Abstract: A computer implemented method includes receiving, from a remote system, object data comprising values of a set of adjustable parameters of a respective object representation model for each object of a plurality of objects and compositing data indicating at least a respective trajectory of each of the plurality of objects relative to a reference frame. The method includes processing the object data and the compositing data using the respective object representation models to generate output video data depicting a scene including an animated representation of each object of the plurality of objects following the respective trajectory relative to the reference frame. For each object of the plurality of objects, the respective object representation model comprises a respective neural network and is arranged to generate, using the respective neural network, animated representations of the object in which a geometry the object is controllable by the set of adjustable parameters.

Abstract: A method of the invention prepares a hydrocarbon-bearing formation for stimulation. A bottom hole assembly comprising a plug and a perforation tool connected to a wireline is lowered into a wellbore having a casing. An acidic composition is injected into the wellbore; wherein a spacer separates the acidic composition from said bottom hole assembly, but the acidic composition is in direct contact with both the wireline and casing. The spacer may be existing water in the wellbore or water injected into the wellbore. The plug is positioned downhole beyond a location where a first perforation area is to be made in the casing. The perforation tool is activated creating the first perforation area. The acid then contacts the first perforation area and cementitious debris generated from the casing being perforated. The perforation tool is next moved up-hole to a second location and the casing is again perforated to create a second perforation area.

Abstract: A method of the invention prepares a hydrocarbon-bearing formation for stimulation. A bottom hole assembly comprising a plug and a perforation tool connected to a wireline is lowered into the wellbore. Acid is injected into the wellbore such that the acid is in direct contact with the perforation tool, wireline and casing of the wellbore. The plug is positioned downhole beyond a location where a first perforation area is to be made in the casing. The perforation tool is activated creating the first perforation area. The acid then contacts the first perforation area and cementitious debris generated from the casing being perforated. The perforation tool is next moved up-hole to a second location and the casing is again perforated to create a second perforation area. The acid also contacts the second perforated area and cementitious debris generated from the perforated casing. The perforation tool is lastly removed from the wellbore.

Abstract: A method of the invention prepares a hydrocarbon-bearing formation for stimulation. A bottom hole assembly comprising a plug and a perforation tool connected to a wireline is lowered into the wellbore. Acid is injected into the wellbore such that the acid is in direct contact with the perforation tool, wireline and casing of the wellbore. The plug is positioned downhole beyond a location where a first perforation area is to be made in the casing. The perforation tool is activated creating the first perforation area. The acid then contacts the first perforation area and cementitious debris generated from the casing being perforated. The perforation tool is next moved up-hole to a second location and the casing is again perforated to create a second perforation area. The acid also contacts the second perforated area and cementitious debris generated from the perforated casing. The perforation tool is lastly removed from the wellbore.

Abstract: A method of the invention prepares a hydrocarbon-bearing formation for stimulation. A bottom hole assembly comprising a plug and a perforation tool connected to a wireline is lowered into a wellbore having a casing. An acidic composition is injected into the wellbore; wherein a spacer separates the acidic composition from said bottom hole assembly, but the acidic composition is in direct contact with both the wireline and casing. The spacer may be existing water in the wellbore or water injected into the wellbore. The plug is positioned downhole beyond a location where a first perforation area is to be made in the casing. The perforation tool is activated creating the first perforation area. The acid then contacts the first perforation area and cementitious debris generated from the casing being perforated. The perforation tool is next moved up-hole to a second location and the casing is again perforated to create a second perforation area.

Abstract: Obtaining input video data depicting footage of an object, obtaining current values of a set of adjustable parameters of an object representation model comprising a neural network and arranged to generate animated representations of the object using the neural network in which a geometry of the object is controllable by the set of adjustable parameters. For a plurality of iterations, using the object representation model to generate a video layer comprising an animated representation of the object in which the geometry of the object corresponds to the current values of the set of adjustable parameters, presenting composite video data comprising the video layer overlaid on the object in the input video data, and updating the current values of the set of adjustable parameters in response to user input via the user interface.

