A method for partitioning a search direction when using least squares reverse time migration (LSRTM) is provided. LSRTM may be used iteratively in order to improve imaging accuracy. As part of LSRTM, multiple local line searches may be performed. In particular, image space may be partitioned, such as by using a set of masks. The search direction, such as the gradient, may be partitioned using the set of masks. Local line searches may be performed for each partition of the search direction, resulting in finding respective line search constants. The respective line search constants may then be used for iterating the model in order to improve imaging accuracy.

A method can include accessing volumetric data from a data store, where the volumetric data correspond to a region; generating structured shape information for the region using at least a portion of the volumetric data; and, in response to a command from a client device, transmitting to the client device, via a network interface, a visualization data stream generated using at least a portion of the structured shape information.

A method for generating a geophysical image of a subsurface region includes defining a computational sub-volume for the geophysical image including a predetermined number of seismic traces of a plurality of seismic traces and a predetermined number of samples per each one of the plurality of seismic traces, generating a data matrix corresponding to a first sub-volume of the subsurface region based on the defined computational sub-volume, the data matrix comprising the predetermined number of samples for the predetermined number of traces of a portion of a seismic dataset corresponding to the first sub-volume. The method also includes estimating a coherence between the predetermined number of traces of the data matrix by performing a sum of a variance of the predetermined number of samples of the data matrix, and assigning the estimated coherence to a location in the geophysical image.

Systems and methods for reservoir modeling include a super resolution seismic data conversion platform for converting input seismic data into high resolution output seismic data. The super resolution seismic data conversion platform can perform a super resolution inversion on the input seismic data by imposing sparsity and/or coherency assumptions on geophysical parameters represented by wavelet information of the input seismic data. For instance, a seismic trace interval can be determined, and both a reflection coefficient and an acoustic impedance of the seismic trace interval can be constrained. An optimization problem, using the constrained reflection coefficient and the constrained acoustic impedance, can be generated and/or solved by a sparse inversion. As such, a vertical resolution, as well as a seismic bandwidth, of super resolution output seismic data can be increased, improving subterranean feature (e.g., sand and/or shale characteristics) interpretation and well planning and construction.

The invention is a method applicable to oil and gas exploration and exploitation for automatically detecting geological objects belonging to a given type of geological object in a seismic image, on a basis of a priori probabilities of belonging to a type of geological object assigned to each of samples of the image to be interpreted. The image is transformed into seismic attributes applied beforehand, followed by a classification method. For each of the classes, an a posteriori probability of belonging to a type of geological object is determined for each of the samples of the class according to the a priori probabilities, of the class, of belonging, and according to a parameter describing a confidence in the a priori probabilities of belonging. Based on the class of the sample, the determined a posteriori probability of belonging to a type of geological object is assigned for the samples of the class. The geological objects belonging to the type of geological object are detected based on determined of the a posteriori probabilities of belonging to the type of geological object for each of the samples of the image to be interpreted.

A method of generating diffraction images based on wave equations includes generating a source wavefield and a receiver wavefield. Based on the source wavefield, a first source wavefield propagating in a first direction and a second source wavefield propagating in a second direction are generated. Based on the receiver wavefield, a first receiver wavefield propagating in the first direction and a second receiver wavefield propagating in the second direction are generated. A first seismic image is generated based on the first source wavefield and the first receiver wavefield. A second seismic image is generated based on the second source wavefield and the second receiver wavefield. A final seismic image is generated based on the first seismic image and the second seismic image.

A cloud based storage system and methods for uploading and accessing 3-D data partitioned across distributed storage nodes of the system. The data cube is processed to identify discrete partitions thereof, which partitions may be organized according to the x (e.g., inline), y (e.g., crossline) and/or z (e.g., time) aspects of the cube. The partitions are stored in unique storage nodes associated with unique keys. Sub-keys may also be used as indexes to specific data values or collections of values (e.g., traces) within a partition. Upon receiving a request, the proper partitions and values within the partitions are accessed, and the response may be passed to a renderer that converts the values into an image displayable at a client device. The request may also facilitate data or image access at a local cache, a remote cache, or the storage partitions using location, data, retrieval, and/or rendering parameters.

A method of determining a migration pathway of a subterranean fluid through a geological volume is provided. The starting object is located within the geological volume. The starting object defines an initial fluid boundary. Data points are distributed through the geological volume. The data points are associated with values of one or more geological attributes. The method includes the steps of: defining an expression which determines a change in position of the fluid boundary at the data points over an iteration based on the values of the one or more attributes; and applying the expression at the data points for successive iterations to evolve the fluid boundary over the successive iterations. The migration pathway of the subterranean fluid through the geological volume can then be determined from the evolution of the fluid boundary.

A computer implemented method for processing a seismic image comprising seismic values obtained from seismic measurements performed on a geological formation includes determining a seismic dip image based on the seismic image, said seismic dip image comprising local seismic dips representative of the local gradient of the seismic values of the seismic image; initializing a seismic horizon surface modeled by using a combination of spline functions or by using a triangle mesh; and iteratively modifying coefficients used for combining the spline functions, thereby iteratively modifying the seismic horizon surface to progressively increase alignment between local orientations of the seismic horizon surface and the corresponding local seismic dips, until a predetermined stop criterion is satisfied.

Hydrocarbon exploration and extraction can be facilitated by determining fault surfaces from fault attribute volumes. For example, a system described herein can receive a fault attribute volume for faults in a subterranean formation determined using seismic data. The fault attribute volume may include multiple traces with trace locations. The system can determine a set of fault samples for each trace location. Each fault sample can include fault attributes such as a depth value, an amplitude value, and a vertical thickness value. The system can determine additional fault attributes such as a dip value and an azimuth value for each fault sample of each trace location. The system can determine fault surfaces for the faults using the fault samples and fault attributes. The system can then output the fault surfaces for use in a hydrocarbon extraction operation.