A method for extracting a downgoing wavelet and attenuation parameters from VSP data, comprising: performing upgoing and downgoing P-waves separation processing on VSP data to obtain downgoing P-wave data; performing a FFT on seismic data with a preset time window length starting from the P-wave first arrival time and cut from the downgoing P-wave data to obtain FFT transformed downgoing P-wave data and a multi-trace downgoing P-wave log spectrum; subtracting a downgoing wavelet log spectrum from the multi-trace downgoing P-wave log spectrum to obtain a wavelet-corrected multi-trace downgoing P-wave log spectrum; performing, based on parameters of the wavelet-corrected multi-trace downgoing P-wave log spectrum, a correction and an inverse FFT on the FFT transformed downgoing P-wave data to obtain a downgoing wavelet; and obtaining attenuation parameters based on P-wave first arrival time and the parameters of the wavelet-corrected multi-trace downgoing P-wave log spectrum. The method can extract a downgoing wavelet and attenuation parameters with high accuracy. Also provided are an apparatus for extracting a downgoing wavelet and attenuation parameters from VSP data, a computer device, and a computer-readable storage medium.

Methods and systems for identifying near-surface heterogeneities in a subterranean formation using surface seismic arrays can include: recording raw seismic data using sensors at ground surface; applying a band bass filter to the raw seismic data using a central frequency; picking a phase arrival time for the filtered data; generating an initial starting phase velocity model for tomographic inversion from the raw seismic data; applying tomographic inversion to the filtered data to generate a dispersion map associated at the central frequency; repeating the applying a band bass filter, picking a phase arrival time, generating an initial starting velocity model, and applying tomographic inversion steps for each of a set of central frequencies; and generating a three-dimensional dispersion volume representing near-surface conditions in the subterranean formation by combining the dispersion maps.

Embodiments provide for a method that utilizes the azimuthally spaced receivers of a sonic logging tool. Signals from monopole and dipole sources are reflected from the geologic interfaces and recorded by arrays of receivers of the same tool. For the incident P-waves from the monopole source, phase arrival times for the azimuthal receivers are compensated for stacking using properties of wave propagation in the borehole, and for the incident SH-waves from the dipole source, signs of waveforms for the receivers are changed for specified azimuths.

A method and apparatus of locating subsurface geohazards in a geographical area that includes: receiving a plurality of seismic trace signals in the geographical area based on a shot gather from a seismic shot source; isolating and stacking the plurality of seismic trace signals to generate a windowed trace signal associated with refraction traces from the seismic shot source; transforming the windowed trace signal to a frequency domain; calculating a low frequency to high frequency ratio for the transformed trace signal; outputting the calculated ratio to a two-dimensional array representing the geographical area at a source location and at a mean receiver location; repeating the steps for a plurality of other shot gathers in the geographical area; and multiplying each source location ratio with one or more mean receiver location ratios on the two-dimensional array to generate a final frequency ratio map.

A method of identifying events includes obtaining an acoustic signal from a sensor, determining one or more frequency domain features from the acoustic signal, providing the one or more frequency domain features as inputs to a plurality of event detection models, and determining the presence of one or more events using the plurality of event detection models. The one or more frequency domain features are obtained across a frequency range of the acoustic signal, and at least two of the plurality of event detection models are different.

A sonic tool is activated in a well having multiple casings and annuli surrounding the casing. Detected data is preprocessed using slowness time coherence (STC) processing to obtain STC data. The STC data is provided to a machine learning module which has been trained on labeled STC data. The machine learning module provides an answer product regarding the states of the borehole annuli which may be used to make decision regarding remedial action with respect to the borehole casings. The machine learning module may implement a convolutional neural network (CNN), a support vector machine (SVM), or an auto-encoder.

An apparatus for detecting a location of an optical fiber having an acoustic sensor disposed subsurface to the earth includes an acoustic emitter configured to emit a first signal having a first frequency and a second signal having a second frequency that is higher than the first frequency, the first and second emitted acoustic signals being azimuthally rotated around the borehole and an optical interrogator configured to interrogate the optical fiber to receive an acoustic measurement that provides a corresponding first received signal and a corresponding second received signal. The apparatus also includes a processor configured to (i) frequency-multiply the first received signal to provide a third signal having a third frequency within a selected range of the second frequency, (ii) estimate a phase difference between the second received signal and the third signal, and (iii) correlate the phase difference to the location of the optical fiber.

A method of determining fluid inflow rates within a wellbore comprises determining a plurality of temperature features from a distributed temperature sensing signal originating in a wellbore, determining one or more frequency domain features from an acoustic signal originating the wellbore, and using at least one temperature feature of the plurality of temperature features and at least one frequency domain feature of the one or more frequency domain features to determine a fluid inflow rate at one or more locations along the wellbore.

A method can include receiving seismic survey data of a subsurface environment from a seismic survey that includes a source arrangement of sources that is spatially denser than a receiver arrangement of receivers; processing the seismic survey data using the principle of reciprocity for performing interpolation across the receivers to generate processed seismic survey data; and generating an image of at least a portion of the subsurface environment using the processed seismic survey data.

A method for enhancing properties of geophysical data with deep learning networks. Geophysical data may be acquired by positioning a source of sound waves at a chosen shot location, and measuring back-scattered energy generated by the source using receivers placed at selected locations. For example, seismic data may be collected using towed streamer acquisition in order to derive subsurface properties or to form images of the subsurface. However, towed streamer data may be deficient in one or more properties (e.g., at low frequencies). To compensate for the deficiencies, another survey (such as an Ocean Bottom Nodes (OBN) survey) may be sparsely acquired in order to train a neural network. The trained neural network may then be used to compensate for the towed streamer deficient properties, such as by using the trained neural network to extend the towed streamer data to the low frequencies.