Techniques to match a signature in seismic data with a seismic attribute space. A method includes automatically selecting a first plurality of seismic attributes corresponding to seismic data as first selected seismic attributes, combining the first selected seismic attributes into a first realization of attributes, performing a first cluster analysis on the first realization of attributes to generate a first clustered volume, selecting a region of interest (ROI) in the seismic data, projecting the ROI onto the first clustered volume to generate a first signature, determining a first level of correlation between the ROI and the first signature, and determining whether the first level of correlation between the ROI and the first signature exceeds a predetermined threshold and outputting a first correlation volume corresponding to the first signature when the first level of correlation between the ROI and the first signature exceeds the predetermined threshold.

Systems and methods are provided for a horizon patch extraction process and in particular, to receiving seismic trace data of a plurality of seismic events of a subterranean volume, selecting a first seismic trace based on the seismic trace data of the plurality of seismic events, the first seismic trace including a plurality of seismic onsets, determining a depth, an amplitude, and a first thickness of a first seismic onset of the first seismic trace, determining a second thickness between the first seismic onset and a second seismic onset, determining a third thickness between the first seismic onset and a third seismic onset, and generating a horizon patch based on the depth, the amplitude, and the first thickness of the first seismic onset, the second thickness between the first seismic onset and the second seismic onset, and the third thickness between the first seismic onset and the third seismic onset.

According to one embodiment, a near-field data is used to determine a taper length that can isolate the source signature at the top of near-field data with minimum interaction with the Green's function. In some embodiments, a range of taper lengths is selected and for each length after tapering the near-filed data, converting each filtered near-field data to its minimum-phase equivalents. Summing pairwise cross-correlation of all of the minimum-phase equivalent wavelets at the zero-lag provides an attribute that shows how much the tapered portions of the near-field data look alike. An acceptable taper size will be the one that has the highest summation value. Finally, the average of the minimum-phase equivalents of tapered near-field data with the selected taper size is the estimated source signature.

A seismic time-frequency analysis method based on generalized Chirplet transform with time-synchronized extraction, which has higher level of energy aggregation in the time direction and can better describe and characterize the local characteristics of seismic signals, and is applicable to the time-frequency characteristic representation of both harmonic signals and pulse signals, comprising the steps of processing generalized Chirplet transform with time-synchronized extraction for each seismic signal to obtain a time spectrum by: carrying out generalized Chirplet transform, calculating group delay operator and carrying out time-synchronized extraction on seismic signals, thereby the boundary and heterogeneity structure of the rock slice are more accurately and clearly shown and subsequence seismic analysis and interpretation are facilitated.

A system and a computer-implemented method of evaluating a formation. The system includes a plurality of acoustic transmitters and acoustic receivers and a processor. Acoustic data is obtained from the formation using the plurality of acoustic transmitters and acoustic receivers. The acoustic data is projected into a plurality of image planes and a feature in one of the image planes is selected. The plurality image planes are scrolled through in order to determine the three-dimensional structure of the feature. The formation is drilled based on the three-dimensional structure of the feature.

A method, computing system, and non-transitory computer-readable medium, of which the method includes receiving offset well data collected while drilling one or more offset wells, generating a machine learning model configured to predict drilling risks from drilling measurements or inferences, based on the offset well data, receiving drilling parameters for a new well, determining that the drilling parameters are within an engineering design window, generating a drilling risk profile for the new well using the machine learning model, and adjusting one or more of the drilling parameters for the new well, after determining the drilling parameters are within the engineering design window, and after determining the drilling risk profile, based on the drilling risk profile.

A performance-level seismic motion hazard analysis method includes: (1) extracting seismic motion data and denoising the data; (2) extracting feature parameters from the data, and carrying out initialization; (3) generating a training set, an interval set and a test set; (4) training a multi-layer neural network based on the training set; (5) training output values of the neural network based on the interval set, and calculating a mean and a standard deviation of relative errors of the output values; (6) training the neural network based on the test set to determine output values, and calculating a magnitude interval based on an interval confidence; (7) carrying out probabilistic seismic hazard analysis to determine an annual exceeding probability and a return period of a performance-level seismic motion; and (8) determining a magnitude and an epicentral distance that reach the performance-level seismic motion based on the performance-level seismic motion and consistent probability.

Apparatus (10) and methods for combining time reversal and elastic nonlinearity of formation materials for qualtitatively probing for over-pressured regions down hole in advance of a well drilling bit, to determine the distance to the over-pressured region, and for accurately measuring pore pressure downhole in a formation, are described. Classical and reciprocal time reversal methods may be utilized to achieve these measurements.

A multivariate analysis may be used to correlate seismic attributes for a subterranean formation with petrophysical properties of the subterranean formation and/or microseismic data associated with treating, creating, and/or extending a fracture network of the subterranean formation. For example, a method may involve modeling petrophysical properties of a subterranean formation, microseismic data associated with treating a complex fracture network in the subterranean formation, or a combination thereof with a mathematical model based on measured data, microseismic data, completion and treatment data, or a combination thereof to produce a petrophysical property map, a microseismic data map, or a combination thereof; and correlating a seismic attribute map with the petrophysical property map, the microseismic data map, or the combination thereof using the mathematical model to produce at least one quantified correlation, wherein the seismic attribute map is a seismic attributed modeled for the complex fracture network.

A system for processing DAS VSP surveys is provided. The system includes a DAS data collection system coupled to at least one optical fiber at least partially positioned within a wellbore and configured to either activate or passively listen to a seismic source of energy for one or more times. The system further includes an information processing system connected to the DAS data collection system. A seismic dataset is received from the DAS data collection system recorded in a spatiotemporal domain. The seismic dataset is converted into intercept-time ray-parameter domain dataset. Local apparent slope is determined for each seismic signal in the received seismic dataset. Amplitude correction is performed for the received seismic signals by using the slowness profile and the determined local apparent slope in the intercept-time ray-parameter domain dataset. The corrected intercept-time ray-parameter domain dataset is converted back into the spatiotemporal domain.