A data acquisition program, which includes core, image log, microseismic, DAS, DTS, and pressure data, is described. This program can be used in conjunction with a variety of techniques to accurately monitor and conduct well stimulation.

A system for estimating a property of a region of interest includes an acoustic measurement device including a transmitter configured to emit an acoustic signal having at least one selected frequency configured to penetrate a surface of a borehole in an earth formation and produce internal diffuse backscatter from earth formation material behind the surface and within the region of interest, and a receiver configured to detect return signals from the region of interest and generate return signal data. The system also includes a processing device configured to receive the return signal data, process the return signal data to identify internal diffuse backscatter data indicative of the internal diffuse backscatter, calculate one or more characteristics of the internal diffuse backscatter, and estimate a property of the region of interest based on the one or more characteristics of the internal diffuse backscatter.

Disclosed is a method and associated computer program and apparatus for characterising changes within a subsurface volume between a first time and a second time. The method comprises obtaining first seismic data corresponding to the first time and processing this data to obtain a seismic image of the subsurface volume. This processing is reversed for relevant portions of the seismic image to obtain relevant portions of first seismic data. Changes within the subsurface volume between the first time and the second time are characterised by estimating the changes between second seismic data corresponding to the second time and the relevant portions of first seismic data.

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.

Provided are techniques for developing a hydrocarbon reservoir that include: determining a reservoir model of a hydrocarbon reservoir that includes columns of gridblocks that represent a vertical segment of the reservoir; acquiring nano-images of a rock sample of the reservoir; determining, based on the nano-images, properties of an inorganic pore network and an organic pore network of the rock sample; generating a divided reservoir model of the reservoir that represents the inorganic and organic pore networks of the reservoir, including: for each of the columns of gridblocks, dividing each of the gridblocks of the column into: a water-wet gridblock associated with the properties of the inorganic pore network determined based on the nano-images; and an oil-wet gridblock associated with the properties of the organic pore network determined based on the nano-images; and generating, using the divided reservoir model, a simulation of the hydrocarbon reservoir.

Systems and methods for estimating reservoir productivity as a function of depth in a subsurface volume of interest are disclosed. Exemplary implementations may: obtain subsurface data and well data corresponding to a subsurface volume of interest; obtain a parameter model; use the subsurface data and the well data to generate multiple production parameter maps; apply the parameter model to the multiple production parameter maps to generate refined production parameter values; generate multiple refined production parameter graphs; display the multiple refined production parameter graphs; generate one or more user input options; receive the one or more user input options selected by a user to generate limited production parameter values; generate a representation of estimated reservoir productivity as a function of depth in the subsurface volume of interest using visual effects; and display the representation.

Methods and systems for generating heterogeneity indices for reservoirs is provided. The method includes generating a geological model based on physical locations of a plurality of wells in a reservoir, wherein the geological model provides: graphical representations corresponding to the physical locations of the plurality of wells, a plurality of pseudo locations of pseudo wells in the reservoir, and graphical representations corresponding to the pseudo locations of the pseudo wells, determining reservoir properties associated with the pseudo locations of the pseudo wells in the reservoir, determining vertical heterogeneity indices associated with each location of the pseudo locations of the pseudo wells in the reservoir, determining using an interpolation operation associated with the vertical heterogeneity indices, lateral heterogeneity indices associated with each pseudo location of the pseudo locations of the pseudo wells, and generating for display a heterogeneity property model based on the vertical heterogeneity indices and the lateral heterogeneity indices.

Methods for interpreting pressure transient tests and predicting future production for a well are provided. In one embodiment, a method for predicting future production includes beginning a pressure transient test within a well at a wellsite and obtaining pressure measurements of well fluid during the pressure transient test. The method can also include using the obtained pressure measurements to determine probabilistic estimates of input parameters of a pressure transient reservoir model while continuing the pressure transient test. Future production from the well can then be estimated based on the probabilistic estimates of the input parameters. Other methods and systems are also disclosed.

Method and systems are provided that create one or more models of a subsurface geological formation (such as a reservoir characterization model of a hydrocarbon reservoir or a model of some other subsurface geological formation). The method and systems are configured to extend a machine learning ensemble (such as an ensemble tree-based machine learning model such as a random forest learning model) to use or embed data derived from one or more secondary models as part of the training operations of the machine learning ensemble and online use of the trained machine learning ensemble. Such data can provide information that supplements the information contained in the training data/input data.

A method for determining a thermal maturity image of a subterranean region and a non-transitory computer readable medium, storing instructions for executing the method, are disclosed. The method includes, obtaining a seismic dataset for the subterranean region of interest, obtaining a thermal maturity value for a plurality of core samples taken from different positions within the subterranean region, and obtaining a plurality of well log types from the core sampling location. The method further includes determining a calibrated rock physics model based on the plurality of well log types, determining a pore fluid type based on the calibrated rock physics model, and determining a thermal maturity model based on the plurality of core samples, on the pore fluid type, and on the plurality of well logs. The method still further includes determining the thermal maturity image of the subterranean region based on the seismic dataset and thermal maturity model.