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AuthorAlkhalifah, Tariq Ali (14)Schuster, Gerard T. (6)Zhang, Zhendong (5)Hanafy, Sherif M. (3)Li, Jing (3)View MoreDepartmentPhysical Sciences and Engineering (PSE) Division (23)Earth Science and Engineering Program (22)Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division (1)Energy Resources and Petroleum Engineering (1)Extreme Computing Research Center (1)View MoreJournal

SEG Technical Program Expanded Abstracts 2018 (24)

KAUST Grant NumberOCRF-2014-CRG3-2300 (1)PublisherSociety of Exploration Geophysicists (24)Subjectfull-waveform inversion (9)inversion (8)dispersion (5)velocity analysis (5)2D (3)View MoreType
Conference Paper (24)

Year (Issue Date)2018 (24)Item AvailabilityOpen Access (24)

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Time-lapse parsimonious refraction interferometry: A field experiment

Hanafy, Sherif M.; Li, Jing; Schuster, Gerard T. (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

A time-lapse field experiment is conducted to test the effectiveness of parsimonious refraction interferometry for rapidly producing snapshots of subsurface fluid migration in the subsurface. In the field experiment we recorded 90 sparse data sets over a 4.5-hour period of injecting 12-tons of water into the subsurface. The recorded data are then transformed into 90 dense data sets by parsimonious refraction interferometry (PRI). Refraction traveltimes are picked and inverted to generate 90 snapshots of the subsurface velocity distribution. Results show the percolation of water from the ground surface down to a depth of few meters. Here, the P-velocity varies by up to 8% over a 270-minute interval. These snapshots every 3 minutes of rapid velocity changes can be used to estimate the porosity and permeability distributions in the subsurface.

Subspace methods for time-lapse elastic full-waveform inversion

Zhang, Zhendong; Alkhalifah, Tariq Ali (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

The application of elastic full waveform inversion on time-lapse seismic data is arising from the boom in conventional full waveform inversion. In the past few years, many different inversion strategies are introduced for the time-lapse case, taking advantage of the power of FWI in capturing small changes. However, all methods tend to suffer from the imperfect repeatability of the data acquisition and the weakness in FWI in focussing on the affected areas (i.e. the reservoir). Thus, we modify the subspace method and apply it to time-lapse elastic full waveform inversion. A soft mask calculated using the gradients of the baseline and monitoring data, which acts as a pre-conditioner, is introduced to localize the update area to the affected regions. Specifically, we suppress the similarities of the two gradients and at the same time highlight their differences when calculating the soft mask. The calculated soft mask can reduce the dimensionality of the inverse problem with a delicately selected threshold, which provides a feasible way to calculate the reduced Hessian matrix. Besides, it is a data-driven approach free of human intervention or apriori knowledge. For comparison, we also use a hard mask surrounding the injection area. The numerical example shows that the proposed soft mask performs better than the hard mask.

Adaptive data-selection elastic full-waveform inversion

Zhang, Zhendong; Alkhalifah, Tariq Ali (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

The multiscale inversion strategy is widely used to mitigate the cycle-skipping problem in full waveform inversion. There are many different approaches to implement the multiscale inversion and the widely used low-to-high frequency continuation is not applicable when the observed data lack low frequencies. As an alternative to multiple frequencies, offsets continuation is also able to suppress the cycle-skipping problem when the initial model is not perfect. We improve the multiscale strategy of offset-selection by introducing a local similarity criterion. Thus, we formulate an adaptive data-driven selection process that is better than conventional offset continuation approaches. The global-crosscorrelation objective function used here aims to maximize the similarity of two data sets instead of subtracting one from another and it is more consistent with the selection strategy. Besides, the crosscorrelation-based objective function is more sensitive to the phase information of the data and thus is more applicable to field data. We use a modified elastic Marmousi example to verify the effectiveness of the proposed method.

