Shoudong Wang

Dealiased Seismic Data Interpolation Using Seislet Transform With Low-Frequency Constraint

Interpolating regularly missing traces in seismic data is thought to be much harder than interpolating irregularly missing seismic traces, because many sparsity-based approaches cannot be used due to the strong aliasing noise in the sparse domain. We propose to use the seislet transform to perform a sparsity-based approach to interpolate highly undersampled seismic data based on the classic projection onto convex sets (POCS) framework. Many numerical tests show that the local slope is the main factor that will affect the sparsity and antialiasing ability of seislet transform. By low-pass filtering the undersampled seismic data with a very low bound frequency, we can get a precise dip estimation, which will make the seislet transform capable for interpolating the aliased seismic data. In order to prepare the optimum local slope during iterations, we update the slope field every several iterations. We also use a percentile thresholding approach to better control the reconstruction performance. Both synthetic and field examples show better performance using the proposed approach than the traditional prediction based and the F-K-based POCS approaches.

Separation of simultaneous sources using a structural-oriented median filter in the flattened dimension

Simultaneous-source shooting can help tremendously shorten the acquisition period and improve the quality of seismic data for better subsalt seismic imaging, but at the expense of introducing strong interference (blending noise) to the acquired seismic data. We propose to use a structural-oriented median filter to attenuate the blending noise along the structural direction of seismic profiles. The principle of the proposed approach is to first flatten the seismic record in local spatial windows and then to apply a traditional median filter (MF) to the third flattened dimension. The key component of the proposed approach is the estimation of the local slope, which can be calculated by first scanning the NMO velocity and then transferring the velocity to the local slope. Both synthetic and field data examples show that the proposed approach can successfully separate the simultaneous-source data into individual sources. We provide an open-source toy example to better demonstratethe proposed methodology. HighlightsWe propose a novel structural-oriented median filter to attenuate the blending noise.We flatten the seismic record in local spatial windows followed by MF in flattened dimension.The local slope can be accurately estimated from velocity-slope transformation.Several simulated synthetic and field data examples show the successful performance.An open-source toy example to better demonstrate the proposed methodology.

Simultaneous-Source Separation Using Iterative Seislet-Frame Thresholding

The distance-separated simultaneous-sourcing (DSSS) technique can make the smallest interference between different sources. In a distance-separated simultaneous-source acquisition with two sources, we propose the use of a novel iterative seislet-frame thresholding approach to separate the blended data. Because the separation is implemented in common shot gathers, there is no need for the random scheduling that is used in conventional simultaneous-source acquisition, where random scheduling is applied to ensure the incoherent property of blending noise in common midpoint, common receiver, or common offset gathers. Thus, DSSS becomes more flexible. The separation is based on the assumption that the local dips of the data from different sources are different. We can use the plane-wave destruction algorithm to simultaneously estimate the conflicting dips and then use seislet frames with two corresponding local dips to sparsify each signal component. Then, the different signal components can be easily separated. Compared with the FK-based approach, the proposed seislet-frame-based approach has the potential to obtain better separated components with less artifacts because the seislet frames are local transforms while the Fourier transform is a global transform. Both simulated synthetic and field data examples show very successful performance of the proposed approach.

Improved random noise attenuation using f-x empirical mode decomposition and local similarity*

Conventional f−x empirical mode decomposition (EMD) is an effective random noise attenuation method for use with seismic profiles mainly containing horizontal events. However, when a seismic event is not horizontal, the use of f−x EMD is harmful to most useful signals. Based on the framework of f−x EMD, this study proposes an improved denoising approach that retrieves lost useful signals by detecting effective signal points in a noise section using local similarity and then designing a weighting operator for retrieving signals. Compared with conventional f−x EMD, f−x predictive filtering, and f−x empirical mode decomposition predictive filtering, the new approach can preserve more useful signals and obtain a relatively cleaner denoised image. Synthetic and field data examples are shown as test performances of the proposed approach, thereby verifying the effectiveness of this method.

Prestack nonstationary deconvolution based on variable-step sampling in the radial trace domain

The conventional nonstationary convolutional model assumes that the seismic signal is recorded at normal incidence. Raw shot gathers are far from this assumption because of the effects of offsets. Because of such problems, we propose a novel prestack nonstationary deconvolution approach. We introduce the radial trace (RT) transform to the nonstationary deconvolution, we estimate the nonstationary deconvolution factor with hyperbolic smoothing based on variable-step sampling (VSS) in the RT domain, and we obtain the high-resolution prestack nonstationary deconvolution data. The RT transform maps the shot record from the offset and traveltime coordinates to those of apparent velocity and traveltime. The ray paths of the traces in the RT better satisfy the assumptions of the convolutional model. The proposed method combines the advantages of stationary deconvolution and inverse Q filtering, without prior information for Q. The nonstationary deconvolution in the RT domain is more suitable than that in the space-time (XT) domain for prestack data because it is the generalized extension of normal incidence. Tests with synthetic and real data demonstrate that the proposed method is more effective in compensating for large-offset and deep data.

Fracture Detection Using 2-D P-wave Seismic Data: A Seismic Physical Modelling Study

We used the seismic physical modelling approach to investigate the effects aligned fractures might have on seismic wave propagation at a larger scale in real Earth imaging. Our primary objective was to examine the effects of aligned fractures on seismic wave amplitude (through the estimation of fracture–induced attenuation) and traveltimes and relating these effects to the fracture orientations. The physical model has two fracture models constructed from a mixture of epoxy resin and silicon rubber and designed to simulate two sets of intersecting fractures. 2-D data were acquired using the pulse-transmission method in three principal directions with the physical model submerged in a water tank. The QVO method, an extension of the classical spectral ratio method for determining attenuation, was used to estimate the quality factor from the pre-processed CMP gathers. The results of our study reveal azimuthal variations in both attenuation expressed through the quality factor Q and the bottom travel-time to the fractured layer. Azimuthal variations in the fractureinduced attenuation and the bottom travel-times were both elliptical to a good approximation, enabling fracture orientations to be obtained quite accurately from the axes of the ellipse. We concluded that attenuation and traveltime anisotropy are potential exploration tools which may be used in fracture detection to complement the use of velocity, amplitude and AVO gradient attributes.

Microencapsulation of sulphur in polyurea

Abstract Polyurea microcapsules containing 33, 50 and 67 wt-% sulphur were prepared by interfacial polymerisation. The characteristics of the fabricated microcapsules were investigated for morphology, thermal property and release property in vulcanising rubber. The morphology showed that microcapsules loading 33 wt-% sulphur were spherical and smooth. The microcapsule sizes decreased going from 33 to 50 to 67 wt-% sulphur. Thermal analysis demonstrated that the microcapsules were thermally stable below 250°C. The process of sulphur released from polyurea microcapsules was put forward in vulcanising nitrile butadiene rubber (NBR) and verified by vulcanising property and tensile strength and elongation of the vulcanised NBR.