We present a new technique for inverting 4D seismic data constrained by dynamics and geology. The inversion is first performed at well positions where all the constraints are set and afterwards extended to the full 3D dataset. The geological and dynamical constraints are set in the model definition i.e. a layered description of the geology (with permeable and non permeable layers) which may be different at each well. This information is then propagated concurrently from each well to the whole dataset. The way the inversion is posed prevents from side lobes effect and enables to discriminate density and velocity effects (P in the case of post-stack data and P&S in the case of prestack). The more reliable information is the P velocity since it affects both reflectivity and travel time.
Seismic image flattening produces subsurface images in which sedimentary layering is horizontal. With flattened images, interpretation of stratigraphic features is straightforward, and horizon picking is trivial. Most flattening methods are limited to vertical shearing and stretching of an image. Because of this limitation, these methods may have difficulty flattening seismic images that contain non-vertical deformations without significantly distorting image features. We propose a new image flattening method that uses a vector shift field, instead of a scalar field of vertical shifts, to represent deformation in an image. The method can flatten by vertically shearing or by rotating portions of an image, or by a combination of vertical shear and rotation. Because it is not limited to vertical shearing, the method can flatten in ways more consistent with geologic deformation.
We propose a new objective function for wave-equation inversion that seeks to minimize the norm of the weighted deconvolution between synthetic and observed data. Compared to more the conventional difference-based objective function which minimizes the norm of the residual between synthetic and observed data, the deconvolution-based objective function is less susceptible to cycle skipping and local minima. Compared to a crosscorrelation-based objective function, the deconvolution-based objective function is less sensitive to a bandlimited or non-impulsive source function, which may result in a nonzero gradient of the objective function even when the constructed velocity model matches the true model.
The analysis of the geothermal structures requires the use of various types of information, such as geologic, geophysical (temperature measurements, time/depth seismic sections, velocity models) and hydro-geological data. Two- and three-dimensional distributions of temperatures and a two-dimensional distribution of geothermal gradient were obtained based on the temperature values recorded in boreholes until the depth of 4000 m. By comparing the geothermal gradient and temperature maps with the geological sections, we notice the presence of near vertical deep faults in the areas characterized by high values of geothermal gradient and temperature; in addition, some of these faults cross intrusive bodies. The paths for the fluid movement are represented by the deep faults.
We present a new 3D gravity-inversion approach that retrieves the geometry of an isolated geologic source with known density contrast and depth of the top. We approximate the source by an interpretation model formed by an ensemble of vertically juxtaposed right prisms whose horizontal cross-sections are described by unknown polygons. The vertices of the polygon of each prism are described by polar coordinates with an unknown origin within the prism. Our method estimates the radii associated with the vertices of each polygon and the horizontal Cartesian coordinates of the unknown origin. The depth of the bottom of the interpretation model is estimated by a new criterion based on the curve of the estimated total-anomalous mass versus the data-misfit measure. Applications to both synthetic and field data sets show that our method obtains stable solutions that recover the geometry of the 3D source and fit the data, even in the case of a complex simulated body with variable dips and strikes. Our method has the advantage of requiring no constraints favoring homogeneity and compactness, which makes it operationally simple.
Understanding fracture compliance is important for characterizing fracture networks and for inferring fluid flow in the subsurface. In an attempt to estimate fracture compliance in the field, we developed a new model to understand tubewave generation at a fracture intersecting a borehole. Solving the dispersion relation in the fracture, amplitude ratios of generated tubewave to incident P-wave were studied over all frequency ranges. Based on the observations from the model, we propose that measuring amplitude ratios near a transition frequency can help constrain fracture compliance and aperture. The transition frequency corresponds to the regime where the viscous skin depth in the fracture is comparable to its aperture. However, measurements in the high frequency limit can place a lower bound on fracture compliance. Comparing the model to a previously published VSP dataset, we argue that compliance values of the order 10
Seismic modeling is an effective method for studying the propagation of seismic waves within complex structures. Based on finite difference method, the arbitrary difference precise integration (ADPI) for seismic forward modeling was developed for 3-D seismic modeling in this paper. When it comes to cases of 3-D modeling, compared with CPU single-core or multi-core processors, graphic processing unit (GPU) parallel calculation shows its outstanding ability of fast calculation to make a seismic forward modeling closer to real seismic records at very low cost of personal computer. Cases study of 3D seismic forward modeling confirm the correction and efficiency about the methodology of ADPI techniques and its GPU algorithms.
This work presents a noise attenuation technique based upon applying a sparsity constraint to a time-frequency transform. It is demonstrated that the solution obtained from applying the sparsity constraint rather than the more common minimum norm constraint produces a superior noise attenuated signal. The sparsity constrained transformation is achieved by finding a sparse representation of the input data in terms of a dictionary of complex Ricker wavelets. The utilization of a complex wavelet dictionary possesses the advantage that signals with arbitrary phase can be represented with enhanced sparsity. Examples with synthetic and real microseismicity data illustrate the capacity of the technique to attenuate ambient noise in microseismic records with low signal-to-noise ratio.
Remote sensing of fractures with elastic waves is important in fields ranging from seismology to non-destructive testing. While previous analytic descriptions of scattering mostly concern very large or very small fractures (compared to the dominant wavelength), we present an analytic solution for the scattering of elastic waves from a fracture of arbitrary size. Based on the linear-slip model for a fracture, we derive the scattered amplitude in the frequency domain under the Born approximation for all combinations of incident and scattered wave modes. Our analytic results match laser-based ultrasonic laboratory measurements of a single fracture in clear plastic, allowing us to quantify the compliance of a fracture.
Joint inversion of PP and PS reflection data has been hindered by the difficult task of registration or correlation of PP and PS events. It can perhaps be achieved by registering the events during inversion but the resulting algorithm is generally computationally intensive. In this paper, we propose a stochastic inversion of PP and PS data which have been registered to the same PP time scale using a new interval velocity analysis technique. The prestack PP and PS wave joint stochastic inversion is achieved by using the PP and PS wave angle gathers using a very fast simulated annealing (VFSA) algorithm. The objective function attempts to match both PP and PS data; the starting models are drawn from fractional Gaussian distribution constructed from interpolated well logs. The proposed method has been applied to synthetic and real data; the inverted results from synthetic data inversion compare very well with model data, and inverted results for real data inversion are consistent with seismic data and log data. These also show that the proposed method has a higher accuracy for estimating rock physics parameters while it circumvents the horizon registration problem in the data interpretation. We also estimate uncertainty in our estimated results from multiple VFSA derived models.