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.

This disclosure presents a system, method, and apparatus for preventing fracture communication between wells, the system comprising: a sensor coupled to a fracking wellhead, circulating fluid line, or standpipe of a well and configured to convert acoustic vibrations in fracking fluid in the well into an electrical signal; a memory configured to store the electrical signal; a machine-learning system configured to analyze current frequency components of the electrical signal in a window of time and to identify impending fracture communication between the well and an offset well, the machine-learning system having been trained on previous frequency components of electrical signals measured during previous instances of fracture communication between wells; and a user interface configured to return a notification of the impending fracture communication to an operator of the well.

Methods and systems for reservoir characterization use identification of lithostratigraphic layers within a subterranean formation based on rock geochemistry of the subterranean formation. This approach includes: collecting rock samples related to lithostratigraphy of target wells in the subterranean formation; measuring geochemical/mineralogical parameters of the rock samples with laboratory equipment; measuring geochemical/mineralogical parameters of the subsurface formation using wellbore geochemical logging tools in the target wells; measuring formation acoustic velocities for the target wells; generating characteristic rock sample and log signature patterns for different lithostratigraphic layers based on the measured geochemical/mineralogical parameters and acoustic velocities associated with the different lithostratigraphic layers identified in the target wells; combining the characteristic log signatures for the different lithostratigraphic layers into a lithographic interpretation using neutron capture spectroscopy model; and identifying the lithostratigraphic layers within the subterranean formation by applying the model to well logs of non-target wells.

A system, method and program product for implementing a machine learning platform that processes a data map having feature and operational information. A system is disclosed that includes an interpretable machine learning model that generates a function in response to an inputted data map, wherein the data map includes feature data and operational data over a region of interest, and wherein the function relates a set of predictive variables to one or more response variables; an integration/interpolation system that generates the data map from a set of disparate data sources; and an analysis system that evaluates the function to predict outcomes at unique points in the region of interest.

Methods, apparatuses, and computer-readable media are set forth for visualizing and interacting with well production data in a three-dimensional or four-dimensional environment, e.g., using a volumetric well production display representation representing a well in an oilfield and including a plurality of display characteristics configured to display historical production data for the well over a time period.

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.

An approach for reservoir characterization is based on rock geochemistry of the subterranean formation. This approach includes: collecting rock samples related to lithostratigraphy of target wells; measuring geochemical/ mineralogical parameters of the rock samples; measuring geochemical/mineralogical parameters of the subsurface formation; measuring formation acoustic velocities for the target wells; generating characteristic rock sample and log signature patterns for different lithostratigraphic layers based on the measured geochemical/mineralogical parameters and acoustic velocities associated with the different lithostratigraphic layers identified in the target wells; combining the characteristic log signatures for the different lithostratigraphic layers into a lithographic interpretation using neutron capture spectroscopy model; and identifying the lithostratigraphic layers within the subterranean formation by applying the model to well logs of non-target wells.

System, method, and apparatus for classifying fracture quantity and quality of fracturing operation activities during hydraulic fracturing operations, the system comprising: a sensor coupled to a fracking wellhead, circulating fluid line, or standpipe of a well and configured to convert acoustic vibrations in fracking fluid in the fracking wellhead into an electrical signal; a memory configured to store the electrical signal; a converter configured to access the electrical signal from the memory and convert the electrical signal in a window of time into a current frequency domain spectrum; a machine-learning system configured to classify the current frequency domain spectrum, the machine-learning system having been trained on previous frequency domain spectra measured during previous hydraulic fracturing operations and previously classified by the machine-learning system; and a user interface configured to return a classification of the current frequency domain spectrum to an operator of the fracking wellhead.

Systems and methods are provided for determining and presenting field view history-matched well quality data. In one embodiment, a method includes receiving well data for a plurality of wells and performing a plurality of functional operations including a trend operation to determine well groups using pattern recognition of well time lapse pressure trends, the trend operation configured to identify at least one connected reservoir region (CRR), a geo-probe integration operation configured to integrate data for each CRR and evaluate a three-dimensional (3D) static model for wells; a history match advisor operation to generate a combined display of time dependent and depth dependent representation of the well data; a spatio-temporal operation configured to generate a space and time visualization of the well data; a front operation configured to track simulated injected fluid front; and an insight operation configured to report static changes between a well field model and history match model.

The present disclosure relates to systems and methods for treating subterranean formations through adjacent well communications. A method to determine well communication, comprises generating one or more pressure excitation signals via an electrical pump in a first well, wherein the one or more pressure excitation signals produce one or more response signals based on the one or more pressure excitations signals interacting with a subterranean formation; measuring the one or more response signals through transmission of the one or more response signals to a second well with a fiber optic cable, wherein the one or more response signals are measured as time-series data; determining a formation response by processing the one or more response signals with an information handling system; determining a well parameter via one or more sensors; and performing a treatment operation to mitigate well interference between the first well and the second well.