The present disclosure provides an earthquake evaluation method based on multi-type geophysical data. The method includes: acquiring natural seismic data about intraplate earthquakes that had occurred, surface elevation data, Bouguer gravity anomaly data, aeromagnetic anomaly data, seismic wave tomography, crustal GPS movement rate and focal mechanism solution in a target region; constructing planar grids of the target region, and respectively performing plane gridding processing on the natural seismic data about the intraplate earthquakes that had occurred, the surface elevation data, the Bouguer gravity anomaly data, and the aeromagnetic anomaly data based on the constructed planar grids of the target region; determining a plane distribution map of a meizoseismal area in the target region based on the data subjected to the plane gridding processing; and superimposing a surface elevation map and the plane distribution map of the meizoseismal area in the target region with the seismic wave tomography, and analyzing the crustal movement on both sides of the meizoseismal area and the matching relationship between the meizoseismal area and the crustal geological structure in combination with the crustal GPS movement rate and the focal mechanism solution so as to determine the geologic origin of a pleistoseismic zone.

Systems and methods for editing multi-Z horizons interpreted from seismic data are provided. A multi-Z horizon having a plurality of surfaces is visualized within a two-dimensional (2D) representation of seismic data displayed via a graphical user interface (GUI) of an application executable at a computing device of a user. Input is received via the GUI from the user for editing one or more of the plurality of surfaces of the multi-Z horizon within a current view of the displayed 2D representation of the seismic data. A location of the received input relative to each of the plurality of surfaces within the current view is determined. The one or more surfaces of the multi-Z horizon are modified based on the location of the received input within the current view. The visualization of the multi-Z horizon within the GUI is updated, based on the modified one or more surfaces.

The present disclosure belongs to the field of capture, utilization, and storage of carbon dioxide, particularly relates to a method and system for intelligently identifying a carbon storage box based on a GAN network, and aims at solving the problem that the analysis accuracy of a fault zone area in the prior art is insufficient. The method comprises the steps: delineating seismic waveform data of a stable sedimentary area through a GAN network, and removing seismic waveform data points in the fault zone area; obtaining a stable sedimentary background seismic waveform data invertomer; obtaining a three-dimensional wave impedance prediction data volume; making a difference to obtain an abnormal wave impedance data volume; retaining abnormal wave impedance data of fault-karst in the three-dimensional variance attribute volume to obtain a fault-karst wave impedance data volume; and then obtaining a carbon storage box interpretation model.

Systems and methods for geochemical sampling grid locations on a seafloor. At least one of the methods includes generating, using received seismic data, an image representing an interpretation of a seafloor horizon surface; extracting, from the image and based on the seismic data, one or more discontinuity attributes of the seafloor horizon surface; extracting, from the image and based on the seismic data, one or more amplitude attributes of a window extending below the seafloor horizon surface; combining the one or more discontinuity attributes and the one or more amplitude attributes; and selecting, using the image and based at least partly on the combining, one or more locations of the seafloor horizon surface for sampling.

A method of estimating a position of a well path within a subsurface formation of the Earth, the method comprising determining a well path estimate using navigation measurements from a downhole tool and a position estimate derived from seismic data. A method of geosteering comprising: estimating a position of the well path and controlling a drill bit in response to the estimated position of the well path to follow a desired well trajectory.

A method is described for assessing subsurface structure uncertainty based on at least one subsurface horizon. The method calculates seismic continuity attributes to determine a mappability of the subsurface horizon(s); determines horizontal uncertainty for each fault in vertical uncertainty for each horizon; generates probabilistic scenarios for a subsurface geometry for at least one conceptual model; and generates a map of geological model uncertainty based on the probabilistic scenarios. In some embodiments, the probabilistic scenarios are stochastic simulations. In some embodiments, generating a map of geological model uncertainty is based on information entropy. The method may be executed by a computer system.

A method may include obtaining, by a computer processor, seismic data regarding a geological region of interest. The method may further include obtaining, by the computer processor, well log data from a wellbore within the geological region of interest. The method may further include determining, by the computer processor, a formation top depth using the seismic data, the well log data, a stratigraphic column, and a machine-learning model. The stratigraphic column may describe an order of various formations within the geological region of interest. The machine-learning model may assign a feature among the seismic data and the well log data to a formation among the formations in the stratigraphic column to determine the formation top depth.

There is disclosed a system and method for analyzing geological features of a reservoir, such as a subterranean hydrocarbon reservoir undergoing changes during different stages of its production, by utilizing an artificial neural network to learn from hydrocarbon reservoir production project. In an aspect, there is provide a system and method for utilizing data collected from 4D seismic studies in order to train an artificial neural network to recognize how physical properties of a hydrocarbon reservoir change over time, as the hydrocarbon reservoir is produced. In an embodiment, the system and method are adapted to generate and obtain a plurality of image slices or image planes derived from a 3D seismic baseline and at least one monitor acquired over the course production of the hydrocarbon reservoir. Corresponding 2D image slices derived from the 3D seismic baseline and a subsequent monitor are correlated and matched and are then used to train an artificial neural network to create a predictive model of how the reservoir may change over time.

Methods of oil and gas exploration that may include: obtaining wavefield data representing recordings from a propagating wavefield through a geophysical volume; obtaining at least one reference digital image of a portion or all of the geophysical volume generated from the recorded wavefield data, wherein the reference image may have a reference sampling ratio and a reference image quality value; selecting a holographic computational method of imaging the wavefield data; selecting a data subset from the wavefield data based on one or more parameters selected from the group consisting of field sampling, imaging sampling, and image quality; decimating the data subset, wherein the decimated data subset may represent a sampling ratio less than the reference sampling ratio; and generating a new digital image based on the selected holographic computational method of imaging, the data subset, and parameters corresponding to the data sub set.

Methods, apparatus, and systems for mapping surface and near surface features and processing artifacts from stacked and processed seismic data are disclosed. In some implementations, a computer system receives a three-dimensional (3D) seismic cube including seismic reflectivity data obtained at a geographical location. The computer system generates a vertical analysis window of the 3D seismic cube. The computer system extracts a second 3D seismic cube from the seismic reflectivity data based on the vertical analysis window. The second 3D seismic cube has multiple vertical amplitude traces associated with the seismic reflectivity data. The computer system generates 3D data comprising multiple frequency traces from the multiple vertical amplitude traces using a domain transform. The computer system generates a two-dimensional (2D) map from the 3D data. The 2D map represents geographical features of the geographical location.