A method can include receiving a first trained machine model trained via unsupervised learning using unlabeled seismic image data; receiving labeled seismic image data acquired via an interactive interpretation process; and building a second trained machine model, as initialized from the first trained machine model, via supervised learning using the received labels, where the second trained machine model predicts stratigraphy of a geologic region from seismic image data of the geologic region.

The present disclosure provides a method of high-resolution amplitude-preserving seismic imaging for a subsurface reflectivity model, including: performing reverse time migration (RTM) to obtain an initial imaging result, performing Born forward modeling on the initial imaging result to obtain seismic simulation data, and performing RTM on the seismic simulation data to obtain a second imaging result; performing curvelet transformation on the two imaging results, performing pointwise estimation in a curvelet domain, and using a Wiener solution that matches two curvelet coefficients as a solution of a matched filter; and applying the estimated matched filter to the initial imaging result to obtain a high-resolution amplitude-preserving seismic imaging result.

A system includes a processor and a memory. The memory includes instructions that are executable by the processor to access a plurality of seismic images of a subterranean formation in a first geological area. The instructions are also executable to generate a plurality of fault estimates from each of the plurality of seismic images. Further, the instructions are executable to generate a processed seismic image of the first geological area by normalizing and merging the plurality of seismic images and the plurality of fault estimates. Additionally, the instructions are executable to generate a statistical fault uncertainty volume of the first geological area using the processed seismic image. Furthermore, the instructions are executable to control a drilling operation in the first geological area using the statistical fault uncertainty volume of the first geological area.

Systems and method are claimed for forming an artifact attenuated seismic image. The method includes obtaining an input seismic image, selecting a seismic partition from the input seismic image and determining a seismic dip for the seismic partition. The method further includes determining flattened seismic partition from the seismic partition based, at least in part, on the seismic dip, determining a filtered seismic partition from the flattened seismic partition, and determining an unflattened seismic segment based on the filtered seismic partition. The method still further includes determining the artifact attenuated seismic image based on the unflattened seismic segment. The system includes a seismic source, a plurality of seismic receivers for detecting and recording an observed seismic dataset generated by the radiated seismic wave; and a seismic processor configured form the artifact attenuated seismic image.

The disclosed embodiments include systems and methods to assess geological data. The method includes obtaining data associated with a geological state of a geological entity. The method also includes assessing a nature of a geological age constraint of the geological entity. The method further includes generating a first probability distribution of a geological age of the geological entity based on the nature of the geological age constraint of the geological entity. The method further includes selecting a time of interest for analysis of the geological entity. The method further includes assessing a nature of the geological age constraint during the time of interest. The method further includes generating a second probability distribution for the time of interest. The method further includes determining a likelihood that the geological age constraint of the geological entity coincides with the time of interest.

This disclosure presents methods and systems to perform fairway analysis on a computing system to automate tasks. The automation of the fairway analysis can reduce bias and uncertainty introduced by a user using their own set of assumptions, estimations, and preferred sequencing of rules and algorithms. The described processes can receive initial input parameters describing the area of interest (AOI) and a geological age range. The processes can retrieve appropriate geological and stratigraphic parameters using the initial input parameters. The combined input parameters can then be geoprocessed using age-aware rules and a determined sequence of algorithms and rules to generate synthesized geological data that can be upscaled and transformed into one or more chance maps indicating the presence and effectiveness of various hydrocarbon elements. The chance maps can be amalgamated and processed to produce a prospective map indicating the likelihood of success of further exploration of the specified AOI.

Systems and methods are provided for determining a formation body wave slowness from an acoustic wave. Waveform data is determined by logging tool measuring the acoustic wave. Wave features are determined from the waveform data and a model is applied to the wave features to determine data-driven scale factors The data-driven scale factors can be used to determine a body wave slowness within a surrounding borehole environment and the body wave slowness can be used to determine formation characteristics of the borehole environment.

Seismic exploration of an underground formation uses seismic excitations to probe the formation's properties such as reflectivity that can be imaged using reverse time migration. Using an equal area spherical binning at reflection points improves and simplifies RTM imaging together with adaptability to the data acquisition geometry, while overcoming drawbacks of conventional cylindrical binning.

Disclosed are methods and systems for detecting and predicting events of increased seismic activity (i.e. earthquake activity). The methods include providing data catalogs, constructing magnitude versus time coordinate graphs, identifying energy levels of the graphs, and identifying further the obliquity angles of maximum and minimum energy levels and average increments between minimum and maximum energy levels. The methods also comprise constructing time arrows using the identified information, identifying energy centers via the time arrows, and analyzing variability throughout the seismic structure to predict a future event. Also disclosed are methods for predicting events based on attenuation wedge and energy parallelogram analysis.

A seismic modeling system is provided which may include a seismic model data storage device, and a processor cooperating with the seismic model data storage device to identify an obstruction within a seismic model spatial domain data set having a lateral boundary, and define a suspect area including spatial domain data within the lateral boundary and directly below the obstruction. The processor may further inpaint the suspect area in the seismic model spatial domain data set based upon an exemplar inpainting algorithm.