A portion of an anisotropy formation through which a wellbore is formed can be identified. An estimate of an elastic anisotropy parameter for the portion can be adjusted based on a first quality control analysis using the elastic anisotropy parameter for the portion. The first signal representing the elastic anisotropy parameter for the portion. The estimate of the elastic anisotropy parameter for the portion can be adjusted based on a second quality control analysis using estimates for the elastic anisotropy parameters for two or more portions of the anisotropy formation.

A seismic warning system comprises: a plurality of sensors, each sensor sensitive to a physical phenomenon associated with seismic events and operative to output an electronic signal representative of the sensed physical phenomenon; a data acquisition unit communicatively coupled to receive the electronic signal from each of the plurality of sensors, the data acquisition unit comprising a processor configured to estimate characteristics of a seismic event based on the electronic signal associated with a P-wave from each of the plurality of sensors; and a local device communicatively coupled to the data acquisition unit. The plurality of sensors, the data acquisition unit and the local device are local to one another.

Methods, systems, devices, and products for performing well logging in a borehole intersecting an earth formation to obtain and transmit an acoustic reflection image of the formation. Methods include identifying a set of features in the acoustic reflection image substantially fitting a pattern, wherein the set of features corresponds to a portion of at least one reflecting structural interface of the formation; and using a representation of the pattern as the compressed representation of the acoustic reflection image. The features may be amplitude peaks in the acoustic reflection image, and the pattern may be a line segment therein that is obtained from the amplitude peaks. Identifying the set of features may include generating a binary image of the amplitude peaks.

Disclosed is a method for analyzing and predicting a main fracture orientation of a mining face based on microseismic monitoring, including: collecting microseismic data generated by a coal rock burst; carrying out a hierarchical clustering on the microseismic data to obtain target hypocenter groups, of which the target hypocenter groups comprise several types of hypocenters; acquiring focal mechanism solutions of all the target hypocenter groups in the target hypocenter group, and acquiring a hypocenter azimuth and a hypocenter dip based on the focal mechanism solutions; and carrying out the hierarchical clustering on a hypocenter location, the hypocenter azimuth and the hypocenter dip, and predicting the main fracture orientation of the mining face.

A seismic warning system comprises: a plurality of sensors, each sensor sensitive to a physical phenomenon associated with seismic events and operative to output an electronic signal representative of the sensed physical phenomenon; a data acquisition unit communicatively coupled to receive the electronic signal from each of the plurality of sensors, the data acquisition unit comprising a processor configured to estimate characteristics of a seismic event based on the electronic signal associated with a P-wave from each of the plurality of sensors; and a local device communicatively coupled to the data acquisition unit.

A wellbore system includes a logging unit having a retrievable logging cable coupled to a downhole tool within a wellbore and a depth correlation unit in the downhole tool that provides current depth data for the wellbore through the retrievable logging cable for recording of a current depth by the logging unit. The wellbore system also includes a distributed acoustic sensing unit that includes a seismic processing unit and a seismic profiling unit connected to a separate optical cable of the retrievable logging cable having distributed acoustic sensing channels, wherein an assignment of the distributed acoustic sensing channels along the separate optical cable is determined by an offset distance between the current depth of a formation reference region within the wellbore and a previous reference depth of the formation reference region within the wellbore. A distributed acoustic sensing method is also included.

A method may include obtaining well log data regarding a geological region of interest. The well log data may correspond to logging-while-drilling (LWD) measurements or measurement-while-drilling (MWD) measurements acquired from various wellbores. The method may further include generating image data regarding the geological region of interest using the well log data and a recurrent neural network. The method may further include determining a drilling parameter for a wellbore among the wellbores in real-time using the image data. The drilling parameter may be determined while the well log data is being acquired in the wellbore. The method may further include transmitting, based on the drilling parameter, a command to a drilling system coupled to the wellbore.

A system to detect and control noise in seismic surveys is provided. The system receives, responsive to a seismic wave generated by a source, seismic data detected by a sensor component of a seismic data acquisition unit. The system generates, for windows of the seismic data, Hough tensors for seismic data transforms in multiple dimensions. The system detects, based on a comparison of an eigenvector and eigenvalue of a canonical matrix of the Hough tensors with a historical eigenvector and eigenvalue of a historical canonical matrix of historical Hough tensors of historical seismic data, a first presence of noise in the seismic data. The first presence of noise can correspond to a noisy spectra pattern in a seismic data transform of the seismic data. The system provides, responsive to detection of the first presence of noise in the seismic data, a notification to adjust a characteristic of the seismic survey.

Providing real-time prediction and mitigation of seismically-induced effects comprises receiving measured seismic data; pre-processing to transform to a uniform format; inputting the preprocessed data into a predictive model; training the predictive model to learn hidden patterns in recorded seismic data, and extract underlying relations between the received measured seismic data and a predicted response at a location of interest at further time instance, as described by the equation: u.sub.I.sup.pred(t+τ)=model(u.sub.I(t), u.sub.M.sub.1(t), u.sub.M.sub.2(t), . . . , u.sub.M.sub.N (t)), where t is current time instance, τ is lead time, u.sub.M.sub.i(t) represents digital signal recorded by the i.sup.th seismic sensor, and N is overall number of sensors in a sensor array that provided the measured seismic data; receiving new real-time seismic data and pre-processing the received new real-time seismic data into the uniform format; inputting the data into the predictive model; and predicting future response at the location of interest in lead time of τ ahead: u.sub.I.sup.pred(t+τ).

A system for monitoring data quality in a drilling operation includes a controller and a plurality of data sources configured to provide data to the controller. The controller is configured to receive data from a plurality of data sources during a drilling operation; apply data quality rules to the received data; calculate a score for each data source of the plurality of data sources based on adherence of the received data for that data source to the data quality rules; compare the calculated scores for the plurality of data sources to determine which calculated scores meet or exceed a threshold score; receive a selection of one of the plurality of data sources having a calculated score that meets or exceeds the threshold score; and use the data from the selected data source. Methods and non-transitory machine-readable media for monitoring data quality are also provided.