A method includes obtaining at least one digital waveform corresponding to acoustic signals collected by a logging tool deployed in a downhole environment. The method also includes performing windowed frequency spectra analysis (WFSA) on the at least one digital waveform to obtain frequency semblance information at different time-slices. The method also includes deriving a slowness log as a function of position using the frequency semblance information.

An exemplary embodiment of the invention relates a method for determining hydraulic permeability of rocks in a subsurface region, the method comprising: in-situ measuring and/or calculating at least one of independent seismic velocities of rocks at different locations in said subsurface region; determining at least one lithological unit in said subsurface region based on the measured seismic velocities; for the at least one lithological unit, acquiring at least one rock sample at an at least one location of said subsurface region; measuring the rock-sample porosity and permeability as functions of stress; measuring and/or calculating of at least one of independent seismic velocities of said at least one rock sample as functions of stress; computing the stiff and compliant porosity of said at least one rock sample; computing numerical coefficients of a given analytical permeability model based on the stiff and compliant porosities; computing coefficients of a given analytical model of an elastic-compliance characteristic of the rock based on the stiff and compliant porosity; computing the stiff and compliant porosity for a plurality of other locations in said subsurface region; and computing the permeability of rocks belonging to said at least one lithological unit, for said at least one location in said subsurface region and for said plurality of other locations in said subsurface region.

The invention discloses an omnidirectional vector seismic data processing method and apparatus, a computer readable storage medium and a device, applied to an omnidirectional vector geophone. Wherein the method comprises: collecting omnidirectional vector seismic data of the omnidirectional vector geophone, and performing a pre-processing operation on the omnidirectional vector seismic data; performing pressure and shear waves separation operation on the omnidirectional vector seismic data after the data is subject to the pre-processing operation, to obtain pressure wave data and shear wave data; sequentially performing space vector calculation, a wave field recovery operation and an imaging operation on the pressure wave data and the shear wave data, and then performing modeling to obtain a pressure wave velocity model and a shear wave velocity model. The invention solves the problem of the existing seismic exploration technology that cannot measure and process divergence data and curl data of seismic wave field, so as to improve construction, lithology, fluid exploration accuracy and reliability and promote seismic exploration to be developed from structural exploration to lithology exploration and fluid exploration.

The present invention relates generally to an apparatus and method for calculating efficient 3-dimensional (3D) traveltime by using coarse-grid mesh for a shallow depth source. More particularly, the present invention relates to an efficient 3D traveltime calculation method for a shallow depth source by combining a suppressed wave equation estimation of traveltime (SWEET) algorithm and an equivalent source distribution (ESD) algorithm, wherein the SWEET algorithm is a traveltime calculation algorithm using an damped wave equation and the ESD algorithm is for equivalently distributed sources; and to an apparatus and method for calculating efficient 3D traveltime by using coarse-grid mesh for a shallow depth source which may need less calculation time compared with that of a conventional SWEET algorithm.

In one or more embodiments, a system comprises a first (target) wellbore disposed in a formation, the first wellbore having a pressure imbalance therein causing an influx of formation fluids, a second (relief) wellbore disposed in the formation, a drill string disposed in the second wellbore, the drill string comprising a drill bit and a logging tool, and a wellbore ranging module comprising a processor and memory, the wellbore ranging module coupled to the drill string. The logging tool is configured to detect acoustic energy originating from the influx in the first wellbore and generate one or more signals associated with the detected acoustic energy. The wellbore ranging module is configured to receive, from the logging tool, the one or more signals associated with the detected acoustic energy and determine, using the received signals, a direction from the drill bit to the influx of the first wellbore.

In acoustic well logging, for each inversion depths of a well at which logging of data occurs, acoustic log signals representative of waveforms received at acoustic receivers are processed in a frequency domain to derive field dispersion curve(s). A neural net is operated to generate formation shear slowness value(s) from the curve(s), and resulting signal(s) indicative of shear slowness values are saved, transmitted, plotted, printed or processed. An apparatus for carrying out the method includes a logging tool having at least one activatable acoustic wave source; spaced and acoustically isolated therefrom in the logging tool an array of acoustic detectors that on the detection of acoustic wave energy generate electrical or electronic log signal(s) characteristic of acoustic energy waves detected by the acoustic detector(s); and at least one processing device associated with or forming part of the logging tool for processing the log signal(s).

Systems and methods for detecting in motion railcar seismic data generated by defective railcar axles of a train traveling on a track. The method uses two or more seismic sensors on the side of the track to capture seismic noise generated by railcar wheels. A wheel that exceeds a preset seismic noise threshold in amplitude, will trigger a wheel tracking algorithm that calculates seismic phase shift data related to the actively tracked wheel noise level, to determine the precise location, in real time, of the faulty wheel carriage while moving. Knowing the precise location of the tracked wheel allows the system to isolate the railcar and capture the railcar and wheel carriage identification information. Subsequently, a railcar log is made on a computer database with the railcar identification information and made available to control centers via ground or satellite links.

A method for characterizing a subsurface fluid reservoir includes inducing a pressure wave in a first well traversing the subsurface reservoir. A pressure wave in at least a second well traversing the subsurface reservoir is detected. The detected pressure wave results from conversion of a tube wave generated by the pressure wave in the first well into guided waves. The pressure wave in the at least a second well is generated by conversion of the guided waves arriving at the at least a second well. A guided (K) wave travel time from the first well to the at least a second well is determined and a physical property of the subsurface fluid reservoir is determined from the K-wave travel time.

A method for locating a microseismic event in a subsurface formation, in some embodiments, comprises: receiving a microseismic signal at a detector; obtaining a velocity model representative of the subsurface formation, the velocity model comprising multiple velocity layers; estimating, for each of the multiple velocity layers in the subsurface formation, a microseismic event location and a microseismic event origin time; and selecting one of the estimated locations and times using a parameter of the microseismic signal received at the detector.

The present invention belongs to the field of deep navigation, and in particular to a high-precision modeling method and system of three-dimensional velocity field for precise navigation of deep oil and gas. The present invention includes: extracting wave impedance characteristics based on standardized well logging data to obtain a wave impedance curve; acquiring a velocity vector of each location at current depth, to obtain a one-dimensional velocity curve; based on the one-dimensional velocity curve, training a velocity value prediction model based on wave impedance at the current depth; performing wave impedance inversion based on the wave impedance curve at the current depth to obtain a wave impedance inversion data volume; and based on the wave impedance inversion data volume, through the velocity value prediction model based on wave impedance at the current depth, acquiring a three-dimensional high-accuracy velocity volume.