A computer-implemented method includes the following. A frequency sweep using sweep parameters is emitted from a vibratory seismic source into geological layers. The sweep parameters include frequencies and modulation parameters for seismic waves. Signals are received from one or more sensors. The signals include seismic data acquisition information, including values identifying energy reflected back from boundaries where rock properties change. A determination is made regarding which of the reflected seismic waves are attenuated. The determination uses an integral transform and a thresholding algorithm for image segmentation. Optimum sweep parameters are determined based on the reflected seismic values that are attenuated and updated to compensate for local geology effects. The emitting, receiving, determining attenuation, determining optimum parameters, and updating are repeated until the received signals are determined to be satisfactory.

A tool and a method for determining material quality of a hydrocarbon wellbore cross section, having one or more tubular elements having filling materials in between, is described. A tool includes a body and moveable assemblies, having multiple arms configured to be in contact with an inner wall of a downhole tubular element, that that are configured to move between a retracted position where the multiple arms of the moveable assemblies are within a housing located in the body of the tool and an extended position where the multiple arms of the moveable assemblies are protruding from the housing and are in contact with the inner wall of the downhole tubular element. The moveable assemblies comprise both an acoustic broad band source array that operates in the frequency range of 0-100 kHz and an acoustic broad band receiver array having a radially spaced acoustic broad band receiver.

Methods of analyzing and optimizing a seismic survey design are described. Specifically, the sampling quality is analyzed as opposed to the overall quality of the whole survey. This allows for analysis of the impact of the offsets, obstacles, and other aspects of the survey on the sampling quality, which will improve the ability to compress the resulting data and minimize acquisition footprints.

A system and method that can include training a deep neural network using time series data that represents functions of a non-linear Kalman filter that represents a dynamic system of equipment and environment and models a pre-defined operational procedure as a temporal sequence. The system and method can also include receiving operation data from the equipment responsive to operation in the environment and outputting an actual operation as an actual sequence of operational actions by the deep neural network. The system and method can additionally include performing an operation-level comparison to evaluate the temporal sequence against the actual sequence using a distance function in a latent space of the deep neural network and outputting a score function that quantifies the distance function in the latent space. The system and method can further include controlling an electronic component to execute an electronic operation based on the score function.

Various implementations directed to quality control and preconditioning of seismic data are provided. In one implementation, a method may include receiving particle motion data from particle motion sensors disposed on seismic streamers. The method may also include performing quality control (QC) processing on the particle motion data. The method may further include performing preconditioning processing on the QC-processed particle motion data. The method may additionally include attenuating noise in the preconditioning-processed particle motion data.

The present invention relates to an apparatus and method for detecting an earthquake using an accelerometer. More particularly, the present invention relates to an apparatus and method for detecting an earthquake using an accelerometer, the apparatus and method being capable of improving reliability of acceleration data obtained from the accelerometer and reliably determining whether an earthquake has occurred on the basis of a change between current acceleration data and previous acceleration data.

Computing device, computer instructions and method for identifying seismic traces prone to cycle-skipping in a full waveform inversion method. The method includes receiving recorded seismic data recorded with seismic sensors over a subsurface of interest; selecting a model that describes the subsurface; calculating, based on the model and the recorded seismic data, estimated seismic data; and choosing a probabilistic measure that characterizes a relationship between the recorded seismic data and the estimated seismic data. The probabilistic measure includes at least one statistical function.

Methods for machine learning-based differencing for hydrocarbon well logs are disclosed. A computer system generates an input layer of a machine learning module. The input layer includes a graphical representation of datasets obtained from one or more hydrocarbon wells. The computer system generates an encoding layer of the machine learning module from the graphical representation. The encoding layer includes a two-dimensional array based on the multiple datasets and a merged dataset of the one or more hydrocarbon wells. The computer system determines that a difference between a first hydrocarbon well log of the multiple datasets and a second hydrocarbon well log of the merged dataset warrants an action. The determining is performed using a convolutional layer. Responsive to determining that the difference warrants an action, the computer system performs the action on the first hydrocarbon well log and the second hydrocarbon well log to modify the merged dataset.

Various implementations directed to quality control and preconditioning of seismic data are provided. In one implementation, a method may include receiving particle motion data from particle motion sensors disposed on seismic streamers. The method may also include performing quality control (QC) processing on the particle motion data. The method may further include performing preconditioning processing on the QC-processed particle motion data. The method may additionally include attenuating noise in the preconditioning-processed particle motion data.

Systems and methods of placing wells in a hydrocarbon field based on seismic attributes and quality indicators associated with a subterranean formation of the hydrocarbon field can include receiving seismic attributes representing the subterranean formation and seismic data quality indicators. A cutoff is generated for each seismic attribute and seismic data quality indicator. A weight is assigned to each seismic attribute and seismic data quality indicator. The weighted seismic attributes and data quality indicators are aggregated for each location in the hydrocarbon field. A risk ranking is assigned based on the weighted seismic attributes and data quality indicators associated with each location in the hydrocarbon field based on the cutoffs. A map is generated with each location on the surface of the subterranean formation color-coded based on its assigned risk ranking.