A method of evaluating a subterranean formation includes conveying a tool along a borehole. The tool includes a transmitter that transmits a drive pulse and a receiver that receives at least one formation response to the drive pulse. The method further includes calculating a signal-to-noise ratio of the at least one formation response and comparing the signal-to-noise ratio to a programmable threshold. The method further includes determining, based on the comparing, an adjusted drive pulse to transmit and transmitting the adjusted drive pulse. The method further includes and receiving at least one formation response to the adjusted drive pulse and deriving formation data from the at least one formation response to the adjusted drive pulse. The method further includes displaying a representation of the formation based on the formation data.

A method and system for modeling a subsurface region include applying a trained machine learning network to an initial petrophysical parameter estimate to predict a geologic prior model; and performing a petrophysical inversion with the geologic prior model, geophysical data, and geophysical parameters to generate a rock type probability model and an updated petrophysical parameter estimate. Embodiments include managing hydrocarbons with the rock type probability model. Embodiments include checking for convergence of the updated petrophysical parameter estimate; and iteratively: applying the trained machine learning network to the updated petrophysical parameter estimate of a preceding iteration to predict an updated rock type probability model and another geologic prior model; performing a petrophysical inversion with the updated geologic prior model, geophysical seismic data, and geophysical elastic parameters to generate another rock type probability model and another updated petrophysical parameter estimate; and checking for convergence of the updated petrophysical parameter estimate.

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.

Systems, methods, and apparatuses for determining pore volume and pore volume compressibility of secondary porosity in rock samples is disclosed. In some implementations, determining a pore volume of a secondary porosity in a rock core sample may include saturating the rock sample with deuterium oxide (D2O) by applying a vacuum to the core sample covered by D2O; centrifuging the saturated rock sample at a selected rotational speed in the presence of a second fluid to displace a portion of the D2O from the rock sample with the second fluid; measuring the rock sample with low-field .sup.1H nuclear magnetic resonance (NMR) to determine a volume of the second fluid within the rock sample; and determining a pore volume associated with a secondary porosity based on the volume of the second fluid within the rock sample.

A method of calculating the temperature and/or porosity of a geological structure, wherein there is provided at least two geophysical parameters of the geological structure, the method including inverting the at least two geophysical parameters to estimate the temperature and/or porosity of the geological structure.

A method for determining a favorable time window of an infill well of an unconventional oil and gas reservoir, which comprises the following steps: S1, establishing a three-dimensional geological model with physical properties and geomechanical parameters; S2, establishing a natural fracture network model in combination with indoor core-logging-seismic monitoring; S3, calculating complex fractures in hydraulic fracturing of parent wells; S4, establishing an unconventional oil and gas reservoir model and calculating a current pore pressure field; S5, establishing a dynamic geomechanical model and calculating a dynamic geostress field; S6, calculating complex fractures in horizontal fractures of the infill well in different production times of the parent wells based on pre-stage complex fractures and the current geostress field; S7, analyzing a microseismic event barrier region and its dynamic changes in infill well fracturing; and S8, analyzing the productivity in different infill times, and determining an infill time window.

Systems, methods, and apparatuses for determining pore volume and pore volume compressibility of secondary porosity in rock samples is disclosed. In some implementations, determining a pore volume of a secondary porosity in a rock core sample may include saturating the rock sample with deuterium oxide (D2O) by applying a vacuum to the core sample covered by D2O; centrifuging the saturated rock sample at a selected rotational speed in the presence of a second fluid to displace a portion of the D2O from the rock sample with the second fluid; measuring the rock sample with low-field .sup.1H nuclear magnetic resonance (NMR) to determine a volume of the second fluid within the rock sample; and determining a pore volume associated with a secondary porosity based on the volume of the second fluid within the rock sample.

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.

A method of predicting model parameters (R.sub.1, R.sub.2, R.sub.3, . . . ) of a geological formation under investigation, wherein said geological formation is distinguished by reservoir parameters including observable data parameters and the model parameters (R.sub.1, R.sub.2, R.sub.3, . . . ) to be predicted, comprises the steps of calculating at least one model constraint (M.sub.1, M.sub.2, M.sub.3, . . . ) of the model parameters (R.sub.1, R.sub.2, R.sub.3, . . . ) by applying at least one rock physics model (f.sub.1, f.sub.2, f.sub.3, . . . ) on the model parameters (R.sub.1, R.sub.2, R.sub.3, . . . ), said at least one model constraint (M.sub.1, M.sub.2, M.sub.3, . . . ) including modelled data of at least one of the data parameters, and applying an inverse model solver process on observed input data (d.sub.1, d.sub.2, d.sub.3, . . . ) of at least one of the data parameters, including calculating predicted model parameters, which comprise values of the model parameters (R.sub.1, R.sub.2, R.sub.3, . . . ) which give a mutual matching of the input data and the modelled data, wherein the modelled data are provided with probability distribution functions, the inverse model solver process is conducted based on the probability distribution functions, wherein multiple predicted values of the model parameters are obtained comprising values of the model parameters (R.sub.1, R.sub.2, R.sub.3, . . . ) which give the mutual matching of the input data and the modelled data, and model probabilities of the predicted model parameters are calculated in dependency on the probability distribution functions.

Methods and an alarming system for long-term carbon dioxide sequestration in a geologic reservoir are described. The geologic reservoir may be a water filled sandstone reservoir or a carbonate reservoir. A reservoir model is constructed to show the effects of varying injection pressures, the number of injection wells, the arrangement of injection wells, the boundary conditions and sizes of the reservoir on caprock uplift, fracture formation and fracture reactivation. The alarming system generates an alarm when caprock uplift that surpasses a threshold is detected. The injection pressures and the number of injection wells operating may be varied in response to the alarm.