Abstract: A computer implemented method that enables detection and mitigation of drilling hazards is described. The method includes determining time-domain electromagnetic parameters and obtaining data at multiple heights by at least one unmanned aerial vehicle equipped with at least one receiver as a time-domain electromagnetic transmitter emits electromagnetic radiation based on the time-domain electromagnetic parameters. The method also includes fusing the obtained data to generate a subsurface model.

Abstract: A method for determining local position of an optical element associated with an optical path for transporting a laser beam in a working head of a machine for laser processing a material, includes generating a measurement beam of low coherence optical radiation traveling a measurement optical path, leading the measurement beam towards the optical element and the reflected or diffused measurement beam towards an optical interferometric sensor arrangement, generating a reference beam of low coherence optical radiation traveling a reference optical path and leading the reference beam towards the interferometric optical sensor arrangement, superimposing the measurement and reference beams on a common region of incidence, detecting a position of a pattern of interference fringes between the measurement and reference beams, and determining a difference in optical length between the measurement and reference optical paths as a function of the position of the interference pattern along an illumination axis.

Abstract: A method, system, and non-transitory computer readable media for seismic imaging of a subterranean formation. The operations include receiving data representing seismic traces corresponding to seismic waves propagating in the subterranean formation, and determining, from the seismic traces, travel time data and a data covariance matrix. The operations include determining a prior velocity model and a prior model covariance matrix for common midpoint locations and generating an objective function based on the travel time data, the data covariance matrix, the prior velocity model, and the prior model covariance matrix. The operations include determining, by minimizing the objective function, values for one-dimensional velocity models and a set of accuracy values. The operations include generating a pseudo-3D model and a set of accuracy values for the pseudo-3D model.

Abstract: A method for determining local position of an optical element associated with an optical path for transporting a laser beam in a working head of a machine for laser processing a material, includes generating a measurement beam of low coherence optical radiation traveling a measurement optical path, leading the measurement beam towards the optical element and the reflected or diffused measurement beam towards an optical interferometric sensor arrangement, generating a reference beam of low coherence optical radiation traveling a reference optical path and leading the reference beam towards the interferometric optical sensor arrangement, superimposing the measurement and reference beams on a common region of incidence, detecting a position of a pattern of interference fringes between the measurement and reference beams, and determining a difference in optical length between the measurement and reference optical paths as a function of the position of the interference pattern along an illumination axis, or of the

Abstract: A measurement vehicle includes a geophysical sensor. One or more operational sensors are configured to detect operational data related to operation of the measurement vehicle. A driving system is configured to move the measurement vehicle in a travel direction relative to a measurement point. A controller is configured to receive information from the geophysical sensor and the operational sensors, and to control the driving system based on the information.

Abstract: A method for determining a location of a hydrocarbon reservoir. The method may include receiving a cluster number and a parameter vector, wherein the parameter vector represents a spatial distribution of a property over a subsurface. The method may further include receiving observed data and iteratively performing a series of steps until the parameter vector is converged. The steps may include determining a cluster center for each cluster in a plurality of clusters and determining a membership matrix. The steps may further include processing the parameter vector with a forward operator to produce predicted data and determining an update parameter vector guided by a composite objective function composed of a data misfit function and a clustering term. The steps may still further include updating the parameter vector with the update parameter vector. Once converged the parameter vector is used to determine the location of the hydrocarbon reservoir.

Abstract: A method may include obtaining seismic data for a geological region of interest. The method may further include obtaining geophysical data for the geological region of interest. The method may further includes determining various pressure wavefields using a slowness model and a reflectivity model. The method may further include determining various slowness gradients for the slowness model based on the geophysical data, the pressure wavefields, the seismic data, and a geophysical constraint. The geophysical constraint may correspond to an objective function that determines a misfit between the geophysical data and the slowness model. The method may further includes updating the slowness model using the slowness gradients to produce an updated slowness model. The method may further include generating, based on the updated slowness model and the reflectivity model, a subsurface image of the geological region of interest.

