A method for generating one or more subsurface stress models. The method may include receiving seismic data. A plurality of first geomechanical property models may be generated based at least partially on the seismic data. A second geomechanical property model may be generated based at least partially on the seismic data. The second geomechanical property model may have a lower resolution than the first geomechanical property models. A stress model, a strain model, or a combination thereof may be generated based on the second geomechanical property model. One or more subsurface stress models may be generated based on the stress model, the strain model, or the combination thereof and the first geomechanical property models.

The present disclosure describes methods and systems, including computer-implemented methods, computer program products, and computer systems, for determining a mudweight of drilling fluids in a hydrocarbon reservoir. One computer-implemented method includes: receiving pore pressure data of a rock formation in the hydrocarbon reservoir; determining permeability data of fractures of the hydrocarbon reservoir; determining Hoek-Brown failure criterion data; and determining a safe mudweight window based on the pore pressure data of the rock formation, the permeability data of the fractures, and the Hoek-Brown failure criterion data.

Exemplary implementations may: obtain subsurface relaxation time data specifying subsurface relaxation time values corresponding to a well in the subsurface volume of interest; generating a subsurface relaxation time distribution using the subsurface relaxation time data; generating a subsurface porosity distribution using the subsurface relaxation time distribution; generating a representation of the subsurface porosity distribution in the subsurface volume of interest using visual effects to depict at least one of the one or more subsurface relaxation time values; and display the representation.

Petrographic data of a carbonate reservoir in a subterranean region is received. Mud content of the carbonate reservoir is determined based on the petrographic data. A depositional porosity of the carbonate reservoir is computed based on the mud content. An amount of cementation of the carbonate reservoir is determined. A porosity loss by compaction of the carbonate reservoir is determined based on the mud content and the amount of cementation of the carbonate reservoir. A post-compaction porosity of the carbonate reservoir is computed based on the depositional porosity, the mud content, the amount of cementation, and the porosity loss by compaction.

Certain aspects and features relate to a system that projects an optimized foam-fluid-application scenario for to stimulate production from a hydrocarbon well. The optimized scenario can include a recommended chemical make-up for the foam entity as well as application parameters such those related to timing and duration. A hybrid discrete fracture network and multi-porosity (DFN-MP) model for fluid interaction with the formation where the well is located can be produced by a processing device. The hybrid DFN-MP model can be optimized using field simulation data for the formation. The optimized hybrid DFN-MP model can be used by the processing device to produce an optimized foam-fluid-application scenario, which can be communicated to at least one well and can be utilized to stimulate the well for increased production.

Systems, methods, and computer programs for monitoring a drilling operation in a subterranean formation include receiving, from a first sensor array, one or more seismic signals caused, at least in part, by the drilling operation in the subterranean formation; receiving, from the first sensor array, one or more electromagnetic signals generated by an electroseismic or seismoelectric conversion of the one or more seismic signals caused, at least in part, by the drilling operation in the subterranean formation; and determining a property of one or more of the drillstring and the subterranean formation based, at least in part, on the seismic signals and the corresponding electromagnetic signals received from the first sensor array. The first sensor array is arranged to monitor the drilling operation.

A method for determining properties of a laminated formation traversed by a well or wellbore employs measured sonic data, resistivity data, and density data for an interval-of-interest within the well or wellbore. A formation model that describe properties of the laminated formation at the interval-of-interest is derived from the measured sonic data, resistivity data, and density data for the interval-of-interest. The formation model represents the laminated formation at the interval-of-interest as first and second zones of different first and second rock types. The formation model is used to derive simulated sonic data, resistivity data, and density data for the interval-of-interest. The measured sonic data, resistivity data, and density data for the interval-of-interest and the simulated sonic data, resistivity data, and density data for the interval-of-interest are used to refine the formation model and determine properties of the formation at the interval-of-interest. The properties of the formation may be a radial profile for porosity, a radial profile for water saturation, a radial profile for gas saturation, radial profile of oil saturation, and radial profiles for pore shapes for the first and second zones (or rock types).

A method and apparatus for generating an image of a subsurface region including obtaining geophysical data/properties for the subsurface region; resampling the geophysical data/properties to generate a resampled data set; iteratively (a) inverting the resampled data set with an initial prior model to generate a new model; and (b) updating the new model based on learned information to generate an updated prior model; substituting the initial prior model in each iteration with the updated prior model from an immediately-preceding iteration; and determining an end point for the iteration. A final updated model may thereby be obtained, which may be used in managing hydrocarbons. Inversion may be based upon linear physics for the first one or more iterations, while subsequent iterations may be based upon non-linear physics.

Exemplary implementations may: obtain, from the electronic storage, geological data corresponding to the geographic volume of interest; generate a framework for sediment deposition using a first set of multiple physical, chemical, biological, and geological processes; generate a framework for diagenesis using a second set of multiple physical, chemical, biological, and geological processes; generate a representation of sediment deposition by applying the geological data corresponding to the geographic volume of interest to the framework for sediment deposition; generate a representation of diagenesis based on the framework for diagenesis and the representation of sediment deposition; and display the representation of sediment deposition and the representation of diagenesis on a graphical user interface.

A method and apparatus for generating a fluid saturation model for a subsurface region. One example method generally includes obtaining a model of the subsurface region; for each of a plurality of fluid types: flooding the subsurface region model with the fluid type to generate a flood model; and running a trial petrophysical inversion with the flood model to generate a trial petrophysical model; identifying potential fluid contact regions in the trial petrophysical models; partitioning the subsurface region model at the identified potential fluid contact regions; and constructing the fluid saturation model from the partitioned subsurface region model.