A soil probing device includes a probing rod with a measuring probe, a driving for penetrating the probing rod into the ground, generators for generating acoustic compression and shear waves into the ground, detectors for detecting the generated acoustic compression and shear waves. The detectors are built into the measuring probe. Also the generators are built into the measuring probe at positions that are interspaced at fixed distances in a z-direction from the detectors in the measuring probe. A processing unit CPU is provided for calculating velocities of the generated acoustic compression and shear waves that get to travel from the generators towards the detectors through local ground layers that lie adjacent the measuring probe in between the generators and detectors.

An apparatus includes a signal acquisition part acquires oscillation signals from sensors provided under lanes of a bridge and close to an expansion joint, a signal separation part applies BSS to the oscillation signals to estimate source oscillation signals respectively separated in the plurality of lanes, and adjusts amplitude of the source oscillation signals to output amplitude adjusted oscillation signals, and a vehicle estimation part estimates, from the amplitude adjusted oscillation signal, a response oscillation due to a vehicle passing on the lane of interest to detect and count vehicles passing on the lane.

An apparatus includes a signal acquisition part acquires oscillation signals from sensors provided under lanes of a bridge and close to an expansion joint, a signal separation part applies BSS to the oscillation signals to estimate source oscillation signals respectively separated in the plurality of lanes, and adjusts amplitude of the source oscillation signals to output amplitude adjusted oscillation signals, and a vehicle estimation part estimates, from the amplitude adjusted oscillation signal, a response oscillation due to a vehicle passing on the lane of interest to detect and count vehicles passing on the lane.

A system for determining a well placement may include an analysis module. The analysis module, using a Bayesian Decision Network model, may perform a first assessment of data availability, saturation, fracture, and seismic data associated with a candidate area for drilling a first well, and may output a first probability that indicates a potential production level of the first well. The analysis module may perform a second assessment of offset, stress, thickness, and porosity data associated with a second, nearby well, and may output a second probability that indicates a potential production level of the first well if a lateral is placed in a layer and at a azimuth direction. The analysis module may perform a third assessment of tortuosity, washout, and porosity data, and a net-to-gross value associated with the first well and may output a third probability that indicates a completion type for the first well.

Systems and methods are disclosed for identifying and displaying geostructural properties as a function of lithology, horizons, and faults interpreted from well and seismic data. Exemplary implementations may include obtaining an initial fracture distribution grid model; obtaining training structural deformation data; obtaining training subsurface lithology parameter data; obtaining training fracture attribute data; and training the initial fracture distribution grid model to generate a trained fracture distribution grid model.

A method is disclosed that includes obtaining a seismic data set and a seismic wave propagation velocity model and approximating the seismic wave propagation velocity model as a plurality of layers each bounded by a first and second bounding depth. For each of the plurality of layers, the method includes: simulation of the propagation of a seismic wave through the layer using a two-way seismic wave propagation simulator; forming an over-determined system of linear equations relating at least one mono-frequency component of the seismic wave at the first depth to one mono-frequency component at the second depth; and determining a plurality of one-way seismic wave propagation operators by inverting the over-determined system of linear equations. The method further includes processing the seismic data set using the one-way seismic wave propagation. A system and a non-transitory computer readable medium for implementing the method are also disclosed.

The present disclosure provides a physics-based and data-driven integrated method for rock burst hazard assessment, including the following steps: determining an initial stress concentration coefficient by conducting grid discretization on an assessment region, and assigning a value to each of grid nodes using a Weibull distribution function; obtaining a stress concentration coefficient value of each grid node under physics-based models; introducing seismic wave CT detection data to obtain stress concentration coefficient distribution in the assessment region under the integration of a seismic wave CT detection and its derived characterization stress model; introducing microseismic data to obtain stress concentration coefficient distribution in the assessment region under the integration of a microseismic damage reconstruction stress model; and assessing the degree of rock burst hazard according to the size of the stress concentration coefficient value.

The present disclosure provides a physics-based and data-driven integrated method for rock burst hazard assessment, including the following steps: determining an initial stress concentration coefficient by conducting grid discretization on an assessment region, and assigning a value to each of grid nodes using a Weibull distribution function; obtaining a stress concentration coefficient value of each grid node under physics-based models; introducing seismic wave CT detection data to obtain stress concentration coefficient distribution in the assessment region under the integration of a seismic wave CT detection and its derived characterization stress model; introducing microseismic data to obtain stress concentration coefficient distribution in the assessment region under the integration of a microseismic damage reconstruction stress model; and assessing the degree of rock burst hazard according to the size of the stress concentration coefficient value.

Recorded seismic data includes seismic traces having respective source orientation angles, where the source orientation angles represent deviations in seismic source orientation relative to an inline survey direction. A plurality of designature operators corresponding to respective designature orientation angles within a defined set of designature orientation angles may be generated. For a given member of the defined set of designature orientation angles, a corresponding designature operator may be applied to the recorded seismic data to generate designatured seismic data for the given designature orientation angle. For a given seismic trace having a given source orientation angle, the designatured seismic data may be interpolated to generate a designatured version of the given seismic trace. The results may be stored in a tangible, computer-readable medium.

Recorded seismic data includes seismic traces having respective source orientation angles, where the source orientation angles represent deviations in seismic source orientation relative to an inline survey direction. A plurality of designature operators corresponding to respective designature orientation angles within a defined set of designature orientation angles may be generated. For a given member of the defined set of designature orientation angles, a corresponding designature operator may be applied to the recorded seismic data to generate designatured seismic data for the given designature orientation angle. For a given seismic trace having a given source orientation angle, the designatured seismic data may be interpolated to generate a designatured version of the given seismic trace. The results may be stored in a tangible, computer-readable medium.