Abstract: A method of characterizing a subterranean formation using a plurality of seismic acquisitions includes obtaining a first seismic acquisition of the subterranean formation, wherein the first seismic acquisition is a baseline survey. Injecting a gas fluid into the subterranean formation, wherein the gas fluid at least partially fills a portion of a fracture network of the subterranean formation. Obtaining a second seismic acquisition of the subterranean formation. Calculating a time-lapse difference in the plurality of seismic acquisitions.

Abstract: A method for 2D seismic data acquisition includes determining source-point seismic survey positions for a combined deep profile seismic data acquisition with a shallow profile seismic data acquisition wherein the source-point positions are based on non-uniform optimal sampling. A seismic data set is acquired with a first set of air-guns optimized for a deep-data seismic profile and the data set is acquired with a second set of air-guns optimized for a shallow-data seismic profile. The data are de-blended to obtain a deep 2D seismic dataset and a shallow 2D seismic dataset.

Abstract: A method for 2D seismic data acquisition includes determining source-point seismic survey positions for a combined deep profile seismic data acquisition with a shallow profile seismic data acquisition wherein the source-point positions are based on non-uniform optimal sampling. A seismic data set is acquired with a first set of air-guns optimized for a deep-data seismic profile and the data set is acquired with a second set of air-guns optimized for a shallow-data seismic profile. The data are de-blended to obtain a deep 2D seismic dataset and a shallow 2D seismic dataset.

Abstract: A method for 2D seismic data acquisition includes determining source-point seismic survey positions for a combined deep profile seismic data acquisition with a shallow profile seismic data acquisition wherein the source-point positions are based on non-uniform optimal sampling. A seismic data set is acquired with a first set of air-guns optimized for a deep-data seismic profile and the data set is acquired with a second set of air-guns optimized for a shallow-data seismic profile. The data are de-blended to obtain a deep 2D seismic dataset and a shallow 2D seismic dataset.

Abstract: A method for 2D seismic data acquisition includes determining source-point seismic survey positions for a combined deep profile seismic data acquisition with a shallow profile seismic data acquisition wherein the source-point positions are based on non-uniform optimal sampling. A seismic data set is acquired with a first set of air-guns optimized for a deep-data seismic profile and the data set is acquired with a second set of air-guns optimized for a shallow-data seismic profile. The data are de-blended to obtain a deep 2D seismic dataset and a shallow 2D seismic dataset.

Abstract: A method of characterizing a subterranean formation using a plurality of seismic acquisitions includes obtaining a first seismic acquisition of the subterranean formation, wherein the first seismic acquisition is a baseline survey. Injecting a gas fluid into the subterranean formation, wherein the gas fluid at least partially fills a portion of a fracture network of the subterranean formation. Obtaining a second seismic acquisition of the subterranean formation. Calculating a time-lapse difference in the plurality of seismic acquisitions.

Abstract: A method for 2D seismic data acquisition includes determining source-point seismic survey positions for a combined deep profile seismic data acquisition with a shallow profile seismic data acquisition wherein the source-point positions are based on non-uniform optimal sampling. A seismic data set is acquired with a first set of air-guns optimized for a deep-data seismic profile and the data set is acquired with a second set of air-guns optimized for a shallow-data seismic profile. The data are de-blended to obtain a deep 2D seismic dataset and a shallow 2D seismic dataset.

Abstract: Computer-implemented method for determining optimal sampling grid during seismic data reconstruction includes: a) constructing an optimization model, via a computing processor, given by minu?Su?1s.t. ?Ru?b?2?? wherein S is a discrete transform matrix, b is seismic data on an observed grid, u is seismic data on a reconstruction grid, and matrix R is a sampling operator; b) defining mutual coherence as ? ? C S ? m ( log ? ? n ) 6 , wherein C is a constant, S is a cardinality of Su, m is proportional to number of seismic traces on the observed grid, and n is proportional to number of seismic traces on the reconstruction grid; c) deriving a mutual coherence proxy, wherein the mutual coherence proxy is a proxy for mutual coherence when S is over-complete and wherein the mutual coherence proxy is exactly the mutual coherence when S is a Fourier transform; and d) determining a sample grid r*=arg minr ?(r).

