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[en] Conventional frequency domain singular value decomposition (SVD) filtering method used in random noise attenuation processing causes bending event damage. To mitigate this problem, we present a mixed Cadzow filtering method based on fractional Fourier transform to suppress random noise in 3D seismic data. First, the seismic data is transformed to the time-frequency plane via the fractional Fourier transform. Second, based on the Eigenimage filtering method and Cadzow filtering method, the mixed high-dimensional Hankel matrix is built; then, SVD is performed. Finally, random noise is eliminated effectively by reducing the rank of the matrix. The theoretical model and real applications of the mixed filtering method in a region of Sichuan show that our method can not only suppress noise effectively but also preserve the frequency and phase of effective signals quite well and significantly improve the signal-to-noise ratio of 3D post-stack seismic data.
[en] In the paper, we propose a surface wave suppression method in time-frequency domain based on the wavelet transform, considering the characteristic difference of polarization attributes, amplitude energy and apparent velocity between the effective signals and strong surface waves. First, we use the proposed method to obtain time–frequency spectra of seismic signals by using the wavelet transform and calculate the instantaneous polarizability at each point based on instantaneous polarization analysis. Then, we separate the surface wave area from the signal area based on the surface-wave apparent velocity and the average energy of the signal. Finally, we combine the polarizability, energy, and frequency characteristic to identify and suppress the signal noise. Model and field data are used to test the proposed filtering method.
[en] Conventional time-space domain and frequency-space domain prediction filtering methods assume that seismic data consists of two parts, signal and random noise. That is, the so-called additive noise model. However, when estimating random noise, it is assumed that random noise can be predicted from the seismic data by convolving with a prediction error filter. That is, the source-noise model. Model inconsistencies, before and after denoising, compromise the noise attenuation and signal-preservation performances of prediction filtering methods. Therefore, this study presents an inversion-based time-space domain random noise attenuation method to overcome the model inconsistencies. In this method, a prediction error filter (PEF), is first estimated from seismic data; the filter characterizes the predictability of the seismic data and adaptively describes the seismic data’s space structure. After calculating PEF, it can be applied as a regularized constraint in the inversion process for seismic signal from noisy data. Unlike conventional random noise attenuation methods, the proposed method solves a seismic data inversion problem using regularization constraint; this overcomes the model inconsistency of the prediction filtering method. The proposed method was tested on both synthetic and real seismic data, and results from the prediction filtering method and the proposed method are compared. The testing demonstrated that the proposed method suppresses noise effectively and provides better signal-preservation performance.
[en] The shales of the Qiongzhusi Formation and Wufeng–Longmaxi Formations at Sichuan Basin and surrounding areas are presently the most important stratigraphic horizons for shale gas exploration and development in China. However, the regional characteristics of the seismic elastic properties need to be better determined. The ultrasonic velocities of shale samples were measured under dry conditions and the relations between elastic properties and petrology were systemically analyzed. The results suggest that 1) the effective porosity is positively correlated with clay content but negatively correlated with brittle minerals, 2) the dry shale matrix consists of clays, quartz, feldspars, and carbonates, and 3) organic matter and pyrite are in the pore spaces, weakly coupled with the shale matrix. Thus, by assuming that all connected pores are only present in the clay minerals and using the Gassmann substitution method to calculate the elastic effect of organic matter and pyrite in the pores, a relatively simple rock-physics model was constructed by combining the self-consistent approximation (SCA), the differential effective medium (DEM), and Gassmann’s equation. In addition, the effective pore aspect ratio was adopted from the sample averages or estimated from the carbonate content. The proposed model was used to predict the P-wave velocities and generally matched the ultrasonic measurements very well.
[en] The elastic moduli of four sandstone samples are measured at seismic (2−2000 Hz) and ultrasonic (1 MHz) frequencies and water- and glycerin-saturated conditions. We observe that the high-permeability samples under partially water-saturated conditions and the low-permeability samples under partially glycerin-saturated conditions show little dispersion at low frequencies (2−2000 Hz). However, the high-permeability samples under partially glycerin-saturated conditions and the low-permeability samples under partially water-saturated conditions produce strong dispersion in the same frequency range (2−2000 Hz). This suggests that fluid mobility largely controls the pore-fluid movement and pore pressure in a porous medium. High fluid mobility facilitates pore-pressure equilibration either between pores or between heterogeneous regions, resulting in a low-frequency domain where the Gassmann equations are valid. In contrast, low fluid mobility produces pressure gradients even at seismic frequencies, and thus dispersion. The latter shows a systematic shift to lower frequencies with decreasing mobility. Sandstone samples showed variations in Vp as a function of fluid saturation. We explore the applicability of the Gassmann model on sandstone rocks. Two theoretical bounds for the P-velocity are known, the Gassmann–Wood and Gassmann–Hill limits. The observations confirm the effect of wave-induced flow on the transition from the Gassmann–Wood to the Gassmann–Hill limit. With decreasing fluid mobility, the P-velocity at 2–2000 Hz moves from the Gassmann–Wood boundary to the Gassmann–Hill boundary. In addition,, we investigate the mechanisms responsible for this transition.
