Abstract: Described techniques determine performance metric values of a performance metric characterizing a performance of a system resource of an information technology (IT) system, and determine driver metric values of a driver metric characterizing an occurrence of an event that is at least partially external to the system resource. A correlation analysis may confirm a potential correlation between the performance metric values and the driver metric values as a correlation. A graph relating the performance metric to the driver metric may be generated. A plurality of extrapolation algorithms may be trained to obtain a plurality of trained extrapolation algorithms using a first subset of data points of the graph, and the plurality of trained extrapolation algorithms may be validated using a second subset of data points of the graph. A driver metric threshold corresponding to the performance metric threshold may be determined using a validated extrapolation algorithm.

Abstract: A method can include receiving data associated with a geologic environment; based on at least a portion of the data, estimating relationships for multiple properties of the geologic environment; and based at least in part on the relationships, performing simultaneous joint inversion for at least one property of the geologic environment.

Abstract: A method can include receiving data associated with a geologic environment; based on at least a portion of the data, estimating relationships for multiple properties of the geologic environment; and based at least in part on the relationships, performing simultaneous joint inversion for at least one property of the geologic environment.

Abstract: A technique includes a method and apparatus for simultaneous joint inversion of surface wave and refraction data to identify near surface geophysical and geological properties.

Abstract: Methods and computing systems for multiple-domain inversion are disclosed to enhance subsurface region evaluation. In one embodiment, three or more datasets corresponding to a subterranean region are received, wherein at least one of the datasets is a magnetic dataset; and the three or more datasets are jointly inverted to generate at least a velocity model that corresponds to at least a first part of the subterranean region, and a susceptibility model that corresponds to at least the first part of the subterranean region, wherein the velocity model and the susceptibility model are correlated.

Abstract: A method for quantitatively evaluating and using multiple geophysical datasets and external constraints for performing velocity model building through simultaneous Joint Inversion and finalized at the improvement of seismic depth images in particularly difficult geology and hydrocarbon high-risk exploration areas is disclosed, which involved the development of techniques: to derive an iterative depth-domain seismic imaging workflow which allows for the simultaneous use of seismic post-migration Common Image Gather residuals together with first arrival (First Break) residuals in conjunction with gravity data and magnetotelluric data; to include in the iterative Joint Inversion workflow the setup of external a-priori constraints as well as of external constraints weighted by probability functions; to include in the iterative Joint Inversion workflow the probabilistic evaluation of the relationships among geophysical parameters that are distinguished into analytical, empirical and structural (i.e.

Abstract: Methods and apparatus are provided for generating velocity models for pre-stack depth migration (“PSDM”). Seismic, gravity and electromagnetic joint inversion input data are generated based on observed seismic, gravity and electromagnetic data (e.g., magnetotelluric and/or controlled source electromagnetic), and velocity, density and resistivity models. A joint inversion is performed to produce a multiparametric model that is a function of velocity, density and resistivity parameter distributions. The separate parameter distributions are extracted from the multiparametric model, and the extracted velocity model is used to perform a PSDM. A migration velocity analysis is performed on PSDM output to generate seismic image residuals. If the seismic image residuals meet predetermined quality objectives, the extracted velocity model is output as the final velocity model for PSDM.

Abstract: A method for quantitatively evaluating and using multiple geophysical datasets and external constraints for performing velocity model building through simultaneous Joint Inversion and finalized at the improvement of seismic depth images in particularly difficult geology and hydrocarbon high-risk exploration areas is disclosed, which involved the development of techniques: to derive an iterative depth-domain seismic imaging workflow which allows for the simultaneous use of seismic post-migration Common Image Gather residuals together with first arrival (First Break) residuals in conjunction with gravity data and magnetotelluric data; to include in the iterative Joint Inversion workflow the setup of external a-priori constraints as well as of external constraints weighted by probability functions; to include in the iterative Joint Inversion workflow the probabilistic evaluation of the relationships among geophysical parameters that are distinguished into analytical, empirical and structural (i.e.

Abstract: Methods and apparatus are provided for generating velocity models for pre-stack depth migration (“PSDM”). Seismic, gravity and electromagnetic joint inversion input data are generated based on observed seismic, gravity and electromagnetic data (e.g., magnetotelluric and/or controlled source electromagnetic), and velocity, density and resistivity models. A joint inversion is performed to produce a multiparametric model that is a function of velocity, density and resistivity parameter distributions. The separate parameter distributions are extracted from the multiparametric model, and the extracted velocity model is used to perform a PSDM. A migration velocity analysis is performed on PSDM output to generate seismic image residuals. If the seismic image residuals meet predetermined quality objectives, the extracted velocity model is output as the final velocity model for PSDM.