Abstract: The disclosure relates to determining rock properties of subterranean formations and learning the distribution of hydrocarbons in the formations. A geometrical element spread function is disclosed that quantifies distortion of the geology as seen by the geophysicists who process seismic images of the subterranean formations. A method of determining the rock properties using the seismic images and synthetic images is provided. In one example, the method includes: (1) obtaining seismic data from a subterranean formation using a seismic acquisition system, (2) generating one or more seismic images of the subterranean formation using the seismic data, (3) creating one or more synthetic images from the one or more seismic images, and (4) determining rock properties of the subterranean formation based on the one or more seismic images and the one or more synthetic images.

Abstract: A geoscience knowledge system can be obtained, where the geoscience knowledge system can include one or more of publicly available information, industry information, proprietary information, or task specific information. The geoscience knowledge system can be represented as a graph, graph data, network nodes, image data, tokenized data, or textualized data. Subsurface information can be obtained such as from seismic images or other types of sensor data. The subsurface information can be transformed or pre-processed, such as denoising, to make it suitable for use by the geoscience knowledge system. Then subsurface knowledge can be inferred from the subsurface information using the geoscience knowledge system. The subsurface knowledge can provided estimates, approximations, or value of the subterranean formation of interest in order to calculate an economic model parameter, such as a hydrocarbon distribution proximate the subterranean formation of interest.

Abstract: Systems and methods include a computer-implemented method: Seismic data is gathered for a reservoir with unknown fractured and unfractured areas. A structural model is generated. A geomechanical model is built. Geomechanically-estimated fractured areas are determined using the geomechanical model, including: areas where fractures are not likely to exist based on a likelihood lower than a first threshold likelihood, areas where fractures are likely to exist based on a likelihood greater than a second threshold likelihood, and areas where fracturing is unknown based on a likelihood between the first threshold likelihood and the second threshold likelihood. Machine learning-based estimates of a likelihood of a fracture of each area of the reservoir are determined using machine learning based on mathematical calculations of the seismic data.

Abstract: Systems and methods for training a model that refines estimated parameter values include computer processors and non-transitory electronic storage that stores subsurface map data sets that correspond to different subsurface volumes of interest, the system configured to obtain training data including unrefined subsurface map data sets specifying estimated parameter values of a first parameter as a function of position within corresponding subsurface volumes of interest, obtain an initial seismic mapping model, generate a conditioned seismic mapping model, and store the conditioned seismic mapping model in the electronic storage.

Abstract: A method is described for seismic imaging that will produce a seismic image with correctly focused and positioned reflectors. This is accomplished by adding physical geological information to a beam tomography process to generate an updated earth model for the seismic imaging. The method may be executed by a computer system.

Abstract: A method is described for seismic facies identification including receiving a seismic dataset representative of a subsurface volume of interest; performing a machine learning algorithm on the seismic dataset to identify seismic facies and generate a classified seismic image; and identifying geologic features based on the classified seismic image. The method may be executed by a computer system.

Abstract: A method is described for seismic imaging that will produce a seismic image with correctly focused and positioned reflectors. This is accomplished by adding physical geological information to a beam tomography process to generate an updated earth model for the seismic imaging. The method may be executed by a computer system.

Abstract: A method is described for seismic imaging including receiving a seismic dataset representative of a subsurface volume of interest and an earth model; decomposing the seismic dataset into a set of data sub-sets based on a decomposition function; imaging each data sub-set using the earth model to generate a set of image sub-sets; and combining the set of image sub-sets based on a criterion to create a high resolution seismic image. The method may be executed by a computer system.

Abstract: A method is described for modifying an earth model including receiving an earth model containing one or more surfaces with surface geometries, such that at least two surface depth locations exist for some horizontal positions; perturbing elastic properties within the earth model; and generating a modified earth model by modifying the surface geometries within the earth model while preserving seismic travel times of the earth model such that after an initial user parameterization all updates of the surfaces are done without additional user input. The method may be executed by a computer system.

