scholarly journals Multiscale reflection phase inversion with migration deconvolution

Geophysics ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. R55-R73 ◽  
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.

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

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.

Near-Borehole Imaging Using Full-Waveform Sonic Data

2021 ◽  
Author(s):  
Hala Alqatari ◽  
Thierry-Laurent Tonellot ◽  
Mohammed Mubarak
Keyword(s):  
Seismic Data ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Full Waveform ◽  
Time Migration ◽  
Imaging Results ◽  
High Resolution Images ◽  
Recorded Data ◽  
The Impact ◽  
Processing Steps

Abstract This work presents a full waveform sonic (FWS) dataset processing to generate high-resolution images of the near-borehole area. The dataset was acquired in a nearly horizontal well over a distance of 5400 feet. Multiple formation boundaries can be identified on the final image and tracked at up to 200 feet deep, along the wellbore's trajectory. We first present a new preprocessing sequence to prepare the sonic data for imaging. This sequence leverages denoising algorithms used in conventional surface seismic data processing to remove unwanted components of the recorded data that could harm the imaging results. We then apply a reverse time migration algorithm to the data at different processing stages to assess the impact of the main processing steps on the final image.

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

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. Q15-Q26 ◽  
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.

From classical reflectivity-to-velocity inversion to full-waveform inversion using phase-modified and deconvolved reverse time migration images

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. S31-S49 ◽  
Author(s):  
Chen Tang ◽  
George A. McMechan
Keyword(s):  
Waveform Inversion ◽  
Time Integration ◽  
Multiscale Approach ◽  
Full Waveform Inversion ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Velocity Inversion ◽  
Full Waveform ◽  
Time Migration ◽  
Gradient Based

To obtain a physical understanding of gradient-based descent methods in full-waveform inversion (FWI), we find a connection between the FWI gradient and the image provided by reverse time migration (RTM). The gradient uses the residual data as a virtual source, and RTM uses the observed data directly as the boundary condition, so the FWI gradient is similar to a time integration of the RTM image using the residual data, which physically converts the phase of the reflectivity to the phase of the velocity. Therefore, gradient-based FWI can be connected to the classical reflectivity-to-velocity/impedance inversion (RVI). We have developed a new FWI scheme that provides a self-contained and physically intuitive derivation, which naturally establishes a connection among the amplitude-preserved RTM, the Zoeppritz equations (amplitude variation with angle inversion), and RVI, and combines them into a single framework to produce a preconditioned inversion formula. In this scheme, the relative velocity update is a phase-modified and deconvolved RTM image obtained with the residual data. Consistent with the deconvolution, the multiscale approach applies a gradually widening low-pass frequency filter to the deconvolved wavelet at early iterations, and then it uses the unfiltered deconvolved wavelet for the final iterations. Our numerical testing determined that the new method makes a significant improvement to the quality of the inversion result.

Efficient snapshot-free reverse time migration and computation of multiparameter gradients in full waveform inversion

Geophysics ◽  
2021 ◽  
pp. 1-79
Author(s):  
Johan O. A. Robertsson ◽  
Fredrik Andersson ◽  
René-Édouard Plessix
Keyword(s):  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Principle Of Superposition ◽  
Model Parameter ◽  
Inversion Model ◽  
Full Waveform ◽  
Time Migration ◽  
Anisotropic Elastic

Computing images in reverse time migration and model parameter gradients from adjoint wavefields in full waveform inversion requires the correlation of a forward propagated wavefield with another reverse propagated wavefield. Although in theory only two wavefield propagations are required, one forward propagation and one reverse propagation, it requires storing the forward propagated wavefield as a function of time to carry out the correlations which is associated with significant I/O cost. Alternatively, three wavefield propagations can be carried out to reverse propagate the forward propagated wavefield in tandem with the reverse propagated wavefield. We show how highly accurate reverse time migrated images and full waveform inversion model parameter gradients for anisotropic elastic full waveform inversion can be efficiently computed without significant disk I/O using two wavefield propagations by means of the principle of superposition.

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