A misfit function based on entropy regularized optimal transport for full-waveform inversion

chen, fuqiang; Peter, Daniel (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

Given two probability distributions, the classical theorem of optimal transport aims to determine a transport plan which can map one distribution to the other such that the transport cost is minimized. The general functions such as seismic traces do not satisfy all properties of probability distribution. Therefore, we normalize the seismic traces by an exponential function prior to applying the optimal transport to define the distance between seismic traces. In this abstract, we report some results of full waveform inversion from an alternative misfit function based on entropy regularized optimal transport. The regularization gives a smooth approximation to the original optimal transport and the regularized optimum can be found efficiently though. Numerical examples demonstrate the proposed misfit function can invert the data with super lower frequency unavailable from a rough initial model.

Numerical simulation of the magnetic cement induction response in the borehole environment

Eltsov, Timofey; Patzek, Tadeusz (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

We present a technique for the detection of integrity of the magnetic cement behind resistive fiberglass casing. Numerical simulations show that an optimized induction logging tool allows one to detect small changes in the magnetic permeability of cement through a non-conductive casing in a vertical (or horizontal) well. Changes in magnetic permeability influence mostly the real part of the vertical component of magnetic field. The signal attenuation is sensitive to a change of magnetic properties of the cement. Our simulations show that optimum separation between the transmitter and receiver coils ranges from 0.25 to 0.6 meters, and the most suitable magnetic field frequencies vary from 0.1 to 10 kHz. Our goal is to build cheap, long-lasting, low-temperature (<150°C) geothermal wells with water recirculation.

A robust full-waveform inversion based on a shifted correlation of the envelope of wavefields

Wu, Zedong; Alonaizi, Faisal; Alkhalifah, Tariq Ali; Zhang, Zhendong; Almalki, Majed (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

The standard full waveform inversion (FWI) attempts to minimize the difference between the observed and modeled data. When the initial velocity is kinematically accurate, FWI often converges to to the best velocity model, usually of a high-resolution nature. However, when the modeled data using an initial velocity is far from the observed data, conventional local gradient based methods converge to a solution near the initial velocity instead of the global minimum. This is also known as the cycle skipping problem, which results in a zero correlation when observed and modeled data are not correlated. To reduce the cycle-skipping problem, we can compare the envelope of the modeled and observed data instead of the original data. However, when the initial velocity is not good enough, the correlation of the envelope of the modeled and observed data do not contribute accurately to the gradient. To mitigate this issue, we suggest to maximize not only the zero-lag correlation of the envelope but also the non-zero-lag correlation of the envelope. A weighting function, which has its maximum value at zero lag and decays away from zero lag, is proposed to balance the role of the lags. The resulting objective function is less sensitive to the choice of the maximum lag allowed and has a wider radius of convergence compared to standard FWI and envelope inversions. The implementation has the same computational complexity as conventional FWI as the only difference in the calculation is related to the modified adjoint source. We implement this algorithm on the AMD GPU based on OPENCL and obtained about a 14 fold speed up compared to a CPU implementation based on OPENMP. At last, several numerical examples are shown to demonstrate the proper convergence of the proposed method. Application to the Marmousi model shows that this method converges starting with a linearly increasing velocity model, even with data free of frequencies below 3 Hz.

A partial-low-rank method for solving acoustic wave equation

Wu, Zedong; Alkhalifah, Tariq Ali; Zhang, Zhendong (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

Numerical solutions of the acoustic wave equation, especially in anisotropic media, is crucial to seismic modeling, imaging and inversion as it provides efficient, practical, and stable approximate representation of the medium. However, a clean implementation (free of shear wave artifacts and dispersion) of wave propagation, especially in anisotropic media, requires an integral operator, the direct evaluation of which is extremely expensive. Recently, the low-rank method was proposed to provide a good approximation to the integral operator utilizing Fourier transforms. Thus, we propose to split the integral operator into two terms. The first term provides a differential operator that approximates that can be approximated with a standard finite-difference method. We, then, apply the lowrank approximation on the residual term of the finite-difference operator. We implement the two terms in two complementing steps, in which the spectral step corrects for any errors admitted by the finite difference step. Even though we utilize finite-difference approximations, the resulting algorithm admits spectral accuracy. Also, through the finite difference step, the method can deal approximately with the free surface and absorbing boundary conditions in a straight forward manner. Numerical examples show that the method is of high accuracy and efficiency.