Abstract: A method of the invention prepares a hydrocarbon-bearing formation for stimulation. A bottom hole assembly comprising a plug and a perforation tool connected to a wireline is lowered into the wellbore. Acid is injected into the wellbore such that the acid is in direct contact with the perforation tool, wireline and casing of the wellbore. The plug is positioned downhole beyond a location where a first perforation area is to be made in the casing. The perforation tool is activated creating the first perforation area. The acid then contacts the first perforation area and cementitious debris generated from the casing being perforated. The perforation tool is next moved up-hole to a second location and the casing is again perforated to create a second perforation area. The acid also contacts the second perforated area and cementitious debris generated from the perforated casing. The perforation tool is lastly removed from the wellbore.

Abstract: A method of the invention prepares a hydrocarbon-bearing formation for stimulation. A bottom hole assembly comprising a plug and a perforation tool connected to a wireline is lowered into a wellbore having a casing. An acidic composition is injected into the wellbore; wherein a spacer separates the acidic composition from said bottom hole assembly, but the acidic composition is in direct contact with both the wireline and casing. The spacer may be existing water in the wellbore or water injected into the wellbore. The plug is positioned downhole beyond a location where a first perforation area is to be made in the casing. The perforation tool is activated creating the first perforation area. The acid then contacts the first perforation area and cementitious debris generated from the casing being perforated. The perforation tool is next moved up-hole to a second location and the casing is again perforated to create a second perforation area.

Abstract: Obtaining input video data depicting footage of an object, obtaining current values of a set of adjustable parameters of an object representation model comprising a neural network and arranged to generate animated representations of the object using the neural network in which a geometry of the object is controllable by the set of adjustable parameters. For a plurality of iterations, using the object representation model to generate a video layer comprising an animated representation of the object in which the geometry of the object corresponds to the current values of the set of adjustable parameters, presenting composite video data comprising the video layer overlaid on the object in the input video data, and updating the current values of the set of adjustable parameters in response to user input via the user interface.

Abstract: A computer implemented method includes receiving, from a remote system, object data comprising values of a set of adjustable parameters of a respective object representation model for each object of a plurality of objects and compositing data indicating at least a respective trajectory of each of the plurality of objects relative to a reference frame. The method includes processing the object data and the compositing data using the respective object representation models to generate output video data depicting a scene including an animated representation of each object of the plurality of objects following the respective trajectory relative to the reference frame. For each object of the plurality of objects, the respective object representation model comprises a respective neural network and is arranged to generate, using the respective neural network, animated representations of the object in which a geometry the object is controllable by the set of adjustable parameters.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: Obtaining input video data depicting footage of an object, obtaining current values of a set of adjustable parameters of an object representation model comprising a neural network and arranged to generate animated representations of the object using the neural network in which a geometry of the object is controllable by the set of adjustable parameters. For a plurality of iterations, using the object representation model to generate a video layer comprising an animated representation of the object in which the geometry of the object corresponds to the current values of the set of adjustable parameters, presenting composite video data comprising the video layer overlaid on the object in the input video data, and updating the current values of the set of adjustable parameters in response to user input via the user interface.

Abstract: A computer-implemented method of processing video data comprising a sequence of image frames. The method includes isolating an instance of an object within the sequence of image frames, generating a modified instance of the object using a machine learning model, and modifying the video data to smoothly transition between at least part of the isolated instance of the object and a corresponding at least part of the modified instance of the object over a subsequence of the sequence of image frames.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: A computer-implemented method includes obtaining source video data comprising a plurality of image frames, and using a face tracker to detect one or more instances of faces within respective sequences of image frames of the source video data. For a first instance of a given face detected within a first sequence of image frames, the method includes determining a framewise location and size of the first instance of the given face in the first sequence of image frames, using a neural renderer to obtain replacement video data comprising a replacement instance of the given face, and using the determined framewise location and size to replace at least part of the first instance of the given face with at least part of the replacement instance of the given face.

Abstract: A computer-implemented method of processing video data comprising a sequence of image frames. The method includes isolating an instance of an object within the sequence of image frames, generating a modified instance of the object using a machine learning model, and modifying the video data to smoothly transition between at least part of the isolated instance of the object and a corresponding at least part of the modified instance of the object over a subsequence of the sequence of image frames.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.