Westerngeco L.l.p.

Bmc Helix, Inc.

Michele De Stefano

Marco Bertoli

Claudio Strobbia

Nir Yavin

Daniele Colombo

Yaron Front

Simone Re

Komal Padmawar

Massimo Virgilio

Jeyashree Sivasubramanian

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.

Resource tuning with usage forecasting

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.

Properties link for simultaneous joint inversion

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.

Simultaneous joint inversion of surface wave and refraction data

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. Otherwise, updated seismic, gravity and electromagnetic joint inversion input data are generated, and the process repeats in an iterative fashion until the seismic image residuals meet the predetermined quality objectives.

Methods and apparatus for geophysical exploration via joint inversion

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Soncino, Italy

Michele De Stefano