Some results of seismic travel-time reflection tomography study

Velocity model is essential for seismic data processing as it plays an important role in migration processes as well as time depth conversion. There are several techniques to reach that goal, among which tomographic inversion is an efficient one. As an upgrade version of handpicked velocity analysis, the tomography technique is based on the reflection ray tracing and conjugate gradient method to estimate an optimum velocity model and can create an initial high quality model for other intensive imaging and modelling module such as reverse-time migration (RTM) and full-waveform inversion (FWI). For the mentioned benefit, we develop a seismic travel-time reflection tomography (SeisT) module to study the accuracy of the approach along with building the technical capability in seismic processing. The accuracy of the module has been tested by both synthetic and real seismic field data; the efficiency and the accuracy of the model have been proven in terms of development method as well as field data application.

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3D high-resolution seismic imaging of the iron-oxide deposits in Ludvika (Sweden) using full-waveform inversion and reverse-time migration

10.5194/se-2021-122 ◽

2021 ◽

Author(s):

Brij Singh ◽

Michał Malinowski ◽

Andrzej Górszczyk ◽

Alireza Malehmir ◽

Stefan Buske ◽

...

Keyword(s):

Waveform Inversion ◽

Velocity Model ◽

Mine Planning ◽

Full Waveform Inversion ◽

Reverse Time ◽

Reverse Time Migration ◽

Depth Imaging ◽

Velocity Models ◽

Full Waveform ◽

Time Migration

Abstract. A sparse 3D seismic survey was acquired over the Blötberget iron-oxide deposits of the Ludvika Mines in south-central Sweden. The main aim of the survey was to delineate the deeper extension of the mineralisation and to better understand its 3D nature and associated fault systems for mine planning purposes. To obtain a high-quality seismic image in depth, we applied time-domain 3D acoustic full-waveform inversion (FWI) to build a high-resolution P-wave velocity model. This model was subsequently used for pre-stack depth imaging with reverse time migration (RTM) to produce the complementary reflectivity section. We developed a data preprocessing workflow and inversion strategy for the successful implementation of FWI in the hardrock environment. We obtained a high-fidelity velocity model using FWI and assessed its robustness. We extensively tested and optimised the parameters associated with the RTM method for subsequent depth imaging using different velocity models: a constant velocity model, a model built using first-arrival traveltime tomography and a velocity model derived by FWI. We compare our RTM results with a priori data available in the area. We conclude that, from all tested velocity models, the FWI velocity model in combination with the subsequent RTM step, provided the most focussed image of the mineralisation and we successfully mapped its 3D geometrical nature. In particular, a major reflector interpreted as a cross-cutting fault, which is restricting the deeper extension of the mineralisation with depth, and several other fault structures which were earlier not imaged were also delineated. We believe that a thorough analysis of the depth images derived with the combined FWIRTM approach that we presented here can provide more details which will help with better estimation of areas with high mineralization, better mine planning and safety measures.

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Simultaneous reverse time migration of primaries and free-surface related multiples without multiple prediction

Geophysics ◽

10.1190/geo2012-0450.1 ◽

2014 ◽

Vol 79 (1) ◽

pp. S1-S9 ◽

Cited By ~ 23

Author(s):

Yibo Wang ◽

Xu Chang ◽

Hao Hu

Keyword(s):

Free Surface ◽

Field Data ◽

Synthetic Data ◽

Velocity Model ◽

Reverse Time ◽

Reverse Time Migration ◽

Data Set ◽

Imaging Condition ◽

Time Migration ◽

Multiple Prediction

Prestack reverse time migration (RTM) is usually regarded as an accurate imaging tool and has been widely used in exploration. Conventional RTM only uses primaries and treats free-surface related multiples as noise; however, free-surface related multiples can sometimes provide extra illumination of the subsurface, and this information could be used in migration procedures. There are many migration methods using free-surface related multiples, but most approaches need to predict multiples, which is time consuming and prone to error. We discovered a new RTM approach that uses the primaries and the free-surface related multiples simultaneously. Compared with migration methods that only use free-surface related multiples, the proposed approach can provide comparable migration results and does not need multiple predictions. In our approach, the source function in conventional RTM was replaced with recorded field data including primaries and free-surface related multiples, together with a synthetic wavelet; the back-propagated primaries in the conventional RTM were replaced with complete recorded field data. The imaging condition of the proposed approach was the same as the crosscorrelation imaging condition of conventional RTM. A three-layer velocity model with scatterers and the Sigsbee 2B synthetic data set were used for numerical experiments. The numerical results showed that the proposed approach can cover a wider range of the subsurface and provide better illumination compared with conventional RTM. The proposed approach was easy to implement and avoided tedious multiple prediction; it might be significant for general complex subsurface imaging.