Abstract: A method is described for seismic imaging including receiving a digital seismic image representative of a subsurface volume of interest and an earth model; decomposing the seismic image into a set of image subsets based on an image-domain decomposition function; forward modeling each image subset to generate a set of synthetic data subsets; decomposing each data subset into a set of data sub-subsets based on a data-domain decomposition function; imaging data sub-subsets using the earth model to generate a set of image sub-subsets; and combining the set of image subsets based on a criterion to create a high resolution seismic image. The method may be executed by a computer system.

Abstract: A method is described for seismic imaging including receiving a digital seismic image representative of a subsurface volume of interest and an earth model; decomposing the seismic image into a set of image sub-sets based on a decomposition function; forward modeling each image sub-set to generate a set of synthetic data sub-sets; imaging each synthetic data sub-set using the earth model to generate a set of image sub-sets; and combining the set of image sub-sets based on a criterion to create a high resolution seismic image. The method may be executed by a computer system.

Abstract: A method is described for seismic imaging including receiving a digital seismic image representative of a subsurface volume of interest and an earth model; decomposing the seismic image into a set of image subsets based on an image-domain decomposition function; forward modeling each image subset to generate a set of synthetic data subsets; decomposing each data subset into a set of data sub-subsets based on a data-domain decomposition function; imaging data sub-subsets using the earth model to generate a set of image sub-subsets; and combining the set of image subsets based on a criterion to create a high resolution seismic image. The method may be executed by a computer system.

Abstract: A method is described for seismic imaging including receiving a seismic dataset representative of a subsurface volume of interest and an earth model; decomposing the seismic dataset into a set of data sub-sets based on a decomposition function; imaging each data sub-set using the earth model to generate a set of image sub-sets; and combining the set of image sub-sets based on a criterion to create a high resolution seismic image. The method may be executed by a computer system.

Abstract: Systems and methods for training a model that refines estimated parameter values include computer processors and non-transitory electronic storage that stores subsurface map data sets that correspond to different subsurface volumes of interest, the system configured to obtain training data including unrefined subsurface map data sets specifying estimated parameter values of a first parameter as a function of position within corresponding subsurface volumes of interest, obtain an initial seismic mapping model, generate a conditioned seismic mapping model, and store the conditioned seismic mapping model in the electronic storage.

Abstract: A method is described for modifying an earth model including receiving an earth model containing one or more surfaces with surface geometries, such that at least two surface depth locations exist for some horizontal positions; perturbing elastic properties within the earth model; and generating a modified earth model by modifying the surface geometries within the earth model while preserving seismic travel times of the earth model such that after an initial user parameterization all updates of the surfaces are done without additional user input. The method may be executed by a computer system.

Abstract: A method is described for seismic facies identification including receiving a seismic dataset representative of a subsurface volume of interest; performing a machine learning algorithm on the seismic dataset to identify seismic facies and generate a classified seismic image; and identifying geologic features based on the classified seismic image. The method may be executed by a computer system.

Abstract: A method and apparatus for estimating velocity in a subsurface region. Seismic data for a subsurface region may be received. One or more attributes for the seismic data may be calculated. A posterior distribution may be generated. The posterior distribution may represent one or more probabilities of one or more velocities for the attributes. A velocity with uncertainty may be determined for the subsurface region based on the posterior distribution. A pore pressure with uncertainty may be determined based on the velocity with uncertainty.

Abstract: A method and apparatus for estimating velocity in a subsurface region. Seismic data for a subsurface region may be received. One or more attributes for the seismic data may be calculated. A posterior distribution may be generated. The posterior distribution may represent one or more probabilities of one or more velocities for the attributes. A velocity with uncertainty may be determined for the subsurface region based on the posterior distribution. A pore pressure with uncertainty may be determined based on the velocity with uncertainty.