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.

The claimed invention relates to means for analysis of a mineral deposit under development using noise logging. The aim of invention consists in increasing accuracy of sound source position determining at surveying in wells with complicated multi-barrier design. The method for locating an acoustic noise source in a well comprises the stages of: computer simulation of acoustic field generated by one or more sources of acoustic signal in the well; simultaneous recording of acoustic signals inside the wellbore using a device for recording acoustic signals comprising at least two acoustic sensors; locating the sought acoustic signal sources in the well by means of co-processing of computer simulation data and data on acoustic signals inside the wellbore recorded using the aforementioned device.

Seismic acquisition having high geophone densities is compressed based on Functional Quantization (FQ) for an infinite dimensional space. Using FQ, the entire sample path of the seismic waveform in a target function space is quantized. An efficient solution for the construction of a functional quantizer is given. It is based on Monte-Carlo simulation to circumvent the limitations of high dimensionality and avoids explicit construction of Voronoi regions to tessellate the function space of interest. The FQ architecture is then augmented with three different Vector Quantization (VQ) techniques which yield hybridized FQ strategies of 1) FQ-Classified VQ, 2) FQ-Residual/Multistage VQ and 3) FQ-Recursive VQ. Joint quantizers are obtained by replacing regular VQ codebooks in these hybrid quantizers by their FQ equivalents. Simulation results show that the FQ combined with any one of the different VQ techniques yields improved rate-distortion compared to either FQ or VQ techniques alone.

Methods are disclosed for monitoring operation integrity during hydrocarbon production or fluid injection operations. According to the methods, received microseismic data is processed to obtain a plurality of data panels corresponding to microseismic data measured over a predetermined time interval. For each data panel, trigger values are calculated for data traces corresponding to sensor receivers of the microseismic monitoring system. At least one data panel is selected as a triggered data panel that satisfies predetermined triggering criteria. A value is calculated for each of at least two event attributes of a plurality of event attributes of the event. An event is classified into at least one event category of a plurality of event categories based on the event score. Related non-transitory computer usable mediums are also disclosed.

A method and system for removing intrinsic transducer noises. The method may comprise disposing a measurement assembly into a wellbore, performing a measurement operation at a depth in the wellbore with the measurement assembly to record two or more raw reflected waveforms, identifying one or more intrinsic transducer noises in the two or more raw reflected waveforms, dividing the two or more raw reflected waveforms into one or more subsections, and identifying one or more incoherent measurements in the one or more subsections. The method may further comprise deriving a noise model for each of the one or more incoherent measurements, performing an inversion for each noise model, and applying an adaptive subtraction to remove the one or more intrinsic transducer noises from the two or more raw reflected waveforms.

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.

Seismic acquisition having high geophone densities is compressed based on Functional Quantization (FQ) for an infinite dimensional space. Using FQ, the entire sample path of the seismic waveform in a target function space is quantized. An efficient solution for the construction of a functional quantizer is given. It is based on Monte-Carlo simulation to circumvent the limitations of high dimensionality and avoids explicit construction of Voronoi regions to tessellate the function space of interest. The FQ architecture is then augmented with three different Vector Quantization (VQ) techniques which yield hybridized FQ strategies of 1) FQ-Classified VQ, 2) FQ-Residual/Multistage VQ and 3) FQ-Recursive VQ. Joint quantizers are obtained by replacing regular VQ codebooks in these hybrid quantizers by their FQ equivalents. Simulation results show that the FQ combined with any one of the different VQ techniques yields improved rate-distortion compared to either FQ or VQ techniques alone.

A method is described for improving distributed acoustic sensing (DAS) seismic data in order to identify seismic events which includes receiving a DAS seismic dataset recorded by a fiber-optic cable in a borehole drilled through a subsurface volume of interest; identifying a portion of the seismic dataset including random noise with no signal to generate a windowed noise dataset; transforming the windowed noise dataset into a noise power spectrum; training a machine-learning algorithm using the noise power spectrum; using the machine-learning algorithm to remove random noise from the DAS seismic dataset to generate a noise-attenuated seismic dataset; and identifying the seismic events in the noise-attenuated seismic dataset. The method may be executed by a computer system.

The claimed invention relates to means for analysis of a mineral deposit under development using noise logging. The aim of invention consists in increasing accuracy of sound source position determining at surveying in wells with complicated multi-barrier design. The method for locating an acoustic noise source in a well comprises the stages of: computer simulation of acoustic field generated by one or more sources of acoustic signal in the well; simultaneous recording of acoustic signals inside the wellbore using a device for recording acoustic signals comprising at least two acoustic sensors; locating the sought acoustic signal sources in the well by means of co-processing of computer simulation data and data on acoustic signals inside the wellbore recorded using the aforementioned device.

Methods and systems for monitoring operation integrity during hydrocarbon production or fluid injection operations by receiving microseismic data; processing the data to obtain data panels corresponding to microseismic data measured over a time interval; determining, with a neural network analysis, whether any of the data panels includes a noise event or a non-noise event; calculating, for each data panel including a non-noise event, trigger values for data traces corresponding to sensor receivers of the microseismic monitoring system; selecting, as a triggered data panel, at least one data panel that satisfies triggering criteria; selecting, as a non-trivial data panel, at least one triggered data panel that satisfies spectral density criteria; calculating a value for each of at least two event attributes of the event; determining an event score based on the event attribute values; and classifying the event into at least one event category based on the event score.