Research on multiple elimination methods in inverse data space based on randomized singular value decomposition

Based on surfaced-related multiple elimination （SRME） , this research has derived the methods on multiples elimination in the inverse data space. Inverse data processing means moving seismic data from forward data space （FDS） to inverse data space （ IDS） . The surface-related multiples and primaries can then be sepa-rated in the IDS, since surface-related multiples wi l l form a focus region in the IDS. Muting the multiples ener-gy can achieve the purpose of multiples elimination and avoid the damage to primaries energy during the process of adaptive subtraction. Randomized singular value decomposition （ RSYD） is used to enhance calculation speed and improve the accuracy in the conversion of FDS to IDS. The synthetic shot record of the salt dome model shows that the relationship between primaries and multiples is simple and clear, and RSVD can easily eliminate multiples and save primaries energy. Compared with conventional multiples elimination methods and ordinary methods of multiples elimination in the inverse data space, this technique has an advantage of high cal-culation speed and reliable outcomes.

Interface Controlled Multiple Elimination by Sparsity Inversion

Removing internal multiples remains an important but challenging problem in seismic processing.The generalized Estimation of Primaries by Sparsity Inversion(EPSI)method minimizes data residuals between the calculated and observed wave-form using the sparse constraint of primary impulse responses to predict multiples and remove them directly,instead of using the conventional adaptive subtraction method.Even though the generalized EPSI method provides a good estimate of the primaries and multiples when they overlap,it is limited by intensive computational cost.In this paper,we introduce two strategies to improve computational efficiency.First,the interface-controlled strategy is introduced by only selecting high-amplitude primary responses related to the interfaces with strong impedance contrasts to estimate multiples.The computational time is approximately proportional to the number of involved reflectors and usually,most of the internal multiple energy in the data is only related to a few strong reflectors.Therefore the modified method can remove most of the internal multiples in fewer computations than in the generalized EPSI,which loops through all the interfaces.Next,an approximate formula for estimating primary impulse responses is proposed by neglecting a computationally intensive term which corresponds to the primary responses estimated from internal multiples.According to our analyses and experiments,in most cases,the contribution of this term is negligible because the internal multiples are weak.Therefore,the computational efficiency can be improved without significantly losing quality when estimating most primaries and multiples.In order to demonstrate this,multiple elimination of a two-layered simple data and the Pluto data are implemented.We find that the modified method can yield reliable results that require fewer computations.The improvements of the modified method may encourage the use of the generalized EPSI method in industry.

First-order multiples imaging aided by water bottom

Surface-related multiples frequently propagate into the subsurface and contain abundant information on small reflection angles.Compared with the conventional migration of primaries,migration of multiples offers complementary illumination and a higher vertical resolution.However,crosstalk artifacts caused by unrelated multiples during reverse time migration(RTM)using multiples severely degrade the reliability and interpretation of the final migration images.Therefore,we proposed RTM using first-order receiver-side water-bottom-related multiples for eliminating crosstalk artifacts and enhancing vertical resolution.We first backward propagate the first-order receiver-side water-bottom-related multiples using a water-layer model,followed by saving the upper boundary wavefield.Then we produce the source wavefield using a seismic wavelet and the receiver wavefield by back-extrapolating the saved boundary.Finally,the cross-correlation imaging condition is applied to generate the final image.This method transforms the receiver-side multiples into primaries,followed by the conventional migration processing procedures.Numerical examples using synthetic datasets demonstrate that our method significantly enhances the imaging quality by eliminating crosstalk artifacts and improving the resolution.

Sustained low diffusing capacity in hepatopulmonary syndrome after liver transplantation

AIM： To study the presence of sustained low diffusing capacity （DLco） after liver transplantation （LT） in patients with hepatopulmonary syndrome （HPS）. METHODS： Six patients with mild-to-severe HPS and 24 without HPS who underwent LT were prospectively followed before and after LT at mid-term （median, 15 mo）. HPS patients were also assessed at Iong-tem （median, 86 mo）. RESULTS： Before LT, HPS patients showed lower PaO2 （71 ± 8 mmHg）, higher AaPO2 （43 ± 10 mmHg） and lower DLco （54% ± 9% predicted）, due to a combination of moderate-to-severe ventilation-perfusion （VA/Q） imbalance, mild shunt and diffusion limitation, than non- HPS patients （94 ± 4 mmHg and 19 ± 3 mmHg, and 85% ± 3% predicted, respectively） （P 〈 0.05 each）. Seven non-HPS patients had also reduced DLco （70% ± 4% predicted）. At mid- and long-term after LT, compared to pre- LT, HPS patients normalized PaO2 （91 ± 3 mmHg and 87 ± 5 mmHg）, AaPO2 （14 ± 3 mmHg and 23 ± 5 mmHg） and all VA/Q descriptors （P 〈 0.05 each） without changes in DLco （53% ± 8% and 56% ± 7% predicted, respectively）. Post-LT DLco in non-HPS patients with pre- LT low DLco was unchanged （75% ± 6% predicted）. CONCLUSION： While complete VA/Q resolution in HPS indicates a reversible functional disturbance, sustained low DLco after LT also present in some non-HPS patients, points to persistence of sub-clinical liver-induced pulmonary vascular changes.