A method, computer program product, and computing system for generating high resolution slowness logs. The method computer program product, and computing system includes receiving a plurality of sonic logs from at least one sensor array and generating at least one high-resolution slowness log from the plurality of sonic logs based upon, at least in part, monopole and dipole data from the plurality of sonic logs.

Systems, methods, and apparatus including computer-readable mediums for forecasting hydrocarbon reservoir properties such as well log responses and petrophysical parameters using artificial intelligence are provided. In one aspect, a method of forecasting well logs of a target well includes obtaining well data of the target well including depth and geological information and reservoir parameters and estimating jointly multiple well logs of the target well by utilizing an artificial intelligence (AI) network with the well data of the target well. The AI network is trained based on well data of existing wells that includes multiple reservoir parameters of the existing wells jointly as inputs and multiple well logs of the existing wells jointly as outputs. The estimated multiple well logs of the target well are reconciled with each other, with the well logs of the existing wells, and with geographic formation associated with the target well and the existing wells.

Systems, methods, and computer-readable media for determining the production rate of oil produced from each of a plurality of oil-bearing geological layers in an oil field. In some embodiments, the method comprises allocating injected fluid into each layer of a plurality of oil-bearing geological layers to a plurality of paths from injection sites of injection wells to production wells in each layer by balancing the mass of fluid injected into and the total fluid recovered from each oil-bearing geological layer. In some embodiments, the method comprises calculating estimated geological properties for each path in the plurality of paths to match total oil and injection fluid recovered at each production well in the plurality of production wells. In some embodiments, the method comprises using the estimated geological properties, calculating an oil production rate for each path between an injector well and a production well in a geological layer.

A system can determine a location for future wells using machine-learning techniques. The system can receive seismic data about a subterranean formation and may determine a set of seismic attributes from the seismic data. The system can block the set of seismic attributes into a set of blocked seismic attributes by distributing the set of seismic attributes onto a geo-cellular grid representative of the subterranean formation. The system can apply a trained machine-learning model to the set of blocked seismic attributes to generate a composite seismic parameter. The system can distribute the composite seismic parameter in the subterranean formation to characterize formation locations based on a predicted presence of hydrocarbons.

A method for identifying a medium structure coupling and a fracture network morphology of a shale gas reservoir includes the following steps. Firstly, performing a fracturing test on shale cores by using a modified Brazilian disc test and categorizing the fracture network morphology. Secondly, performing a shale matrix-fracture structure and stress sensitivity test on the shale cores having different fracture network morphology. After that, determining a stress sensitivity constant of different fracture network morphology according to indoor core data and finally preparing an identification chart of the fracture network morphology based on an indoor core stress sensitivity test combined with a production practice. The identification chart can be applied to an actual fracturing well, and the fracture network morphology is directly identified by a real-time effective stress and a normalized flow.

A method for imaging non-specular seismic events as well as correlating non-specular events with physically measurable quantites in a volume of Earth's subsurface. Includes entering as input to a computer signals detected by a plurality of seismic sensors disposed above and/or within the volume in response to actuation of at least one seismic energy source above and/or within the volume. Parameter analysis is performed to populate the initial model with point-wise, best-fit wavefront travel-time approximations. Imaging is performed to obtain undifferentiated specular and non-specular representations of the volume. Specular boundaries are mapped using the imaged volume and using the boundaries to form a model of specular components of the volume. Beamforming is used to characterize seismic attributes associated with specular and non-specular reflections as separate and differentiated data sets.

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.

System and method of developing a hydrocarbon reservoir that includes the following: determining, for each of the layers, a reservoir model defining layers representing a portion of a hydrocarbon reservoir; determining points of intersection; generating, for each of the layers, a two-dimensional (2D) unstructured mesh layer including a triangulated mesh; generating, for each pair of adjacent 2D unstructured mesh layers of the reservoir model, a three-dimensional (3D) tetrahedral mesh; generating, for the 3D tetrahedral mesh, a 3D triangulated tetrahedral mesh; generating, for the 3D triangulated tetrahedral mesh, a 3D vertically-refined triangulated tetrahedral mesh; generating, for the 3D vertically-refined triangulated tetrahedral mesh, a 3D dual mesh; and generating, using the 3D dual mesh, a simulation of the hydrocarbon reservoir represented by the layers.

The present disclosure belongs to the field of capture, utilization, and storage of carbon dioxide, particularly relates to a method and system for intelligently identifying a carbon storage box based on a GAN network, and aims at solving the problem that the analysis accuracy of a fault zone area in the prior art is insufficient. The method comprises the steps: delineating seismic waveform data of a stable sedimentary area through a GAN network, and removing seismic waveform data points in the fault zone area; obtaining a stable sedimentary background seismic waveform data invertomer; obtaining a three-dimensional wave impedance prediction data volume; making a difference to obtain an abnormal wave impedance data volume; retaining abnormal wave impedance data of fault-karst in the three-dimensional variance attribute volume to obtain a fault-karst wave impedance data volume; and then obtaining a carbon storage box interpretation model.

Systems and methods are disclosed for generating subsurface data as a function of position and time. Exemplary implementations may include obtaining a first initial subsurface model and a first set of subsurface parameters, obtaining training subsurface property data and a first training subsurface dataset, generating a first conditioned subsurface model, and storing the first conditioned subsurface model.