Abstract: Methods and systems for training a machine learning model to process microseismic data recorded during fracturing of a subterranean geological formation are configured for selecting a volume in the subterranean geological formation, the volume comprising a set of vertices and a center, the set of vertices defining a first dimension; determining seismogram data for sources at the vertices of the volume and at the center of the volume; generating training data from the seismogram data, the training data relating values of seismogram data to values of moment tensor components; training a machine learning model using the training data; and determining, based on the trained machine learning model, a second dimension defined for the set of vertices, the second dimension being a maximum value enabling an accuracy for outputs of the trained machine learning model that satisfies a threshold.

Abstract: Methods and devices for geophysical exploration include: acquiring seismic data representing a subterranean formation; obtaining a plurality of virtual super gathers (VSGs) comprising the seismic data by sorting the seismic data based on a hypercube with dimensions comprising common midpoint X-Y coordinates, an offset, and an azimuth, wherein one or more seismic attributes are obtained at the dimensions of the hypercube; transforming the seismic data, in the plurality of VSGs from a time-offset domain to a frequency-phase velocity domain; isolating, for VSGs of the plurality, frequencies and phase velocities of the frequency-phase velocity domain based on a windowing operation; and for frequencies isolated by the windowing operation, identifying a maximum magnitude of a phase velocity spectrum from the plurality of VSGs.

Abstract: A method may include obtaining various seismic traces for a geological region of interest. The method may further include determining an offset attribute and an azimuthal attribute. The method may further include determining, using the offset attribute and the azimuthal attribute, a virtual trace bin for the geological region of interest. The method may further include generating a virtual trace using a subset of the seismic traces and corresponding to the virtual trace bin. The method may further include generating a velocity model for the geological region of interest using a virtual shot gather including the virtual trace and various virtual traces. A respective virtual trace among the virtual traces may correspond to a respective virtual trace bin among various virtual trace bins. The method may further include generating a seismic image of the geological region of interest using the velocity model.

Abstract: The present invention relates to a synergistic pharmacological antibiofilm association of colistin and fosfomycin for use in the treatment of a bacterial infection caused by a biofilm-forming pathogen selected from A. baumannii, P. aeruginosa, S. maltophilia and K. pneumoniae strains, preferably in the biofilm phase of growth and, in particular infections associated with a respiratory tract disease, such as a chronic respiratory tract disease comprising CF, NCFB and COPD, especially in hospitalized patients.

Abstract: This specification describes workflows for, but is not limited to, performing full waveform inversion (FWI) to build high resolution velocity models to improve the accuracy of seismic imaging of a subterranean formation. This specification describes processes to automatically edit and enhance S/N quality of seismic data (such as land seismic data) to prepare the datasets for FWI. The methods for automatic corrections and pre-processing include: automatic iterative surface-consistent residual statics calculation, automatic rejection of anomalous traces (such as dead traces), and the automatic correction of surface-consistent amplitude anomalies (such as by scalar or deconvolution approaches). The operations include automatic “muting” of noise before first arrivals.

Abstract: A system and methods are disclosed for determining a model of a subterranean region. The method includes obtaining an observed dataset and a current model for the subterranean region, simulating a dataset from the current model, and determining a data penalty function based on a difference between the observed and simulated datasets. The method further includes training a machine learning (ML) network to predict a model from the observed dataset and determining the predicted model using the trained ML network. The method further includes determining a first model penalty function based on the current model, a second model penalty function based on a difference between the current and the predicted models, and a composite penalty function based on a weighted sum of the data penalty function, the first and the second model penalty functions. Finally, the method includes determining the model based on an extremum of a composite penalty function.

