Abstract: This disclosure provides systems, methods and apparatus, including computer programs encoded on computer storage media, for sidelink assistance for communication between a user equipment (UE) and a network entity. In some aspects, a set of UEs and a network entity may support one or more signaling mechanisms according to which at least one UE is able to assist other UEs in receiving or obtaining information to use for communication with the network entity. For example, a first UE may receive assistance information from a second UE and may use the received assistance information for communication between the first CE and the network entity or may otherwise operate in accordance with the received assistance information. Such assistance information may include an indication of a system information change, a public warning signal (PWS) notification, one or more signal strength measurements, or uplink transmission information.

Abstract: The present invention discloses a right-angle turning method for small-diameter TBM exploration adit excavation and belongs to the field of geological exploration of water conservancy and hydropower projects.

Abstract: A method is described for property estimation including receiving a seismic dataset representative of a subsurface volume of interest and a well log from a well location within the subsurface volume of interest; identifying seismic traces in the seismic dataset that correspond to the well location to obtain a subset of seismic traces; windowing the subset of seismic traces and the well log to generate windowed seismic traces and a windowed well log; multiplying the windowed seismic traces and the windowed well log by a random matrix to generate a plurality of training datasets; and training a neural network using the plurality of training datasets. The method may be executed by a computer system.

Abstract: A method is described for estimating hydrocarbon reservoir attributes including obtaining a geophysical dataset and a geological dataset; obtaining a parameter model, the parameter model having been conditioned by training an initial parameter model using training data, wherein the geological data includes well data and the training data includes the well data; picking a surface in the geophysical dataset; assigning stratigraphic meaning to the at least one surface based on the geological dataset; identifying at least one region of interest on the at least one surface; generating statistical seismic attributes for the at least one region; identifying critical attributes among the statistical seismic attributes by applying the parameter model to generate response variable maps for the at least one region; and generating uncertainty maps for each of the critical attributes and for the response variables. The method may be executed by a computer system.

Abstract: A method is described for estimating hydrocarbon reservoir attributes including obtaining a geophysical dataset and a geological dataset; obtaining a parameter model, the parameter model having been conditioned by training an initial parameter model using training data, wherein the geological data includes well data and the training data includes the well data; picking a surface in the geophysical dataset; assigning stratigraphic meaning to the at least one surface based on the geological dataset; identifying at least one region of interest on the at least one surface; generating statistical seismic attributes for the at least one region; identifying critical attributes among the statistical seismic attributes by applying the parameter model to generate response variable maps for the at least one region; and generating uncertainty maps for each of the critical attributes and for the response variables. The method may be executed by a computer system.

Abstract: A method is described for property estimation including receiving a seismic dataset representative of a subsurface volume of interest and a well log from a well location within the subsurface volume of interest; identifying seismic traces in the seismic dataset that correspond to the well location to obtain a subset of seismic traces; windowing the subset of seismic traces and the well log to generate windowed seismic traces and a windowed well log; multiplying the windowed seismic traces and the windowed well log by a random matrix to generate a plurality of training datasets; and training a neural network using the plurality of training datasets. The method may be executed by a computer system.

Abstract: A system and method to predict rock strength by directly inverting for petrophysical properties. In one embodiment, seismic data is received or obtained from a seismic survey (step 101). The seismic data are then conditioned (step 103) in order to prepare them for an inversion process (step 105). The inversion process has an embedded rock physics model that allows the inversion to be formulated based upon, and thereby outputting or calculating (step 107), petrophysical properties. Rock strength data may then be calculated from the petrophysical properties (step 109).

Abstract: A hydrocarbon exploration method for determining subsurface properties from geophysical survey data. Rock physics trends are identified and for each trend a rock physics model is determined that relates the subsurface property to geophysical properties (103). The uncertainty in the rock physics trends is also estimated (104). A geophysical forward model is selected (105), and its uncertainty is estimated (106). These quantities are used in an optimization process (107) resulting in an estimate of the subsurface property and its uncertainty.

Abstract: A system and method to predict rock strength by directly inverting for petrophysical properties. In one embodiment, seismic data is received or obtained from a seismic survey (step 101). The seismic data are then conditioned (step 103) in order to prepare them for an inversion process (step 105). The inversion process has an embedded rock physics model that allows the inversion to be formulated based upon, and thereby outputting or calculating (step 107), petrophysical properties. Rock strength data may then be calculated from the petrophysical properties (step 109).

Abstract: A hydrocarbon exploration method for determining subsurface properties from geophysical survey data. Rock physics trends are identified and for each trend a rock physics model is determined that relates the subsurface property to geophysical properties (103). The uncertainty in the rock physics trends is also estimated (104). A geophysical forward model is selected (105), and its uncertainty is estimated (106). These quantities are used in an optimization process (107) resulting in an estimate of the subsurface property and its uncertainty.