[en] A wideband dipole signal is required for dipole dispersion correction and near-borehole imaging. To obtain the broadband flexural wave dispersion, we use a nonlinear frequency modulation (NLFM) signal and propose a segment linear frequency modulation (SLFM) signal as the dipole excitation signal to compensate for the excitation intensity. The signal-to-noise ratio (SNR) of the signal over the entire frequency band is increased. The finite-difference method is used to simulate the responses from a Ricker wavelet, a linear frequency modulation (LFM) signal, an NLFM signal, and an SLFM signal in two borehole models of a homogeneously hard formation and a radially stratified formation. The dispersion and radial tomography results at low SNR of the sound source signals are compared. Numerical modeling suggests that the energy of the flexural waves excited by the Ricker wavelet source is concentrated near the Airy phase. In this case, the dispersion is incomplete and information regarding the formation near or far from the borehole cannot be obtained. The LFM signal yields dispersion information near the Airy phase and the high-frequency range but not in the low-frequency range. Moreover, the information regarding the formation far from the borehole is not accurate. The NLFM signal extends the frequency range of the flexural waves by compensating for the excitation intensity and yields information regarding the formation information, but it is not easy to obtain. The SLFM signal yields the same results as the NLFM signal and is easier to implement. Consequently, the dipole detection range expands and the S-wave velocity calculation accuracy improves.
[en] Common prestack fracture prediction methods cannot clearly distinguish multiplescale fractures. In this study, we propose a prediction method for macro- and mesoscale fractures based on fracture density distribution in reservoirs. First, we detect the macroscale fractures (larger than 1/4 wavelength) using the multidirectional coherence technique that is based on the curvelet transform and the mesoscale fractures (1/4–1/100 wavelength) using the seismic azimuthal anisotropy technique and prestack attenuation attributes, e.g., frequency attenuation gradient. Then, we combine the obtained fracture density distributions into a map and evaluate the variably scaled fractures. Application of the method to a seismic physical model of a fractured reservoir shows that the method overcomes the problem of discontinuous fracture density distribution generated by the prestack seismic azimuthal anisotropy method, distinguishes the fracture scales, and identifies the fractured zones accurately.
[en] We evaluated 2011–2015 mobile relative gravity data from the Hexi monitoring network that covers the epicenter of the 2016 Menyuan Ms6.4 earthquake, Qinghai Province, China and examined the spatiotemporal characteristics of the gravity field at the focal depth. In addition, we assessed the regional gravity field and its variation the half-year before the earthquake. We use first different interpolation algorithms to build a grid for the gravity data and then introduce potential field interpolation–cutting separation techniques and adaptive noise filtering. The results suggest that the gravity filed at the focal depth of 11.12 km separated from the total gravity field at about–400~150 × 10−8 m/s2 in the second half of 2015, which is larger than that in the same period in 2011 to 2014 (±30 × 10−8 m/s2). Moreover, at the same time, the gravity field changed fast from September 2014 to May 2015 and May 2015 to September 2015, reflecting to some extent material migration deep in the crust before the Menyuan earthquake.
[en] Aliased surface waves are caused by large-space sampling intervals in threedimensional seismic exploration and most current surface-wave suppression methods fail to account for. Thus, we propose a surface-wave suppression method using phase-shift and phase-filtering, named the PSPF method, in which linear phase-shift is performed to solve the coupled problem of surface and reflected waves in the FKXKY domain and then used phase and FKXKY filtering to attenuate the surface-wave energy. Processing of model and field data suggest that the PSPF method can reduce the surface-wave energy while maintaining the low-frequency information of the reflected waves.
[en] The normal moveout correction is important to long-offset observations, especially deep layers. For isotropic media, the conventional two-term approximation of the normal moveout function assumes a small offset-to-depth ratio and thus fails at large offset-to-depth ratios. We approximate the long-offset moveout using the Padé approximation. This method is superior to typical methods and flattens the seismic gathers over a wide range of offsets in multilayered media. For a four-layer model, traditional methods show traveltime errors of about 5 ms for offset-to-depth ratio of 2 and greater than 10 ms for offset-to-depth ratio of 3; in contrast, the maximum traveltime error for the [3, 3]-order Padé approximation is no more than 5 ms at offset-to-depth ratio of 3. For the Cooper Basin model, the maximum offset-to-depth ratio for the [3, 3]-order Padé approximation is typically double of those in typical methods. The [7, 7]-order Padé approximation performs better than the [3, 3]-order Padé approximation.