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Multiscale reflection phase inversion with migration deconvolution

Geophysics ◽

10.1190/geo2018-0751.1 ◽

2020 ◽

Vol 85 (1) ◽

pp. R55-R73 ◽

Cited By ~ 4

Author(s):

Yuqing Chen ◽

Zongcai Feng ◽

Lei Fu ◽

Abdullah AlTheyab ◽

Shihang Feng ◽

...

Keyword(s):

Phase Inversion ◽

Waveform Inversion ◽

Low Frequency ◽

Velocity Model ◽

Reverse Time ◽

Reverse Time Migration ◽

Reflection Phase ◽

Full Waveform ◽

Time Migration ◽

Recorded Data

Reflection full-waveform inversion (RFWI) can recover the low-wavenumber components of the velocity model along with the reflection wavepaths. However, this requires an expensive least-squares reverse time migration (LSRTM) to construct the perturbation image that can still suffer from cycle-skipping problems. As an inexpensive alternative to LSRTM, we use migration deconvolution (MD) with RFWI. To mitigate cycle-skipping problems, we develop a multiscale reflection phase inversion (MRPI) strategy that boosts the low-frequency data and should only explain the phase information in the recorded data, not its magnitude spectrum. We also use the rolling-offset strategy that gradually extends the offset range of data with an increasing number of iterations. Numerical results indicate that the MRPI + MD method can efficiently recover the low-wavenumber components of the velocity model and is less prone to getting stuck in local minima compared to conventional RFWI.

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Iterative passive-source location estimation and velocity inversion using geometric-mean reverse-time migration and full-waveform inversion

Geophysical Journal International ◽

10.1093/gji/ggaa428 ◽

2020 ◽

Vol 223 (3) ◽

pp. 1935-1947

Author(s):

Bin Lyu ◽

Nori Nakata

Keyword(s):

Geometric Mean ◽

Waveform Inversion ◽

Velocity Model ◽

Source Location ◽

Location Estimation ◽

Reverse Time ◽

Reverse Time Migration ◽

Velocity Inversion ◽

Time Migration ◽

Passive Seismic

SUMMARY Passive-seismic provides useful information for reservoir monitoring and structural imaging; for example, the locations of microseismic events are helpful to understand the extension of the hydraulic fracturing. However, passive-seismic imaging still faces some challenges. First, it is not easy to know where the passive-seismic events happened, which is known as passive-source locating. Additionally, the accuracy of the subsurface velocity model will influence the accuracy of the estimated passive-source locations and the quality of the structural imaging obtained from the passive-seismic data. Therefore the velocity inversion using the passive-seismic data is required to provide the velocity with higher accuracy. Focusing on these challenges, we develop an iterative passive-source location estimation and velocity inversion method using geometric-mean reverse-time migration (GmRTM) and full-waveform inversion (FWI). In each iteration, the source location is estimated using a high-resolution GmRTM method, which provides a better focusing of passive-source imaging compared to conventional wavefield scanning method. The passive-source FWI is then followed to optimize the velocity model using the estimated source location provided by GmRTM. The source location estimation and velocity inversion are implemented sequentially. We evaluate this iterative method using the Marmousi model data set. The experiment result and sensitivity analysis indicate that the proposed method is effective to locate the sources and optimize velocity model in the areas with complicated subsurface structures and noisy recordings.

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Seismic wavefield reconstruction inversion using a plane-wave encoding strategy

Journal of Geophysics and Engineering ◽

10.1093/jge/gxaa062 ◽

2020 ◽

Vol 17 (6) ◽

pp. 1037-1048

Author(s):

Sumin Kim ◽

Wookeen Chung ◽

Young Seo Kim ◽

Changsoo Shin

Keyword(s):