Abstract: A system and methods for determining an updated geophysical model of a subterranean region of interest are disclosed. The method includes obtaining a preprocessed observed geophysical dataset based, at least in part, on an observed geophysical dataset of the subterranean region of interest, and forming a training dataset composed of a plurality of geophysical training models and corresponding simulated geophysical training datasets. The method further includes iteratively determining a simulated geophysical dataset from a current geophysical model, determining a data loss function between the preprocessed observed geophysical dataset and the simulated geophysical dataset, training a machine learning (ML) network, using the training dataset, to predict a predicted geophysical model and determining a model loss function between the current and predicted geophysical models. The method still further includes updating the current geophysical model based on an inversion using the data loss and model loss functions.

Abstract: Systems and methods for removing galvanic distortion caused by near-surface inhomogeneities from surface-to-borehole (STB) measurements are disclosed. Corrected STB measurements may provide for a representation of the resistivity of an oil-bearing reservoir and may be used to determine movement of a waterfront within the reservoir caused by waterflooding of the reservoir.

Abstract: A system and methods for determining a refined seismic model of a subterranean region are disclosed. The method includes obtaining an observed seismic dataset and a current seismic model for the subterranean region and training a machine learning (ML) network using seismic training models and corresponding seismic training datasets and predicting, using the trained ML network, a predicted seismic model from the observed seismic dataset. The method further includes determining a simulated seismic dataset from the current seismic model and a seismic wavelet, a data penalty function based on a difference between the observed and the simulated seismic datasets and a model penalty function from the difference between the current the predicted seismic models. The method still further includes determining the refined seismic model based on an extremum of a composite penalty function based on a weighted sum of the data penalty function and the model penalty function.

Abstract: A method may include obtaining various seismic traces for a geological region of interest. The method may further include determining an offset attribute and an azimuthal attribute. The method may further include determining, using the offset attribute and the azimuthal attribute, a virtual trace bin for the geological region of interest. The method may further include generating a virtual trace using a subset of the seismic traces and corresponding to the virtual trace bin. The method may further include generating a velocity model for the geological region of interest using a virtual shot gather including the virtual trace and various virtual traces. A respective virtual trace among the virtual traces may correspond to a respective virtual trace bin among various virtual trace bins. The method may further include generating a seismic image of the geological region of interest using the velocity model.

Abstract: Disclosed are methods, systems, and computer-readable medium to perform operations including: receiving for a plurality of common midpoint-offset bins each comprising a respective plurality of seismic traces, respective candidate pilot traces representing the plurality of common midpoint-offset bins; generating, based on the respective candidate pilot traces, a respective plurality of corrected seismic traces for each of the plurality of common midpoint-offset bins; grouping the respective pluralities of corrected seismic traces into a plurality of enhanced virtual shot gathers (eVSGs); generating, based on the plurality of common midpoint-offset bins, a common-midpoint (CMP) velocity model; calibrating the CMP velocity model using uphole velocity data to generate a pseudo-3 dimensional (3D) velocity model; performing, based on the plurality of enhanced virtual shot gathers and the pseudo-3D velocity model, a 1.

Abstract: Methods and systems for identifying near-surface heterogeneities in a subterranean formation using surface seismic arrays can include: recording raw seismic data using sensors at ground surface; applying a band bass filter to the raw seismic data using a central frequency; picking a phase arrival time for the filtered data; generating an initial starting phase velocity model for tomographic inversion from the raw seismic data; applying tomographic inversion to the filtered data to generate a dispersion map associated at the central frequency; repeating the applying a band bass filter, picking a phase arrival time, generating an initial starting velocity model, and applying tomographic inversion steps for each of a set of central frequencies; and generating a three-dimensional dispersion volume representing near-surface conditions in the subterranean formation by combining the dispersion maps.

Abstract: A method and a system for determining relative position of an element of an optical system of an assembly for processing or measuring an object along a measurement line, involve generating a measurement beam and a reference beam of low coherence optical radiation. The measurement and reference beams, alternately or in combination, have a main beam and a multiplexed additional beam. The measurement beam, led toward the element of the optical system, and back-reflected, is superimposed on the reference beam in a region of common incidence of an interferometric optical sensor arrangement. Position or frequency of a main interference fringe pattern and an additional interference fringe pattern is detected.