Techniques for calibration of a simulation of a subterranean region having complex fracture geometries. Calibration of indeterministic subsurface discrete fracture network models is performed via non-intrusive embedded discrete fracture modeling formulations applied in conjunction with well testing interpretation and numerical simulation. Subterranean fracture networks are characterized dynamically by embedded discrete fracture modeling to accurately and efficiently determine an optimal fracture model.

Systems and methods for determining object location may include a memory and a processor. The processor may be configured to collect seismic data and geophysical data to determine object location. The processor may be configured to determine one or more seismic attributes associated with a plurality types of noises based on the seismic data and the geophysical data using one or more machine learning algorithms. The processor may be configured to eliminate unwanted noises from noise classifications based on the one or more seismic attributes. The processor may be configured to predict the object location by comparing time and velocity data of the object with recorded timing and velocity data. The processor may be configured to validate the object location by comparing the determined noise with image data. The systems and methods may be used in, for example, detecting missing planes such as Malaysian Airlines Flight 370.

A system can determine a location for future wells using machine-learning techniques. The system can receive seismic data about a subterranean formation and may determine a set of seismic attributes from the seismic data. The system can block the set of seismic attributes into a set of blocked seismic attributes by distributing the set of seismic attributes onto a geo-cellular grid representative of the subterranean formation. The system can apply a trained machine-learning model to the set of blocked seismic attributes to generate a composite seismic parameter. The system can distribute the composite seismic parameter in the subterranean formation to characterize formation locations based on a predicted presence of hydrocarbons.

This disclosure presents processes and systems for estimating a source wavelet from seismic data recorded in a seismic survey of a subterranean formation. In one aspect, a base wavelet is determined based on recorded seismic traces obtained in a seismic survey of a subterranean formation. Processes and systems include a phase-only wavelet based on the base wavelet and the recorded seismic data. An estimated source wavelet is obtained by convolving the base wavelet with the phase-only wavelet. Properties of the subterranean formation are determined based on the estimated source wavelet and the recorded seismic data.

An earthquake estimation method for more promptly estimating an earthquake on the basis of observation data. The earthquake estimation method includes, by a computer: generating an observation image showing a spatial distribution of seismic wave propagation on a basis of an observation result of seismic waves at a plurality of observation points on a ground; and estimating a parameter of an earthquake with respect to the observation image by using an earthquake estimation model in which a parameter of an earthquake including at least a position of a hypocenter and a magnitude is associated with a simulated observation image showing a spatial distribution of seismic wave propagation on a ground obtained from a result of a numerical simulation of the earthquake, performed with the parameter.

A system is described for determining a likelihood of a type of fluid in a subterranean reservoir. The system may include a processor and a non-transitory computer-readable medium that includes instructions executable by the processor to cause the processor to perform various operations. The processor may receive pre-stack seismic data having seismically-acquired data elements for geometric locations in a subterranean reservoir. The processor may determine, using the pre-stack seismic data, input features for each geometric location and may execute a trained model on the input features for determining a likelihood of a type of fluid in the subterranean reservoir and for determining a list of features affecting the likelihood. The processor may subsequently output the likelihood and the list of features.

The present disclosure relates to a method of processing seismic signals comprising: receiving a set of seismic signals, applying a wavelet transformation to the set of signals and generating transformed signals across a plurality of scales. Then for each scale determining coherence information indicative of the transformed signals and generating a comparison matrix comparing the transformed signals, then outputting seismic attribute information based on combined coherence information.

Systems and methods for seismic imaging of a subterranean geological formation include receiving parameter data representing one or more parameters of a seismic survey, the seismic data specifying an incident angle and an azimuth angle for each trace of the seismic survey; determining a relationship between the incident angle and the azimuth angle for each trace and a location in a spiral coordinate system, and generating a weighting function for applying a weight value to each trace seismic data based on the incident angle and the azimuth angle associated with each trace; and determining a residual moveout value of the seismic data for each location in the spiral coordinate system by applying the weighting function to each; and generating a seismic image representing the residual moveout value of the seismic data for each location in the spiral coordinate system.

A device may include a processor that may recover the signals misallocated in the deblending process of seismic data acquired with simultaneous sources. The processor may update the primary signal estimate based at least in part on a separation operation that separates coherence signals from noise signals in an output associated with the residual determined to be remaining energy for separation. The processor may be incorporated into the iterative primary signal estimate of the deblending process or be applied towards preexisting deblending output. In response to satisfying an end condition, the processor may transmit a deblended output that includes the weak coherence signals recovered from the misallocation or error in the primary signal estimate. The processor may also transmit the deblended output for use in generating a seismic image. The seismic image may represent hydrocarbons in a subsurface region of Earth or subsurface drilling hazards.

A method may include obtaining seismic data regarding a geological region of interest. The method may further include obtaining a property model regarding the geological region of interest. The method may further include determining an adjoint migration operator based on the property model. The method may further include updating the property model using the seismic data and a conjugate gradient solver in a least-squares reverse time migration to produce a first updated property model. The conjugate gradient solver is based on the adjoint migration operator. The method may further include updating the first updated property model using a threshold shrinkage function to produce a second updated property model. The threshold shrinkage function comprises a sign function and a maximum function that are applied to the first updated property model. The method may further include generating a seismic image of the geological region of interest using the second updated property model.