Abstract: Method for estimating porosity and water saturation or other geological parameters of a subsurface region when the lithology of the region is unknown, requiring only geophysical data from remote surveys. The geophysical data are inverted (14-18) treating lithology as a third, and discrete, unknown model parameter (12) to be solved for in the inversion. A technique for solving mixed integer non-linear programs may be used. Suitable rock physics relationships (13) are used to relate the desired geological parameters to the geophysical model parameters required for simulating the geophysical data in the inversion process.

Abstract: Method for estimating geological properties in a subsurface region using multiple types of geophysical data (21). An initial physical properties model 22 is constructed. Some parameters in the model are frozen (23) and optionally portions of the model wave number and spatial domains (24) and the data frequency and data time domains (25), are also frozen. Then, a joint inversion (26) of the multiple data types is performed to calculate an update to the model only for the portions that are not frozen. The converged model (27) for this inversion is used as a new starting model, and the process is repeated (28), possibly several times, unfreezing more parameters and data each time until the desired spatial and parameter resolution (29) has been achieved.

Abstract: Method for adaptive weighting of geophysical data types in iterative joint inversion to speed convergence and aid escape from local minima of the penalty (objective) function. Two or more geophysical data sets (11) representing a region of interest are obtained, and are jointly inverted to infer models of the physical properties that affect the particular types of data used. The misfit for each data type is a weighted tem in the penalty function (13). The invention involves changing the weights (51) as the iteration cycles progress when the iteration convergence criteria are satisfied (15), to see if they remain satisfied (52) with the modified penalty function.

Abstract: Method for joint inversion of geophysical data to obtain 3-D models of geological parameters for subsurface regions of unknown lithology. Two or more data sets of independent geophysical data types are obtained, e.g. seismic and electromagnetic. Then they are jointly inverted, using structural coupling, to infer geophysical parameter volumes, e.g. acoustic velocity and resistivity. Regions of common lithology are next identified based on similar combinations of geophysical parameters. Then a joint inversion of the multiple data types is performed in which rock physics relations vary spatially in accordance with the now-known lithology, and 3-D models of geological properties such as shale content and fracture density are inferred. The computational grid for the last inversion may be defined by the lithology regions, resulting in average geological properties over such regions, which may then be perturbed to determine uncertainty in lithologic boundaries.

Abstract: Method for reducing a 3D joint inversion of at least two different types of geophysical data acquired by 3-D surveys to an equivalent set of 1D inversions. First, a 3D inversion is performed on each data type separately to the yield a 3-D model of a physical property corresponding to the data type. Next, a 1D model of the physical property is extracted at selected (x,y) locations. A 1D simulator and the 1D model of the physical property is then used at each of the selected locations to create a synthetic 1D data set at each location. Finally, the 1D synthetic data sets for each different type of geophysical data are jointly inverted at each of the selected locations, yielding improved values of the physical properties. Because the joint inversion is a 1D inversion, the method is computationally advantageous, while recognizing the impact of 3-D effects.

Abstract: Systems and methods which provide electromagnetic subsurface mapping to derive information with respect to subsurface features whose sizes are near to or below the resolution of electromagnetic data characterizing the subsurface are shown. Embodiments operate to identify a region of interest (203) in a resistivity image generated (202) using electromagnetic data (201). One or more scenarios may be identified for the areas of interest, wherein the various scenarios comprise representations of features whose sizes are near to or below the resolution of the electromagnetic data (204). According to embodiments, the scenarios are evaluated (205), such as using forward or inverse modeling, to determine each scenarios' fit to the available data and further to determine their geologic reasonableness (206). Resulting scenarios may be utilized in a number of ways, such as to be substituted in a resistivity image for a corresponding region of anomalous resistivity for enhancing the resistivity image (207).

Abstract: Method for using seismic data from earthquakes to address the low frequency lacuna problem in traditional hydrocarbon exploration methods. Seismometers with frequency response down to about 1 Hz are placed over a target subsurface region in an array with spacing suitable for hydrocarbon exploration (21). Data are collected over a long (weeks or months) time period (22). Segments of the data (44) are identified with known events from earthquake catalogs (43). Those data segments are analyzed using techniques such as traveltime delay measurements (307) or receiver function calculations (46) and then are combined with one or more other types of geophysical data acquired from the target region, using joint inversion (308-310) in some embodiments of the method, to infer physical features of the subsurface indicative of hydrocarbon potential or lack thereof (26).

Abstract: Method for estimating a model of seismic velocity in a subsurface region from seismic data (31) recorded on 3-component instruments. The method measures the apparent incidence angle (32) of a seismic wave observed at a surface as a function of wave frequency. This apparent angle is converted to an effective velocity as a function of frequency (33), which is then inverted (34) to obtain a subsurface velocity model.

Abstract: Method for joint inversion of geophysical data to obtain 3-D models of geological parameters for subsurface regions of unknown lithology. Two or more data sets of independent geophysical data types are obtained, e.g. seismic and electromagnetic. Then they are jointly inverted, using structural coupling, to infer geophysical parameter volumes, e.g. acoustic velocity and resistivity. Regions of common lithology are next identified based on similar combinations of geophysical parameters. Then a joint inversion of the multiple data types is performed in which rock physics relations vary spatially in accordance with the now-known lithology, and 3-D models of geological properties such as shale content and fracture density are inferred. The computational grid for the last inversion may be defined by the lithology regions, resulting in average geological properties over such regions, which may then be perturbed to determine uncertainty in lithologic boundaries.

