Methods for validating reservoir simulation models can include determining one or more time segments of fluid recovery of a reservoir; generating, for a first time segment, one or more streamlines on a full simulation grid corresponding to the reservoir by performing one or more reservoir simulations; generating, for the first time segment, one or more drainage volumes; generating, for the first time segment, grid regions along one or more no-flow boundaries of the one or more drainage volumes; generating, for the first time segment, sector models corresponding to the grid regions; performing, for the first time segment, a history matching process corresponding to a time phase simultaneously on each of the sector models to generate, for each sector model, a history matching output; and comparing, for the first time segment and for each sector model, the history matching output for that sector model to a tolerance threshold.

A computer-implemented method and a related system for determining seismic hazard related data. The method includes processing geological/seismological data associated with an area of unknown hazard using a simulation model, and determining simulated ground motion intensity data associated with the area of unknown hazard. The simulation model is determined based on geological/seismological data associated with an area of known hazard and ground motion intensity data associated with the area of known hazard. Alternatively, or additionally, the method includes processing simulated ground motion intensity data associated with the area of unknown hazard with another simulation model. Such simulation model is determined at least partly based on: geological/seismological data associated with an area of unknown hazard, geological/seismological data associated with an area of known hazard, ground motion intensity data associated with the area of known hazard, and simulated ground motion intensity data associated with the area of known hazard.

A wireline width measuring apparatus and associated method which may be used to measure static and dynamic fracture width in fractures used for energy storage, water injection, or hydrocarbon production. In one embodiment, the method comprises determining a depth of the formation fracture, determining the depth of the bottom of the wellbore, positioning a caliper tool string comprising a caliper apparatus at the bottom of the wellbore, wherein the caliper apparatus is positioned at a depth capable of measuring movement of a window cut into a casing of the wellbore at the depth of the formation fracture, inflating the fracture by injecting a fluid into the fracture, uninflating the fracture by producing the fluid from the fracture, and measuring movement of the window cut into the wellbore while the fracture is inflated and uninflated.

A system for determining completion parameters for a wellbore includes a sensor and a computing device. The sensor can be positioned at a surface of a wellbore to detect data prior to finishing a completion stage for the wellbore. The computing device can receive the data, perform a history match for simulation and production using the sensor data and historical data, generate inferred data for completion parameters using the historical data identified during the history match, predict stimulated area and production by inputting the inferred data into a neural network model, determine completion parameters for the wellbore using Bayesian optimization on the stimulated area and production from the neural network model, profit maximization, and output the completion parameters for determining completion decisions for the wellbore.

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 system includes a processor and a memory. The memory includes instructions that are executable by the processor to cause the processor to receive basin data of a target basin including an area of the target basin, a number of exploration wells in the target basin, and a number of discovery wells in the target basin. Additionally, the instructions are executable to cause the processor to provide the basin data as input to a trained machine-learning model to determine a predicted trajectory of exploration efficiency of the target basin. Further, the instructions are executable to cause the processor to, in response to providing the basin data as input to the trained machine-learning model, receive an output from the trained machine-learning model indicating the predicted trajectory of exploration efficiency in the target basin.

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.

Disclosed is a magnetotelluric inversion method based on a fully convolutional neural network. The magnetotelluric inversion method includes: constructing a multi-dimensional geoelectric model; constructing a fully convolutional neural network structure model to obtain initialized fully convolutional neural network model parameters; training and testing the fully convolutional neural network structure model based on the training sets and the test sets to obtain optimized fully convolutional neural network structure model parameters; determining whether training of the fully convolutional neural network structure model is completed according to fitting error changes corresponding to the training sets and the test sets; and finally, inputting measured apparent resistivity into a trained fully convolutional neural network structure model for inversion, and further optimizing the fully convolutional neural network structure model by analyzing precision of an inversion result until an inversion fitting error satisfies a set error requirement.

A method may include obtaining a real-time petrophysical data derived from a plurality of well logs during drilling and utilizing the real-time petrophysical data to quantify a formation damage profile using a resistivity tornado chart and a wellbore modeling. The method further includes utilizing the resistivity tornado chart to determine a depth of invasion inside a formation at each depth in a wellbore by using ratios between different resistivity logs obtained while drilling and creating a synthetic wellbore model by using a fluid flow equation for the wellbore modeling and calculating a time-specific invasion profile to determine a condition at a flowback time. The method further includes performing a computational fluid dynamics investigation in order to identify invaded fluid flow characteristics from the formation to the wellbore and calculating a duration needed to flowback an obtained invaded volume for removal of the formation damage based on a fluid flow behavior.