Systems and methods for generating candidate designs and selecting a fracturing position design scheme for a horizontal well to be fractured based on fracturing potential are disclosed. A fracturing potential value of each designed fracturing point or each fracturing point is calculated using obtained values of various indexes of various depth points. A first corresponding relation between fracture conductivity value and the fracturing potential value and a second corresponding relation between a fracture half length and the fracturing potential value is determined. Corresponding first simulated production data for each candidate design is generated, and the candidate design with a highest predicted net present value is selected as the fracturing position design scheme which provides higher rationality and practicability to better guide development.

Geologic modeling methods and systems disclosed herein employ an improved simulation meshing technique. One or more illustrative geologic modeling methods may comprise: obtaining a geologic model representing a faulted subsurface region in physical space; providing a set of background cells that encompass one or more partial faults within the subsurface region; defining a pseudo-extension from each unterminated edge of said one or more partial faults to a boundary of a corresponding background cell in said set; using the pseudo-extensions and the background cell boundaries to partition the subsurface region into sub-regions; deriving a simulation mesh in each sub-region based on the horizons in each sub-region; and outputting the simulation mesh.

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 improved prediction and enhancement of hydrocarbon recovery from ultra-tight/unconventional reservoirs for both the primary production and any subsequent solvent huff‘n’puff periods based on facilitating the diffusion process may include steps of defining one or more initial properties of a reservoir and integrating characterization data of the reservoir; defining a wellbore trajectory for each of at least one well and one or more parameters associated with a completion/reservoir stimulation design; specifying operating conditions for a current development cycle; performing diffusion-based dynamic fracture/reservoir simulation for calculating hydrocarbon recovery and efficiency of a hydrocarbon process; and; determining whether to commence or continue enhanced oil recovery (EOR) or enhanced gas recovery (EGR) cycles.

Systems and methods are disclosed for generating subsurface feature prediction probability distributions from a subsurface feature as a function of position in a subsurface volume of interest. For example, a computer-implemented method may include: obtaining subsurface data and well data, generating subsurface feature values, generating subsurface feature realizations, generating subsurface feature realization uncertainty values, generating subsurface parameter values, generating subsurface parameter realizations, generating subsurface feature prediction probability distributions, generating a first representation of likelihoods of the subsurface feature values, and displaying the first representation.

The invention notably relates to a computer-implemented method of geomodelling. The method comprises providing a pseudo-stratigraphic grid. The pseudo-stratigraphic grid represents a reservoir and has pillars. Each pillar includes respective cells. Each cell has a respective stratigraphic layering index. The method then comprises providing a surface. The surface has a first region and a second region. The second region is complementary to the first region. The method also comprises, for each first pillar intercepted by the first region, determining a respective first stratigraphic layering value based on the relative position of the surface in the first pillar. The method also comprises, for each second pillar intercepted by the second region, determining a respective second stratigraphic layering value by interpolating and/or extrapolating first stratigraphic layering values. This provides an improved solution of geomodeling.

A runoff yield calculation method and device based on double free reservoirs, and a storage medium are provided, the method includes: forming a four-layer vadose zone structure by making a tension water storage layer be located under a deep vadose zone based on a three-layer vadose zone structure of a Xin'anjiang model; dividing a space occupied by free water in the four-layer vadose zone structure into an upper free reservoir and a lower free reservoir; calculating a time interval runoff yield by using a saturation excess runoff method; and dividing, based on a runoff yield structure of the double free reservoirs, the time interval runoff yield into a surface runoff, an interflow and a subsurface runoff. The method proposes a runoff yield structure of double free reservoirs, which can be well applied to semi-arid and semi humid watersheds with deeper buried depth of shallow groundwater.

In one aspect, a system (5) for use in providing an approximation or estimation of a characteristic (for example, a bulk density value) of a deposit subject to a drilling operation is disclosed. In one form, the system (5) comprises a processor module (25) arranged in operable association with a network of sensors (30) operable for measuring one or more parameters relating to the operation of the drilling assembly (10). The processor module (25) is configured operable for receiving data/information derived from the network of sensors (30), and processing the data/information so as to provide a representation of the incursion (eg. depth of penetration into the relevant deposit) achieved by way of the drilling assembly (10). The processor module (25) is further configured for processing the representation of the incursion with a predetermined relationship that is characteristic of, or unique to, the drilling assembly (10) for providing or allowing an approximation/estimation of the characteristic of the deposit as a function of one or more parameters of the incursion to be made.

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.

Techniques for determining one or more hydrocarbon sweet spots include generating a three-dimensional (3D) simulation model of a hydrocarbon reservoir in a subterranean formation; executing a gas winnowing process to the 3D simulation model; applying one or more geomechanical restraints to the 3D simulation model; activating one or more energy simulation parameters with the 3D simulation model; applying a total dynamic productivity index (TDPI) process to the 3D simulation model to generate at least one 3D index that includes one or more hydrocarbon sweet spots; and generating a graphical representation of the generated 3D index for presentation on a graphical user interface (GUI) to a user.