A method for separating the unknown contributions of two or more sources from a commonly acquired set of wavefield signals representing a wavefield where the contributions from different sources are both encoded by means of the principles of signal apparition and as well as by means of different source encoding techniques.

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.

A method for processing seismic data includes receiving seismic data comprising seismic traces collected from a land-based or marine seismic array, applying a noise mitigation process to the seismic data to generate a first stack volume, identifying, using a machine-learning algorithm, one or more traces of the seismic traces as having a relatively high residual noise, after applying the noise mitigation process, in comparison to other traces of the seismic traces, mitigating noise in the one or more identified traces, and performing a wavefield reconstruction to generate a second stack volume after mitigating the noise in the one or more traces after mitigating the noise in the one or more identified traces, to interpolate a portion of the wavefield corresponding to where the one or more identified traces were located and mitigated.

The present method predicts and separates dispersive surface waves from seismic data using dispersion estimation and is completely data-driven and computer automated and no human intervention is needed. The method is capable of predicting and suppressing surface waves from recorded seismic data without damaging the reflections. Nonlinear signal comparison (NLSC) is used to obtain a high resolution and accurate dispersion. Based on the dispersion, surface waves are predicted from the field recorded seismic data. The predicted surface waves are then subtracted from the original data.

A method includes receiving, via a processor, input data based upon received seismic data, migrating, via the processor, the input data via a pre-stack depth migration technique to generate migrated input data, encoding, via the processor, the input data via an encoding function as a migration attribute to generate encoded input data having a migration function that is non-monotonic versus an attribute related to the input data, migrating, via the processor, the encoded input data via the pre-stack depth migration technique to generate migrated encoded input data, and generating an estimated common image gather based upon the migrated input data and the migrated encoded input data. The method also includes generating a seismic image utilizing the estimated common image gather, wherein the seismic image represents hydrocarbons in a subsurface region of the Earth or subsurface drilling hazards.

A method and system for locating a reflector in a formation. The method may comprise broadcasting a sonic waveform as a shear formation body wave or a compressional formation body wave into the formation, recording a reflected wave from a reflector with the one or more receivers as dipole data by the dipole receiver and quadrupole data by the quadrupole receiver, and processing the dipole data and the quadrupole data with an information handling system to determine a location of the reflector from the borehole sonic logging tool. The system may comprise a borehole sonic logging tool and an information handling system. The borehole sonic logging tool may comprise one or more transmitters configured to transmit a sonic waveform into a formation and one or more receivers configured to record a reflected wave as a dipole receiver for dipole data and a quadrupole receiver for quadrupole data.

Seismic data processing may include computing the travel time shift between two seismic signals or the depth shift between two seismic images. In Full Waveform Inversion (FWI), the travel time difference between an observed trace and a simulated trace may be computed such that the two traces match after the travel time shift is applied to the observed trace. The travel time shift may be computed based on a constrained optimization that maximizes the windowed cross-correlation between the two seismic traces by constraining the time derivative of the travel time shift to be less than a constant while maximizing the windowed cross-correlation. Further, the travel time shift may be computed during the model line search in FWI by computing a plurality of travel time shifts where a first travel time shift is dependent on the observed trace and a second travel time shift is independent of the observed trace.

Systems and methods include a method for deblending signal and noise data. A shot domain for actual sources, a receiver domain for virtual sources, and a receiver domain for actual sources are generated from blended shot data. A dictionary of signal atoms is generated. Each signal atom includes a small patch of seismic signal data gathered during a small time window using multiple neighboring traces. A dictionary of noise atoms is generated. Each noise atom includes a small patch of seismic noise data gathered during a small time window using multiple neighboring traces. A combined signal-and-noise dictionary is generated that contains the signal atoms and the noise atoms. A sparse reconstruction of receiver domain data is created from the combined signal-and-noise dictionary. The sparse reconstruction is split into deblended data and blending noise data based on atom usage to create deblended shot domain gathers for actual sources.

Methods (700) and devices (600) for seismic data processing estimate (720) signal-to-noise ratios of data in a spatio-temporal block of data, determine (730) data-domain weights associated to the data based on the estimated signal-to-noise ratios, and then generate (740) a model of the signal and/or a model of the noise using the data-domain weights.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a seismic data de-blending model. In one aspect, a method comprises: obtaining a plurality of de-blending training examples, wherein each de-blending training example defines: (i) one or more blended seismic traces, and (ii) for each blended seismic trace, a corresponding plurality of target unblended seismic traces; using the de-blending training examples to train a de-blending model having a plurality of de-blending model parameters, comprising, for each de-blending training example: processing the one or more blended seismic traces of the training example using the de-blending model to generate an output which defines, for each of the one or more blended seismic traces of the training example, a corresponding plurality of estimated unblended seismic traces; and adjusting values of the plurality of de-blending model parameters.