Abstract: Computer-implemented method for determining optimal sampling grid during seismic data reconstruction includes: a) constructing an optimization model, via a computing processor, given by minu?Su?1 s.t. ?Ru?b?2?? wherein S is a discrete transform matrix, b is seismic data on an observed grid, u is seismic data on a reconstruction grid, and matrix R is a sampling operator; b) defining mutual coherence as ? ? C S ? m ( log ? ? n ) 6 , wherein C is a constant, S is a cardinality of Su, m is proportional to number of seismic traces on the observed grid, and n is proportional to number of seismic traces on the reconstruction grid; c) deriving a mutual coherence proxy, wherein the mutual coherence proxy is a proxy for mutual coherence when S is over-complete and wherein the mutual coherence proxy is exactly the mutual coherence when S is a Fourier transform; and d) determining a sample grid r*=arg minr ?(r).

Abstract: Methods for fracture characterization of unconventional formations are provided. Synthetic seismic fracture responses can be generated based on the derived fracture parameters. The synthetic seismic fracture responses may then be used to derive optimum seismic data acquisition geometry for fracture characterization. These methods of determining the seismic data acquisition geometry are advantageous over conventional methods in that these methods are more reliable and cheaper than existing empirical methods, particularly as applied to fractured unconventional formations. Moreover, these methods allow fracture parameters to be derived from limited but common well log data. Certain embodiments additionally contemplate determining the presence of gas filled fractures. These characterizations and evaluations of unconventional formations are useful for, among other things, determining optimal producing intervals and optimal drilling locations. These methods can eliminate the use of costly image logs and core data.

Abstract: Methods for fracture characterization of unconventional formations are provided. Synthetic seismic fracture responses can be generated based on the derived fracture parameters. The synthetic seismic fracture responses may then be used to derive optimum seismic data acquisition geometry for fracture characterization. These methods of determining the seismic data acquisition geometry are advantageous over conventional methods in that these methods are more reliable and cheaper than existing empirical methods, particularly as applied to fractured unconventional formations. Moreover, these methods allow fracture parameters to be derived from limited but common well log data. Certain embodiments additionally contemplate determining the presence of gas filled fractures. These characterizations and evaluations of unconventional formations are useful for, among other things, determining optimal producing intervals and optimal drilling locations. These methods can eliminate the use of costly image logs and core data.

Abstract: Method for determining best and worst cases for values of model parameters such as porosity and shale volume fraction generated by non-unique matrix inversion of physical data such as seismic reflection amplitudes. The matrix is diagonalized, and then orthonormal basis vectors associated with insignificant diagonal elements are used to generate upper and lower bounds on the solution. Best and worst case solutions are determined as linear combinations of the null basis vectors, where the expansion coefficients are determined by making a best fit to the upper and lower bounds.

Abstract: Method for constructing an integrated rock physics model that simulates both shale anisotropy and stress-induced anisotropy of clastic rocks. In the model, the total pore volume is divided into three parts according to the estimated shale volume and effective stress: (1) clay-related pores, (2) sand-related pores, and (3) microcracks (mainly in the sand component). The pore space is then partitioned into the clay-related and sand-related pores using a scheme first disclosed by Xu and White in 1995. The model simulates shale anisotropy via the preferred orientation of clay-related pores and stress-induced anisotropy via the preferred orientation of microcracks, which is controlled by the differential stresses. Laboratory measurements or well logs are needed to establish a relationship between crack density and the effective stress.

Abstract: A method for eliminating sinusoidal noise without affecting the response of the formation means that the actual formation responses of the logging tools are recovered, and the logs can be used quantitatively. Removal of sinusoidal noise from a log is accomplished in three steps. First, the log is reduced to a zero-mean, stationary series. Second, the wavenumber of the sinusoidal noise is identified by its peak in the Fourier amplitude spectrum. And third, the noise is removed by applying a zero-phase notch filter. In order to preserve the quantitative data integrity, the low wavenumber trend is kept. Preserving the quantitative data integrity is accomplished by approximating the log with a least-squares cubic spline which retains the overall log character, ignoring the sinusoidal noise. A zero mean stationary series is formed by subtracting the least-squares cubic spline from the data. The remaining steps, Fourier analysis and filtering are performed on the difference series.

Abstract: Recorded seismic traces are gathered into common offset groups. Within each group, the traces are arranged according to shot point number. Mean and standard deviations are determined for each trace. High frequency amplitude variations in the mean and standard deviations caused by variations in source strengths and receiver calibrations are removed to produce traces of low frequency amplitude variations representing subsurface geology or wave propagation effects.