Zero-offset sections with a deblurring filter in the time domain

Feng, Shihang; Yilmaz, Oz; Chen, Yuqing; Schuster, Gerard T. (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

We present a workflow for reconstructing a high-quality zero-offset reflection section from prestack data. This workflow constructs a migration image volume by prestack time migration (PSTM) using a series of constant-velocity models. A deblurring filter for each constant-velocity model is applied to each time-migration image to get a deblurred image volume. In order to preserve all events in the image volume, each deblurred image panel is demigrated and then summed over the velocity axis. The resulting demigration section is equivalent to a zero-offset reflection section. Compared with the workflow without a deblurring filter, the composite zero-offset reflection section has higher resolution and a better signal-to-noise ratio. Numerical tests are used to validate the effectiveness of this method with both synthetic and field data.

Image-guided wavefield tomography for VTI media

Li, Vladimir; Guitton, Antoine; Tsvankin, Ilya; Alkhalifah, Tariq Ali (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

Transversely isotropic (TI) models have become essential in generating accurate depth images from seismic data. Here, we develop image-domain tomography (IDT) for building acoustic VTI (TI with a vertical symmetry axis) models from P-wave reflection data. Based on a separable dispersion relation, the modeling operator extrapolates only P-wavefields without the shear-wave artifacts. The inversion algorithm includes least-squares reverse-time migration (LSRTM), which improves the quality of the extended images and accuracy of parameter estimation. Whereas the zero-dip NMO velocity (V) and anellipticity parameter η are updated by focusing energy in space-lag LSRTM gathers, the Thomsen parameter δ is constrained by image-guided interpolation between two or more boreholes. We also apply image-guided smoothing to the IDT gradients of V and η to steer the inversion towards geologically plausible models. To mitigate the trade-off between V and η, we adopt a multistage approach that gradually relaxes the constraints on the spatial η-variation. The robustness of the algorithm is demonstrated on the elastic VTI Marmousi-II model. We also present preliminary inversion results for a line from a 3D data set acquired in the Gulf of Mexico.

Time-lapse waveform inversion regularized by spectral constraints and Sobolev space norm

Kazei, Vladimir; Alkhalifah, Tariq Ali (SEG Technical Program Expanded Abstracts 2018, Society of Exploration Geophysicists, 2018-08-27) [Conference Paper]

Imperfect illumination from surface seismic data due to lack of aperture and frequency content leads to ambiguity and resolution loss in seismic images and in full-waveform inversion (FWI) results. The resolution of time-lapse velocity updates can, however, be improved enforcing the sparsity of the parameter changes. Edge-preserving regularizations and constraints are typically used to promote sparsity. However, different choice of regularization parameters leads to different inversion results and optimal parameters are hard to identify, especially for real data. In particular it is not straightforward to balance the inversion between sparsity constraint and data fit. Fortunately, it is possible to estimate local spatial wavenumbers in a velocity model that are best illuminated by the data. We propose to constrain part of the model difference spectrum that is well illuminated by the data and optimize the rest of the spectrum to enhance sparsity. We approximate correctly retrieved model wavenumbers by simply picking large enough values in the inverted spectrum and constrain that part of model spectrum. Then we adjust the rest of the wavenumbers to reduce the value of a Sobolev space norm (SSN). SSN reduction promotes sparsity of time-lapse updates, while spectral constraints ensure that the part of the modeled spectrum retrieved from the data is completely retained. Application to synthetic noisy data for a perturbation of the Marmousi II model shows that the model resolution can be improved by using our method to extrapolate the model spectrum.

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