In a first step, a defined scope value is selected for each of a plurality of hydrodynamic input parameters. A simulated topographical result is generated using the selected scope values and a forward model. A detailed seismic interpretation is generated to represent specific seismic features or observed topography. A calculated a misfit value representing a distance between the simulated topographical result and a detailed seismic interpretation is minimized. An estimated optimized sand ratio and optimized hydrodynamic input parameters are generated. In a second step, a genetic algorithm is used to determine a proportion of each grain size in the estimated optimized sand ratio. A misfit value is used that is calculated from thickness and porosity data extracted from well data and a simulation result generated by the forward model to generate optimized components of different grain sizes. Optimized hydrodynamic input parameters and optimized components of different grain sizes are generated.

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.

A DAS VSP technique is used to determine the induced fracture height and fracture density of an induced fracture region. The DAS VSP technique obtains pre-hydraulic fracturing DAS VSP survey time-lapse data to establish a baseline reference for the direct acoustic wave travel time. The DAS VSP technique obtains one or more time-lapse data corresponding to the subsequent monitor surveys conducted after each hydraulic fracturing stage along the well. Forward modeling is used to determine a theoretical acoustic wave travel time difference. The forward modeling uses seismic anisotropy to describe the behavior of seismic waves traveling through the induced fracture regions. An inversion scheme is then used to invert for the induced fracture height and the fracture density using the forward modeling. The two extracted induced fracture characteristics may then be used to determine optimal hydraulic fracturing parameters.

A seismic dataset and a task to be performed with the seismic dataset may be received. A representative seismic line representative of the seismic dataset may be generated. The representative seismic line may include pixel data representative of the seismic dataset. Based on the representative seismic line, the task may be performed. The task may include at least finding an analogous geological region by searching for an analogous seismic dataset existing in a seismic database by comparing the representative seismic line with the analogous seismic dataset's representative seismic line.

A method is described for generating a subsurface model using stochastic full waveform inversion by receiving a seismic dataset representative of a subsurface volume of interest; performing stochastic full waveform inversion of the seismic dataset to generate a long wavelength subsurface model; and performing full waveform inversion of the seismic dataset using the long wavelength subsurface model as a starting model to generate an improved subsurface model. The method may further include performing seismic imaging of the seismic dataset using the improved subsurface model to generate a seismic image and identifying geologic features based on the seismic image. The method may be executed by a computer system.

The present disclosure provides a design method for a distributed hydrological cycle model based on a multi-source complementary water supply mode, the method including the following steps: S1, nested hydrological response unit (HRU) division; S2, HRU attribute design; S3, design of a multi-source complementary water supply module; and S4, improvement on a SWAT model. Based on the Soil and Water Assessment Tool (SWAT) model, the present disclosure develops a distributed natural-artificial hydrological dynamic reciprocal simulation model. The model is endowed with the functions of simulating dynamic reciprocation of natural water cycle and artificial water cycle, and integration of development, utilization and regulation of water resources, thereby simulating a natural-artificial hydrological cycle based on modes of urban multi-source water supply and multi-source irrigation water supply.

A method may include obtaining fracture image data regarding a geological region of interest. The method may further include determining various fractures in the fracture image data using a first artificial neural network and a pixel-searching process. The method may further include determining a fracture model using the fractures, a second artificial neural network, and borehole image data. The method may further include determining various fracture permeability values using the fracture model and a third artificial neural network. The method may further include determining various matrix permeability values for the geological region of interest using core sample data. The method may further include generating a coarsened grid model for the geological region of interest using a fourth artificial neural network, the matrix permeability values, and the fracture permeability values.

A method for fracture dynamic hydraulic properties estimation and reservoir simulation may include obtaining a first set of images of a first fracture. The method may include obtaining a first set of fracture detections from the first set of images, generating a plurality of numerical calculations based on the first set of fracture detections, and generating a second model based on the plurality of numerical calculations and the first set of fracture detections. The method may further include obtaining a second set of images of a second fracture of a new reservoir, generating a second set of fracture detections of the second fracture, and generating dynamic hydraulic estimations of the second fracture. The method may also include generating a three-dimensional reservoir simulation and determining a plurality of recovery schemes for the new reservoir.

A computer-implemented method, and system implementing the method, are disclosed for computing a final model of elastic properties, using nonlinear direct prestack seismic inversion for Poisson impedance. User inputs and earth-model data is obtained over points of incidence of a survey region, at various angles of incidence. Various models are then computed that serve for lithology identification and fluid discrimination and take part in preliminary seismic exploration and reservoir characterization. Therefore, further refinement of these models is required due to changes in burial depths, compaction and overburden pressure, as they provide limitations for reservoirs on porous media. The further refinement using nonlinear direct prestack seismic model is performed on a system computer, which produces a final model of elastic properties. This model can then be applied for lithology prediction and fluid detection to identify potential targets of oil and gas exploration and estimating spots in unconventional shale gas applications.

Methods and systems are disclosed for forming an image of a subterranean region of interest. The method includes receiving an observed seismic dataset and a seismic velocity model for the subterranean region of interest, and generating a simulated seismic dataset based on the seismic velocity model and the geometry of the observed seismic dataset. The method further includes determining a transformed observed seismic dataset by applying a nonlinear amplitude transform to the observed seismic dataset and determining a transformed simulated seismic by applying the same transform to the simulated seismic dataset. The method still further includes forming an objective function based on the transformed observed seismic and the transformed simulated seismic dataset, and determining an updated seismic velocity model based upon finding an extremum of the objective function.