In wave-equation migration and demigration,the cross-correlation imaging/forwarding step implicitly injects an additional copy of the source wavelet,so that the amplitude spectrum of the wavelet is applied redundantly...In wave-equation migration and demigration,the cross-correlation imaging/forwarding step implicitly injects an additional copy of the source wavelet,so that the amplitude spectrum of the wavelet is applied redundantly(effectively imposing a wavelet-spectrum weighting,often akin to an amplitude-squared bias).This redundancy degrades structural fidelity and amplitude balance yet is frequently overlooked.We(i)formalize the mechanism by which cross-correlation duplicates the source-wavelet amplitude effect in both migration and demigration,and(ii)introduce a source-equalized operator that removes the redundancy by deconvolving(or dividing by)the wavelet amplitude spectrum in the imaging condition and its demigration counterpart,while leaving phase/kinematics intact.Using a band-limited Ricker wavelet on a two-layer model and on Marmousi,we show that,if unmanaged,the redundant wavelet spectrum broadens main lobes,introduces ringing,and suppresses vertical resolution in migrated images,and inflates spectrum mismatches between demigrated and observed data even when peak times agree.With our correction,images recover observed-data-consistent bandwidth and sharpened interfaces,and demigrated data also exhibit improved spectrum conformity and reduced amplitude misfit.The results clarify when source amplitudes matter,why cross-correlation makes them redundantly matter,and how a lightweight spectral correction restores physically meaningful amplitude behavior in wave-equation migration/demigration.展开更多
Full-waveform inversion is a promising tool to produce accurate and high-resolution subsurface models.Conventional full-waveform inversion requires an accu-rate estimation of the source wavelet,and its computational c...Full-waveform inversion is a promising tool to produce accurate and high-resolution subsurface models.Conventional full-waveform inversion requires an accu-rate estimation of the source wavelet,and its computational cost is high.We develop a novel source-independent full-waveform inversion method using a hybrid time-and frequency-domain scheme to avoid the requirement of source wavelet estimation and to reduce the computational cost.We employ an amplitude-semblance objective function to not only effectively remove the source wavelet effect on full-waveform inver-sion,but also to eliminate the impact of the inconsistency of source wavelets among different shot gathers on full-waveform inversion.To reduce the high computational cost of full-waveform inversion in the time domain,we implement our new algorithm using a hybrid time-and frequency-domain approach.The forward and backward wave propagation operations are conducted in the time domain,while the frequency-domain wavefields are obtained during modeling using the discrete-time Fourier trans-form.The inversion process is conducted in the frequency domain for selected frequen-cies.We verify our method using synthetic seismic data for the Marmousi model.The results demonstrate that our novel source-independent full-waveform inversion pro-duces accurate velocity models even if the source signature is incorrect.In addition,our method can significantly reduce the computational time using the hybrid time-and frequency-domain approach compared to the conventional full-waveform inversion in the time domain.展开更多
基金supported by the National Natural Science Foundation of China(42430303)Strategy Priority Research Program(Category B)of the Chinese Academy of Sciences(XDB0710000)+2 种基金National Natural Science Foundation of China(42288201)the National Key R&D Program of China(2023YFF0803203)the IGGCAS start-up funding(Grant No.E251510101).
文摘In wave-equation migration and demigration,the cross-correlation imaging/forwarding step implicitly injects an additional copy of the source wavelet,so that the amplitude spectrum of the wavelet is applied redundantly(effectively imposing a wavelet-spectrum weighting,often akin to an amplitude-squared bias).This redundancy degrades structural fidelity and amplitude balance yet is frequently overlooked.We(i)formalize the mechanism by which cross-correlation duplicates the source-wavelet amplitude effect in both migration and demigration,and(ii)introduce a source-equalized operator that removes the redundancy by deconvolving(or dividing by)the wavelet amplitude spectrum in the imaging condition and its demigration counterpart,while leaving phase/kinematics intact.Using a band-limited Ricker wavelet on a two-layer model and on Marmousi,we show that,if unmanaged,the redundant wavelet spectrum broadens main lobes,introduces ringing,and suppresses vertical resolution in migrated images,and inflates spectrum mismatches between demigrated and observed data even when peak times agree.With our correction,images recover observed-data-consistent bandwidth and sharpened interfaces,and demigrated data also exhibit improved spectrum conformity and reduced amplitude misfit.The results clarify when source amplitudes matter,why cross-correlation makes them redundantly matter,and how a lightweight spectral correction restores physically meaningful amplitude behavior in wave-equation migration/demigration.
基金supported by the U.S.Department of Energy(DOE)through the Los Alamos National Laboratory(LANL),which is operated by Triad National Security,LLC,for the National Nuclear Security Administration(NNSA)of U.S.DOE under Contract No.89233218CNA000001provided by the LANL Institutional Computing Program,which is supported by the U.S.DOE NNSA under Contract No.89233218CNA000001.
文摘Full-waveform inversion is a promising tool to produce accurate and high-resolution subsurface models.Conventional full-waveform inversion requires an accu-rate estimation of the source wavelet,and its computational cost is high.We develop a novel source-independent full-waveform inversion method using a hybrid time-and frequency-domain scheme to avoid the requirement of source wavelet estimation and to reduce the computational cost.We employ an amplitude-semblance objective function to not only effectively remove the source wavelet effect on full-waveform inver-sion,but also to eliminate the impact of the inconsistency of source wavelets among different shot gathers on full-waveform inversion.To reduce the high computational cost of full-waveform inversion in the time domain,we implement our new algorithm using a hybrid time-and frequency-domain approach.The forward and backward wave propagation operations are conducted in the time domain,while the frequency-domain wavefields are obtained during modeling using the discrete-time Fourier trans-form.The inversion process is conducted in the frequency domain for selected frequen-cies.We verify our method using synthetic seismic data for the Marmousi model.The results demonstrate that our novel source-independent full-waveform inversion pro-duces accurate velocity models even if the source signature is incorrect.In addition,our method can significantly reduce the computational time using the hybrid time-and frequency-domain approach compared to the conventional full-waveform inversion in the time domain.
