Systems and methods for identifying anomalies in a subterranean formation based on seismic attributes include: receiving a seismic cube and a seismic surface, wherein the seismic cube includes traces recorded at receivers deployed to collect seismic data, and the seismic surface is picked on the seismic cube; extracting seismic wavelets with a selected length from the seismic cube along an intersection with the seismic surface for each spatial coordinate associated with the seismic surface; determining a population trend of the seismic wavelets; and generating a attribute map based on comparing each of the seismic wavelets to the population trend.

A method and device of identifying a fracture are provided in the embodiments of the present application. The method comprises: determining three components of structure quantification for each data point in a seismic data volume; constructing a structure quantification matrix of the data point according to the three components of structure quantification for each of the data points; determining feature value and feature vector of the structure quantification matrix of each of the data points; determining fracture attribute value of the data point according to the feature value and feature vector of the structure quantification matrix of each of the data points; constructing a data volume of the fracture attribute according to the fracture attribute values of respective data points; and performing a fracture extraction for the data volume of the fracture attribute according to the feature vectors of the structure quantification matrix of the respective data points. The embodiments of the present application can improve the accuracy of identifying a minor fracture, so as to realize an effective identification of the minor fracture.

A method of invertibly transforming acoustic log signals comprises steps of: a) inserting into a borehole (11), forming part of a borehole-formation system (11, 12) in which the borehole (11) penetrates a rock formation (12), an elongate acoustic logging tool (17), the acoustic logging tool including at least one dipole acoustic source (28) and, spaced from the acoustic source along the logging tool, a sequential array of two or more acoustic signal receiver stations (29, 31, 32, 33, 34, 36, 37, 38), the receiver stations each including at least one receiver and being spaced along the logging tool (17) from the acoustic source by successively greater known transmitter-receiver distances; b) causing the acoustic source (28) to emit acoustic energy in a manner (I) effecting the propagation in the borehole-formation system (11, 12) towards the receiver stations (29, 31, 32, 33, 34, 36, 37, 38) of plural signal packets exhibiting paths characteristic of at least first and second respective modes one or more of which is dispersive and (II) stimulating at least one receiver of each sequential receiver station (29, 31, 32, 33, 34, 36, 37, 38) to generate at least one output signal per receiver station that is indicative of the signal packets, received at the at least one receiver of each respective receiver station (29, 31, 32, 33, 34, 36, 37, 38), representing the modes in combination with one another; c) transforming the output signals into respective transformed mode signals containing phase and amplitude information of each respective mode across the array and in which estimated phase and amplitude information are linked by an operator to the slowness and attenuation characteristics of the respective mode and the transmitter-receiver distance of the respective receiver station; and d) using the estimated phase and amplitude information for each mode to extract slowness and attenuation information for each mode from the output signals.

A method of identifying regions in a subsurface that may be a hydrocarbon reservoir, the method including: extracting features from cross-attribute clusters; assigning a distance metric and linkage criterion in feature space; calculating, with a computer, a degree of anomaly for the cross-attribute clusters in the feature space; ranking the cross-attribute clusters in accordance with the degree of anomaly; and prospecting for hydrocarbons by investigating a subsurface region in accordance with the rankings.

A method, computing system, and non-transitory computer-readable medium, of which the method includes receiving offset well data collected while drilling one or more offset wells, generating a machine learning model configured to predict drilling risks from drilling measurements or inferences, based on the offset well data, receiving drilling parameters for a new well, determining that the drilling parameters are within an engineering design window, generating a drilling risk profile for the new well using the machine learning model, and adjusting one or more of the drilling parameters for the new well, after determining the drilling parameters are within the engineering design window, and after determining the drilling risk profile, based on the drilling risk profile.

Methods and systems for performing log quality control on well data of non-key wells is provided. A method of identifying elastic facies in non-key wells as part of Log Quality Control (LQC) includes selecting one or more key wells, building a reference model of elastic facies using the well log data of the selected one or more key wells, propagating the reference model to well data of one or more non-key wells, benchmarking the well data of the non-key wells with the reference model, and calibrating the well data of the non-key wells with the reference model.

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.

The present disclosure describes methods and systems, including computer-implemented methods, computer program products, and computer systems for direct gas reservoir detection using frequency amplitude. One computer-implemented method includes spectrally decomposing seismic data associated with a target area into a plurality of mono-frequency volumes. Further, the method includes based on a low-frequency volume of the plurality of volumes, generating a low frequency map of the target area. Yet further, the method includes based on a high-frequency volume of the plurality of volumes, generating a high frequency map of the target area. Additionally, the method includes dividing the low frequency map by the high frequency map to generate a frequency ratio map. The method also includes using the frequency ratio map to identify a subsurface gas reservoir in the target area.

The invention relates to petroleum seismic exploration, and more specifically to a method for gas-bearing reservoir characterization using logging information. In the method, logging information is used as a constraint to indirectly characterize the distribution range of the gas-bearing reservoir by determining the upper and lower boundaries. In addition, this method enables the automatic determination of the optimal calculation parameters according to the characteristics of input data, allowing for more accurate results.

A method, apparatus, and program product analyze time-series data such as seismic data collected from a subsurface formation by splitting a time-series data set such as an individual seismic trace into a plurality of spectral components, each having an associated frequency, determining an instantaneous frequency for each spectral component, determining a frequency difference for each spectral component based at least in part on the associated and instantaneous frequencies therefor, and determining a tuning parameter based at least in part on the determined frequency difference of each spectral component. Doing so enables, for example, thin-bed structures in the subsurface formation to be identified, and in some instances, thicknesses of such structures to be determined.