Abstract: Method for estimating the Hessian of the objective function, times a vector, in order to compute an update in an iterative optimization solution to a partial differential equation such as the wave equation, used for example in full wave field inversion of seismic data. The Hessian times vector operation is approximated as one forward wave propagation (24) and one gradient computation (25) in a modified subsurface model (23). The modified subsurface model may be a linear combination of the current subsurface model (20) and the vector (21) to be multiplied by the Hessian matrix. The forward-modeled data from the modified model are treated as a field measurement in the data residual of the objective function for the gradient computation in the modified model. In model parameter estimation by iterative inversion of geophysical data, the vector in the first iteration may be the gradient of the objective function.

Abstract: Method for stabilizing the updated model (13) in iterative seismic data inversion so that the model-simulated data for the next iteration does not “blow up.” A Projection Onto Convex Sets (“POCS”) operator is defined that converts the matrix corresponding to the model to a positive semi-definite matrix. The stability projection operator may be looped with physical constraint projection operators until the model converges (15). The resulting stable and constrained model is then used to simulate seismic data in the next cycle of the outer iteration loop (16).

Abstract: Method for speeding up iterative inversion of seismic data (106) to obtain a subsurface model (102), using local cost function optimization. The frequency spectrum of the updated model at each iteration is controlled to match a known or estimated frequency spectrum for the subsurface region, preferably the average amplitude spectrum of the subsurface P-impedance. The controlling is done either by applying a spectral-shaping filter to the source wavelet (303) and to the data (302) or by applying the filter, which may vary with time, to the gradient of the cost function (403). The source wavelet's amplitude spectrum (before filtering) should satisfy D(f)=fIp(f)W(f), where f is frequency, D(f) is the average amplitude spectrum of the seismic data, and Ip(f) is the average amplitude spectrum for P-impedance in the subsurface region (306,402) or an approximation thereof.

Abstract: An exemplary embodiment of the present invention provides a method for interpolating seismic data. The method includes collecting seismic data of two or more types over a field (401), determining an approximation to one of the types of the seismic data (402), and performing a wave-field transformation on the approximation to form a transformed approximation (405), wherein the transformed approximation corresponds to another of the collected types of seismic data. The method may also include setting the transformed approximation to match the measured seismic data of the corresponding types at matching locations (408), performing a wave-field transformation on the transformed approximation to form an output approximation (412), and using the output approximation to obtain a data representation of a geological layer (416).

Abstract: The invention includes a method for reducing noise in migration of seismic data, particularly advantageous for imaging by simultaneous encoded source reverse-time migration (SS-RTM). One example embodiment includes the steps of obtaining a plurality of initial subsurface images; decomposing each of the initial subsurface images into components; identifying a set of components comprising one of (i) components having at least one substantially similar characteristic across the plurality of initial subsurface images, and (ii) components having substantially dissimilar characteristics across the plurality of initial subsurface images; and generating an enhanced subsurface image using the identified set of components. For SS-RTM, each of the initial subsurface images is generated by migrating several sources simultaneously using a unique random set of encoding functions. Another embodiment of the invention uses SS-RTM for velocity model building.

Abstract: Provided is a method for processing seismic data. One exemplary embodiment includes the steps of obtaining a plurality of initial subsurface images; decomposing each of the initial subsurface images into components; identifying a set of components comprising one of (i) components having at least one substantially similar characteristic across the plurality of initial subsurface images, and (ii) components having substantially dissimilar characteristics across the plurality of initial subsurface images; and generating an enhanced subsurface image using the identified set of components. Each of the initial subsurface images is generated using a unique random set of encoding functions.

Abstract: Method for adapting a template to a target data set. The template may be used to remove noise from, or interpret noise in, the target data set. The target data set is transformed (550) using a selected complex-valued, directional, multi-resolution transform (‘CDMT’) satisfying the Hubert transform property at least approximately. An initial template is selected, and it is transformed (551) using the same CDMT. Then the transformed template is adapted (560) to the transformed target data by adjusting the template's expansion coefficients within allowed ranges of adjustment so as to better match the expansion coefficients of the target data set. Multiple templates may be simultaneously adapted to better fit the noise or other component of the data that it may be desired to represent by template.

Abstract: Method for simultaneous full-wavefield inversion of gathers of source (or receiver) encoded (30) geophysical data (80) to determine a physical properties model (20) for a subsurface region, especially suitable for surveys where fixed-receiver geometry conditions were not satisfied in the data acquisition (40). The inversion involves optimization of a cross-correlation objective function (100).

Abstract: Method for converting seismic data to obtain a subsurface model of, for example, bulk modulus or density. The gradient of an objective function is computed (103) using the seismic data (101) and a background subsurface medium model (102). The source and receiver illuminations are computed in the background model (104). The seismic resolution volume is computed using the velocities of the background model (105). The gradient is converted into the difference subsurface model parameters (106) using the source and receiver illumination, seismic resolution volume, and the background subsurface model. These same factors may be used to compensate seismic data migrated by reverse time migration, which can then be related to a subsurface bulk modulus model. For iterative inversion, the difference subsurface model parameters (106) are used as preconditioned gradients (107).

Abstract: Method for adapting a template to a target data set. The template may be used to remove noise from, or interpret noise in, the target data set. The target data set is transformed (550) using a selected complex-valued, directional, multi-resolution transform (‘CDMT’) satisfying the Hubert transform property at least approximately. An initial template is selected, and it is transformed (551) using the same CDMT. Then the transformed template is adapted (560) to the transformed target data by adjusting the template's expansion coefficients within allowed ranges of adjustment so as to better match the expansion coefficients of the target data set. Multiple templates may be simultaneously adapted to better fit the noise or other component of the data that it may be desired to represent by template.

Abstract: An exemplary embodiment of the present invention provides a method for interpolating seismic data. The method includes collecting seismic data of two or more types over a field (401), determining an approximation to one of the types of the seismic data (402), and performing a wave-field transformation on the approximation to form a transformed approximation (405), wherein the transformed approximation corresponds to another of the collected types of seismic data. The method may also include setting the transformed approximation to match the measured seismic data of the corresponding types at matching locations (408), performing a wave-field transformation on the transformed approximation to form an output approximation (412), and using the output approximation to obtain a data representation of a geological layer (416).

Abstract: Method for interpolating aliased seismic data to generate shot records at regular shot points. The method involves sorting the data into common offsets to obtain the finer sampling in the common-offset domain, then using DMO to transform the data to zero offset to eliminate azimuth and offset variations, from which densely sampled shot records are reconstructed by an efficient Log-Stretch Inverse Shot Record DMO. The method has ready application to techniques that benefit from input data that are regularly and densely sampled, such as 3-D surface related multiple elimination and shot record wave equation migration.