A seismic observation device includes: a waveform acquisition unit that acquires waveform data for a predetermined period including an observation start time of a P wave; a delay time specifying unit that inputs the waveform data to a trained model and acquires, from the trained model, a delay time from the observation start time of the P wave to an observation start time of an S wave; and an observation time estimation unit that estimates the observation start time of the S wave based on the observation start time of the P wave and the delay time.

A seismic observation device includes a vibration detection status information acquisition that acquires vibration detection status information at each of a plurality of observation points, a multidimensionalization unit that generates vibration detection status information in two or more dimensions related to a geographical position and a time on the basis of the vibration detection status information at each of the plurality of observation points, and a group specifying unit that classifies element information that forms the vibration detection status information in two or more dimensions and each piece of which indicates a vibration detection status at a certain geographical position and a certain time into groups for each cause of vibration.

A seismic observation device includes an input unit receiving input of time-series data of measurement values of a vibration, a processing target determination unit determining a time period of the time-series data that is a processing target, and a type determination unit acquiring a likelihood of classifying a cause of the vibration indicated in the time-series data in the time period into each of types of cause.

Provided is a technique that can suppress erroneous determination of noise as an earthquake in a seismic sensor and erroneous output of a shut-off signal. The seismic sensor includes: an earthquake determination unit configured to determine an occurrence of an earthquake based on acceleration measured in a determination period after shifting from a power saving mode to a measurement mode with higher power consumption when measured acceleration exceeds a predetermined threshold; and an index calculator configured to calculate an index value indicating a scale of an earthquake in an earthquake processing period after the determination period, when the earthquake determination unit determines that an earthquake has occurred. The seismic sensor causes output of a shut-off signal when the index value is equal to or larger than a threshold in the earthquake processing period. The seismic sensor further includes: a continuous earthquake determination unit configured to determine whether or not an earthquake has occurred, based on acceleration measured in the earthquake processing period; and a shut-off determination unit configured to inhibit output of the shut-off signal regardless of the index value when the continuous earthquake determination unit determines that no earthquake has occurred.

The techniques described herein relate to methods, apparatus, and computer readable media for real-time induced seismicity management. A distribution value, such as a b value, and an uncertainty of the distribution value is calculated based on the received magnitude data, wherein the distribution represents the proportion of each magnitude earthquake observed in the distribution. A seismogenic index is calculated based on a set of fluid injection rates and the distribution value, wherein the seismogenic index represents the proportion of earthquakes per volume of fluid injected into the earth at a particular location. A distribution of a number of earthquakes that will be induced of each magnitude from future injection is forecasted based on the seismogenic index. A ground motion prediction model is calculated, representing shaking intensity and distance based on the forecasted distribution of earthquakes. Seismicity can then be managed to not exceed a tolerated chance of induced shaking consequences.

Providing real-time prediction and mitigation of seismically-induced effects comprises receiving measured seismic data; pre-processing to transform to a uniform format; inputting the preprocessed data into a predictive model; training the predictive model to learn hidden patterns in recorded seismic data, and extract underlying relations between the received measured seismic data and a predicted response at a location of interest at further time instance, as described by the equation: u.sub.I.sup.pred(t+τ)=model(u.sub.I(t), u.sub.M.sub.1(t), u.sub.M.sub.2(t), . . . , u.sub.M.sub.N (t)), where t is current time instance, τ is lead time, u.sub.M.sub.i(t) represents digital signal recorded by the i.sup.th seismic sensor, and N is overall number of sensors in a sensor array that provided the measured seismic data; receiving new real-time seismic data and pre-processing the received new real-time seismic data into the uniform format; inputting the data into the predictive model; and predicting future response at the location of interest in lead time of τ ahead: u.sub.I.sup.pred(t+τ).

The present invention describes a mechanical coupling microseismic monitoring system, which includes at least one microseismic sensor, push rods that are arranged at both ends of the microseismic sensor through a first connection mechanism to send the microseismic sensor into the monitoring hole, introduction mechanisms that are mounted on the push rods for introducing the microseismic sensor into the monitoring hole, and one microseismic monitoring computer that receives signals from the microseismic sensor; the microseismic sensor is a recoverable microseismic sensor; the first connection mechanism is a connection mechanism that can make the push rod swing relative to the microseismic sensor; the introduction mechanism is a three-roller introduction mechanism. The present invention meets the requirement of microseismic monitoring for different parts of deep monitoring hole using multiple microseismic sensors.

An earthquake sensing module includes an acceleration sensor configured to detect accelerations on a plurality of detection axes, a module control unit configured to control the acceleration sensor, and a module storage unit configured to store state information of the acceleration sensor.

A seismic sensor according to one or more embodiments may include: an acceleration measuring unit configured to repeatedly measure acceleration in three directions orthogonal to each other; and an index value calculator configured to operate in a measurement mode for calculating an index value of a magnitude of an earthquake based on a measurement result of acceleration in at least one direction by the acceleration measuring unit, and to operate in a standby mode with less power consumption than power consumption in the measurement mode. Then, the acceleration measuring unit monitors establishment of an activation condition that N times (M≥N≥2) measurement results in consecutive M times (M≥2) measurement results of acceleration in a predetermined direction exceed an acceleration threshold value. When the acceleration measuring unit detects establishment of the activation condition, the index value calculator transitions from the standby mode to the measurement mode.

A device for assigning to the unknown onset of a signal in a noisy time series a probability of that onset having a signed excursion away from the trace mean including one or more means arranged to: define a polarity at a given time sample by reference to the sign of the amplitude difference between the extrema immediately before and after the given time sample in the time series; define a positive and a negative polarity probability density function; take the respective products of the positive and negative polarity probability density functions with an onset probability density function defining the probability that the onset of the signal occurs at a given time sample; and marginalize the respective products of the positive and negative polarity probability density functions with the onset probability density function over time to estimate final probabilities that the onset has a positive or a negative polarity.