Abstract: Method for adaptive weighting of geophysical data types in iterative joint inversion to speed convergence and aid escape from local minima of the penalty (objective) function. Two or more geophysical data sets (11) representing a region of interest are obtained, and are jointly inverted to infer models of the physical properties that affect the particular types of data used. The misfit for each data type is a weighted tem in the penalty function (13). The invention involves changing the weights (51) as the iteration cycles progress when the iteration convergence criteria are satisfied (15), to see if they remain satisfied (52) with the modified penalty function.

Abstract: Method for estimating geological properties in a subsurface region using multiple types of geophysical data (21). An initial physical properties model 22 is constructed. Some parameters in the model are frozen (23) and optionally portions of the model wave number and spatial domains (24) and the data frequency and data time domains (25), are also frozen. Then, a joint inversion (26) of the multiple data types is performed to calculate an update to the model only for the portions that are not frozen. The converged model (27) for this inversion is used as a new starting model, and the process is repeated (28), possibly several times, unfreezing more parameters and data each time until the desired spatial and parameter resolution (29) has been achieved.

Abstract: Method for reducing a 3D joint inversion of at least two different types of geophysical data acquired by 3-D surveys (21) to an equivalent set of ID inversions. First, a 3D inversion is performed on each data type separately to the yield a 3-D model of a physical property corresponding to the data type (22). Next, a ID model of the physical property is extracted at selected (x,y) locations. A ID simulator (23) and the ID model of the physical property is then used at each of the selected locations to create a synthetic ID data set at each location (24). Finally, the ID synthetic data sets for each different type of geophysical data are jointly inverted at each of the selected locations, yielding improved values of the physical properties. Because the joint inversion is a ID inversion, the method is computationally advantageous, while recognizing the impact of 3-D effects.

Abstract: Method for estimating porosity and water saturation or other geological parameters of a subsurface region when the lithology of the region is unknown, requiring only geophysical data from remote surveys. The geophysical data are inverted (14-18) treating lithology as a third, and discrete, unknown model parameter (12) to be solved for in the inversion. A technique for solving mixed integer non-linear programs may be used. Suitable rock physics relationships (13) are used to relate the desired geological parameters to the geophysical model parameters required for simulating the geophysical data in the inversion process.

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 obtaining rock parameters such as porosity and vshale directly from inversion of seismic data corresponding to a single trace location. This method is distinguished from existing methods that obtain elastic properties from inversion of seismic data, then relate the elastic parameters to rock lithology parameters such as porosity or vshale because it is accomplished in one step, can incorporate anisotropy and does not require multiple trace locations for stability. The data are separated into partial stacks, and a wavelet is specified for each stack. A set of linearized equations are constructed relating seismic reflectivity to changes in elastic parameters, and another set of linearized equations is constructed relating the changes in elastic parameters to the lithologic parameters. The linearized reflectivity equations are combined with the linearized rock physics equations, convolved with the specified wavelets, and equated to the seismic data.

Abstract: Method for estimating a model of seismic velocity in a subsurface region from seismic data (31) recorded on 3-component instruments. The method measures the apparent incidence angle (32) of a seismic wave observed at a surface as a function of wave frequency. This apparent angle is converted to an effective velocity as a function of frequency (33), which is then inverted (34) to obtain a subsurface velocity model.

Abstract: Method for using seismic data from earthquakes to address the low frequency lacuna problem in traditional hydrocarbon exploration methods. Seismometers with frequency response Select Receivers of Desired Frequency Ranges and Design Survey Seismometer Configuration down to about 1 Hz are placed over a target subsurface region in an array with spacing suitable for hydrocarbon exploration (21). Data are collected over a long (weeks or months) time period (22). Segments of the data (44) are identified with known events from earthquake catalogs (43). Those data segments are analyzed using techniques such as trayeltime delay measurements (307) or receiver function calculations (46) and then are combined with one or more other types of geophysical data acquired from the target region, using joint inversion (308-310) in some embodiments of the method, to infer physical features of the subsurface indicative of hydrocarbon potential or lack thereof (26).

Abstract: Systems and methods which provide electromagnetic subsurface mapping to derive information with respect to subsurface features whose sizes are near to or below the resolution of electromagnetic data characterizing the subsurface are shown. Embodiments operate to identify a region of interest (203) in a resistivity image generated (202) using electromagnetic data (201). One or more scenarios may be identified for the areas of interest, wherein the various scenarios comprise representations of features whose sizes are near to or below the resolution of the electromagnetic data (204). According to embodiments, the scenarios are evaluated (205), such as using forward or inverse modeling, to determine each scenarios' fit to the available data and further to determine their geologic reasonableness (206). Resulting scenarios may be utilized in a number of ways, such as to be substituted in a resistivity image for a corresponding region of anomalous resistivity for enhancing the resistivity image (207).

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: 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.