Plane Wave ◽

Initial Velocity ◽

Random Noise ◽

Homogeneous Model ◽

Waveform Inversion ◽

Velocity Model ◽

Reverse Time ◽

Computationally Efficient ◽

Reverse Time Migration ◽

Time Migration

Abstract Wavefield reconstruction inversion (WRI) mitigates cycle skipping by using an inaccurate initial velocity. This attractive technique is usually implemented with shot records. However, if large numbers of shot records are used, WRI can become computationally burdensome due to the many over-determined linear systems that need to be solved. To alleviate this computational issue, we propose an efficient WRI scheme involving plane-wave encoding (WRI-PW) in the frequency domain. Plane-wave encoding can dramatically reduce the number of relevant datasets by transforming shot records into common ray-parameter gathers with time shifting. Therefore, plane-wave encoding is widely used in many aspects of seismic data processing (e.g. waveform inversion, reverse time migration, etc.). Initially, we performed a simple numerical experiment using a velocity model with a box-shaped anomaly. WRI-PW also could generate scattering wavefields in a homogeneous model. Next, computational efficiency was checked with a modified Marmousi-2 model. The results show that the usage of a sufficient plane-wave angle can achieve satisfactory inversion results. It indicates that WRI-PW requires small datasets compared to WRI. Thus, the computational costs for solving the augmented system can be reduced. Further experiments were conducted to evaluate the robustness of WRI-PW to random noise and to compare WRI-PW and conventional full waveform inversion (FWI) with a modified SEG/EAGE salt velocity model. We verify that WRI-PW is more robust to random noise than WRI, it exhibited less dependency on the accuracy of the initial velocity model than conventional FWI and it is computationally efficient.

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Subsurface cavity detection by Improved Reverse Time Migration with Full Waveform Inversion: A Numerical Study

10.1002/essoar.10501271.1 ◽

2019 ◽

Author(s):

Alok Routa ◽

Priya Mohanty ◽

Divakar Vashisth

Keyword(s):

Numerical Study ◽

Waveform Inversion ◽

Full Waveform Inversion ◽

Reverse Time ◽

Reverse Time Migration ◽

Cavity Detection ◽

Full Waveform ◽

Time Migration

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Application of RTM 3D angle gathers to wide-azimuth data subsalt imaging

Geophysics ◽

10.1190/geo2010-0396.1 ◽

2011 ◽

Vol 76 (5) ◽

pp. WB175-WB182 ◽

Cited By ~ 9

Author(s):

Yan Huang ◽

Bing Bai ◽

Haiyong Quan ◽

Tony Huang ◽

Sheng Xu ◽

...

Keyword(s):

Model Updating ◽

Velocity Model ◽

Azimuth Angle ◽

Reverse Time ◽

Reverse Time Migration ◽

Data Set ◽

Additional Information ◽

Time Migration ◽

Reflection Angle ◽

Subsalt Imaging

The availability of wide-azimuth data and the use of reverse time migration (RTM) have dramatically increased the capabilities of imaging complex subsalt geology. With these improvements, the current obstacle for creating accurate subsalt images now lies in the velocity model. One of the challenges is to generate common image gathers that take full advantage of the additional information provided by wide-azimuth data and the additional accuracy provided by RTM for velocity model updating. A solution is to generate 3D angle domain common image gathers from RTM, which are indexed by subsurface reflection angle and subsurface azimuth angle. We apply these 3D angle gathers to subsalt tomography with the result that there were improvements in velocity updating with a wide-azimuth data set in the Gulf of Mexico.

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Use of RTM full 3D subsurface angle gathers for subsalt velocity update and image optimization: Case study at Shenzi field

Geophysics ◽

10.1190/geo2011-0065.1 ◽

2011 ◽

Vol 76 (5) ◽

pp. WB27-WB39 ◽

Cited By ~ 8

Author(s):

Zheng-Zheng Zhou ◽

Michael Howard ◽

Cheryl Mifflin

Keyword(s):

Model Building ◽

Transverse Isotropy ◽

Velocity Model ◽

Reverse Time ◽

Reverse Time Migration ◽

Data Set ◽

Edge Diffraction ◽

Time Migration ◽

Image Optimization ◽

Free Generation

Various reverse time migration (RTM) angle gather generation techniques have been developed to address poor subsalt data quality and multiarrival induced problems in gathers from Kirchhoff migration. But these techniques introduce new problems, such as inaccuracies in 2D subsurface angle gathers and edge diffraction artifacts in 3D subsurface angle gathers. The unique rich-azimuth data set acquired over the Shenzi field in the Gulf of Mexico enabled the generally artifact-free generation of 3D subsurface angle gathers. Using this data set, we carried out suprasalt tomography and salt model building steps and then produced 3D angle gathers to update the subsalt velocity. We used tilted transverse isotropy RTM with extended image condition to generate full 3D subsurface offset domain common image gathers, which were subsequently converted to 3D angle gathers. The angle gathers were substacked along the subsurface azimuth axis into azimuth sectors. Residual moveout analysis was carried out, and ray-based tomography was used to update velocities. The updated velocity model resulted in improved imaging of the subsalt section. We also applied residual moveout and selective stacking to 3D angle gathers from the final migration to produce an optimized stack image.

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