redatuming and convolutional interferometry

Geophysics ◽

10.1190/geo2015-0377.1 ◽

2016 ◽

Vol 81 (2) ◽

pp. Q15-Q26 ◽

Cited By ~ 29

Author(s):

Giovanni Angelo Meles ◽

Kees Wapenaar ◽

Andrew Curtis

Keyword(s):

Velocity Model ◽

Reverse Time ◽

Reverse Time Migration ◽

Data Set ◽

Seismic Reflection Data ◽

Surface Reflection ◽

Reflection Data ◽

Reference Velocity ◽

Time Migration ◽

Recorded Data

State-of-the-art methods to image the earth’s subsurface using active-source seismic reflection data involve reverse time migration. This and other standard seismic processing methods such as velocity analysis provide best results only when all waves in the data set are primaries (waves reflected only once). A variety of methods are therefore deployed as processing to predict and remove multiples (waves reflected several times); however, accurate removal of those predicted multiples from the recorded data using adaptive subtraction techniques proves challenging, even in cases in which they can be predicted with reasonable accuracy. We present a new, alternative strategy to construct a parallel data set consisting only of primaries, which is calculated directly from recorded data. This obviates the need for multiple prediction and removal methods. Primaries are constructed by using convolutional interferometry to combine the first-arriving events of upgoing and direct-wave downgoing Green’s functions to virtual receivers in the subsurface. The required upgoing wavefields to virtual receivers are constructed by Marchenko redatuming. Crucially, this is possible without detailed models of the earth’s subsurface reflectivity structure: Similar to the most migration techniques, the method only requires surface reflection data and estimates of direct (nonreflected) arrivals between the virtual subsurface sources and the acquisition surface. We evaluate the method on a stratified synclinal model. It is shown to be particularly robust against errors in the reference velocity model used and to improve the migrated images substantially.

Download Full-text

2403 A Reference Velocity Model in Passing Non-signalized Intersections Based on Urban Road Driving Database

The Proceedings of the Transportation and Logistics Conference ◽

10.1299/jsmetld.2015.24._2403-1_ ◽

2015 ◽

Vol 2015.24 (0) ◽

pp. _2403-1_-_2403-9_

Author(s):

Yusuke SHIOKAWA ◽

Yasuhiro AKAGI ◽

Keyword(s):

Velocity Model ◽

Signalized Intersections ◽

Urban Road ◽

Reference Velocity

Download Full-text

2D High-Resolution Crosswell Seismic Traveltime Tomography

Journal of Environmental and Engineering Geophysics ◽

10.2113/jeeg19-003 ◽

2020 ◽

Vol 25 (1) ◽

pp. 47-53

Author(s):

Chuan Li ◽

JianXin Liu ◽

Jianping Liao ◽

Andrew Hursthouse

Keyword(s):

High Resolution ◽

Eastern China ◽

Velocity Model ◽

Well Logging ◽

Oil Field ◽

Traveltime Tomography ◽

Reference Velocity ◽

Velocity Information ◽

High Resolution Reconstruction

This paper presents a method for combining the hybrid eikonal solver and the prior velocity information to obtain high-resolution crosswell imaging. The hybrid eikonal solver in this technique can ensure rapid and reliable forward modeling of traveltime field in an unsmoothed velocity model. We also utilize the sonic well logging curve to properly develop an initial reference velocity model, and use the sonic well logging data as the prior information for the inversion part, which can restrict the problem of non-uniqueness. The results of the numerical experiment of traveltime in multi-layer media showed that the hybrid eikonal solver was more accurate than the finite difference method. The case study of an oil field in eastern China demonstrated that our method can derive a high-resolution reconstruction of the subsurface structure by inverting the primary traveltime datasets. These results suggest that even though the eikonal equation is a high frequency approximation to the wavefield, the hybrid eikonal solver can provide an accurate traveltime field in the forward modelling step of seismic crosswell tomography, which is critical to ensure high-resolution invert imaging in a highly heterogeneous environment.

Download Full-text

Reference velocity model estimation from prestack waveforms: Coherency optimization by simulated annealing

Geophysics ◽

10.1190/1.1442741 ◽

1989 ◽

Vol 54 (8) ◽

pp. 984-990 ◽

Cited By ~ 67

Author(s):

Evgeny Landa ◽

Wafik Beydoun ◽

Albert Tarantola

Keyword(s):

Monte Carlo ◽

Simulated Annealing ◽

Velocity Model ◽

Monte Carlo Step ◽

Lateral Velocity ◽

Seismic Waveforms ◽

Reference Velocity ◽

Velocity Information ◽

Zero Offset ◽

Annealing Method

Coherency inversion, which consists of maximizing a semblance function calculated from unstacked seismic waveforms, has the potential of estimating reliable velocity information without requiring traveltime picking on unstacked data. In this work, coherency inversion is based on the assumption that reflectors’ zero‐offset times are known and that the velocity in each layer may vary laterally. The method uses a type of Monte Carlo technique termed the generalized simulated annealing method for updating the velocity field. At each Monte Carlo step, time‐to‐depth conversion is performed. Although this procedure is slow at convergence to the global minimum, it is robust and does not depend on the initial model or topography of the objective function. Applications to both synthetic and field data demonstrate the efficiency of coherency inversion for estimating both lateral velocity variations and interface depth positions.

Download Full-text

Imaging vertical interfaces using acoustic time reversal

Geophysics ◽

10.1190/geo2018-0135.1 ◽

2019 ◽

Vol 84 (3) ◽

pp. Q1-Q11 ◽

Cited By ~ 3

Author(s):

Satyan Singh ◽

Andrew Curtis

Keyword(s):

Seismic Velocity ◽

Velocity Model ◽

Image Point ◽

Small Scale ◽

Wave Interactions ◽

Seismic Surveys ◽

Reference Velocity ◽

Novel Approach ◽

Event Location ◽

Imaging Artifacts

We have developed a novel approach to image vertical structures using multiply scattered waves. This method requires only a smooth seismic velocity model and data recorded at the surface. Previous methods to image near-vertical interfaces or faults using migration methods all require prior information about small-scale details in the seismic velocity model to infer the locations of multiple-scattering wave interactions. We used waves that had their last scattering interaction with near-vertical interfaces, while their other scattering points might be anywhere in the earth, including at the free surface. Our algorithm then images the final scattering point using a time-reversed mirror-style imaging condition, so we refer to the method as time-reversed mirror imaging. Artifacts in the images produced have clear causes and can be filtered out by stacking over shots and including contributions from multiples. Our numerical examples demonstrate the successful application of the method for staircase structures and a section of the Marmousi model. They also reveal a new way to diagnose errors in the smooth or reference velocity model used. In addition, our method can be used to image point scatterers in active seismic surveys or for event location in passive surveys.

Download Full-text