A B S T R A C T P-and S-wave velocity and attenuation coefficients (accurate to ±0.3% and ±0.2 dB/cm, respectively) were measured in synthetic porous rocks with aligned, penny-shaped fractures using the laboratory ultrasonic pulse-echo method. Shearwave splitting was observed by rotating the S-wave transducer and noting the maximum and minimum velocities relative to the fracture direction. A block of synthetic porous rock of fracture density 0.0201 ± 0.0068 and fracture size 3.6 ± 0.38 mm (measured from image analysis of X-ray CT scans) was sub-sampled into three 20-30 mm long, 50 mm diameter core plugs oriented at 0 • , 45 • and 90 • to the fracture normal (transversely isotropic symmetry axis). Full waveform data were collected over the frequency range 500-1000 kHz for both water and glycerin saturated cores to observe the effect of pore fluid viscosity at 1 cP and 100 cP, respectively. The shear-wave splitting observed in the 90 • core was 2.15 ± 0.02% for water saturated and 2.39 ± 0.02% for glycerin saturated, in agreement with the theory that suggests that the percentage splitting should be 100 times the fracture density and independent of the saturating fluid. In the 45 • core, by contrast, splitting was 0.00 ± 0.02% for water saturation and −0.77 ± 0.02% for glycerin saturation. This dependence on fracture orientation and pore fluid viscosity is consistent with the poro-visco-elastic theory for aligned, meso-scale fractures in porous rocks. The results suggest the possible use of shear-or converted-wave data to discriminate between fluids on the basis of viscosity variations.

This is a repository copy of Seismic waveform classification and first-break picking using convolution neural networks.

The inversions of complex geophysical data always solve multi-parameter, nonlinear, and multimodal optimization problems. Searching for the optimal inversion solutions is similar to the social behavior observed in swarms such as birds and ants when searching for food. In this article, first the particle swarm optimization algorithm was described in detail, and ant colony algorithm improved. Then the methods were applied to three different kinds of geophysical inversion problems: (1) a linear problem which is sensitive to noise, (2) a synchronous inversion of linear and nonlinear problems, and (3) a nonlinear problem. The results validate their feasibility and effi ciency. Compared with the conventional genetic algorithm and simulated annealing, they have the advantages of higher convergence speed and accuracy. Compared with the quasi-Newton method and LevenbergMarquardt method, they work better with the ability to overcome the locally optimal solutions.

[1] Differential Acoustic Resonance Spectroscopy (DARS) has been developed to investigate the acoustic properties of samples in the kilohertz frequency range. This new laboratory measurement technique examines the change in resonant frequencies of a cavity perturbed by the introduction of a small test sample. The resonant frequency shift between the empty and sample-loaded cavity is used to estimate the acoustic properties of the loaded sample. This paper presents a DARS perturbation formula that combines a theoretical derivation with numerical simulation and laboratory measurements. Furthermore, a semi-empirical calibration technique is proposed to estimate the acoustic properties of a test sample. This research demonstrates the potential of the DARS measurement technique for estimating the acoustic properties of acoustically small and/or irregularly shaped samples.

Using the forced oscillation method and the ultrasonic transmission method, we measure the elastic moduli of a clay‐bearing Thüringen sandstone under dry and water‐saturated conditions in a broad frequency band at [0.004–10, 106] Hz for different differential pressures up to 30 MPa. Under water‐saturated condition, clear dispersion and attenuation for Young's modulus, Poisson's ratio, and Bulk modulus are observed at seismic frequencies, except for shear modulus. The measured dispersion and attenuation are mainly attributed to the drained/undrained transition, which considers the experimentally undrained boundary condition. Gassmann's predictions are consistent with the measured undrained bulk moduli but not with the shear moduli. Clear shear weakening is observed, and this water‐softening effect is stronger at seismic frequencies than at ultrasonic frequencies where stiffening effect related to squirt flow may mask real shear weakening. The reduction in surface free energy due to chemical interaction between pore fluid and rock frame, which is not taken into account by Gassmann's theory, is the main reason for the departure from Gassmann's predictions, especially for this rock containing a large number of clay minerals.

Full-waveform inversion (FWI) utilizes optimization methods to recover an optimal Earth model to best fit the observed seismic record in a sense of a predefined norm. Since FWI combines mathematic inversion and full-wave equations, it has been recognized as one of the key methods for seismic data imaging and Earth model building in the fields of global/regional and exploration seismology. Unfortunately, conventional FWI fixes background velocity mainly relying on refraction and turning waves that are commonly rich in large offsets. By contrast, reflections in the short offsets mainly contribute to the reconstruction of the high-resolution interfaces. Restricted by acquisition geometries, refractions and turning waves in the record usually have limited penetration depth, which may not reach oil/gas reservoirs. Thus, reflections in the record are the only source that carries the information of these reservoirs. Consequently, it is meaningful to develop reflection-waveform inversion (RWI) that utilizes reflections to recover background velocity including the deep part of the model. This review paper includes: analyzing the weaknesses of FWI when inverting reflections; overviewing the principles of RWI, including separation of the tomography and migration components, the objective functions, constraints; summarizing the current status of the technique of RWI; outlooking the future of RWI.

A B S T R A C TA spectral sparse Bayesian learning reflectivity inversion method, combining spectral reflectivity inversion with sparse Bayesian learning, is presented in this paper. The method retrieves a sparse reflectivity series by sequentially adding, deleting or reestimating hyper-parameters, without pre-setting the number of non-zero reflectivity spikes. The spikes with the largest amplitude are usually the first to be resolved. The method is tested on a series of data sets, including synthetic data, physical modelling data and field data sets. The results show that the method can identify thin beds below tuning thickness and highlight stratigraphic boundaries. Moreover, the reflectivity series, which is inverted trace-by-trace, preserves the lateral continuity of layers.

The impedance inversion technique plays a crucial role in seismic reservoir properties prediction. However, most existing impedance inversion methods often suffer from spatial discontinuities and instability because each vertical profile is processed independently in the inversion. We tested a transform-domain sparsity promotion simultaneous multitrace impedance inversion method to address this issue. The approach was implemented through minimizing a data misfit term and a transform-domain sparsity constraint term that incorporates the (2D or 3D) structural information into the inversion processing. A 2D synthetic data example was applied to mainly explain the roles of the transform-domain sparsity constraint. We determined that the transform-domain sparsity constraint can help in stabilizing the inversion, reducing the influence of high-wavenumber noise on the inverted result, and exploring spatial continuities of structures. Furthermore, a 3D field data example was used to examine the effectiveness of the proposed method for dealing with the real data and to reveal the difference between the results from the 3D simultaneous inversion and the section-by-section inversion. We found that the inverted results roughly matched a lowpass-filtered version of impedance curves derived from well log data. Also, it has been demonstrated that the 3D simultaneous inversion technique provided a better estimation than the section-by-section inversion technique in terms of guaranteeing more spatial continuities of geologic features in the impedance model.