Abstract: A method for predicting oil flow rates is provided. The method includes accessing historical data from a plurality of databases, accessing historical perforation data and historical reservoir properties data from a simulation model, and determining fluid flow values and rock quality index values associated with perforated intervals of the plurality of wells. The method further includes corresponding the fluid flow values and rock quality values to the well production data, training, using the plurality of input values, a machine learning model for predicting oil flow values at perforated intervals of a plurality of target wells, predicting, using the trained machine learning model, the oil flow values at the perforated intervals of the plurality of target wells, and generating a synthetic production log that includes the predicted oil flow values at the perforated intervals of the plurality of target wells.

Abstract: A method for vascular assessment is disclosed. The method, in some embodiments, comprises receiving a plurality of 2-D angiographic images of a portion of a vasculature of a subject, and processing the images to produce a stenotic model over the vasculature, the stenotic model having measurements of the vasculature at one or more locations along vessels of the vasculature. The method, in some embodiments, further comprises obtaining a flow characteristic of the stenotic model, and calculating an index indicative of vascular function, based, at least in part, on the flow characteristic in the stenotic model.

Abstract: Quantifying power usage for a service. An example method may include identifying a dependency model for the service, the dependency model based in part on infrastructure providing the service. The method may also include determining power usage for the service using the dependency model.

Abstract: Reservoir management based on unstructured grid reservoir simulation is improved with machine learning based intelligent automation. Reservoir heterogeneity, geological internal boundary features and well geometry complexity are taken into account to automatically detect well zone and focusing reservoir area by calculating the region-of-interests in the model and defining cell spacing for grid coarsening and refinement in the reservoir. Data points for wells in the reservoir are grouped into reservoir regions according to datasets organized as a convex hull, which is a minimum convex set in spatial geometry which encloses the totality of such data points. The reservoir regions form a basis for grid spacing utilized in the reservoir model.

Abstract: According to one embodiment, a method of displaying model includes: sampling a pattern to acquire an attention point; calculating a spatial or planar distribution that indicates any one of a design density, a lithography target density, a mask transmittance, or an optical image intensity at N points (N being an integer equal to or greater than 1) on the pattern including the attention point; calculating a threshold for the pattern; estimating, based on the distribution and the threshold, N elements respectively corresponding to the N points as a model; and displaying the estimated model.

Abstract: A method of balancing a heating system with a flow system, including a supply flow line (60) and a return flow line (70), a heat source (55) and a pump (10) hydraulic lines (L1-Ln), some having a heating element (H1-Hn) with a balancing valve (V1-Vn). The method includes: carrying out one or more measurements by opening one hydraulic line only and determining a flow rate through the pump and a pressure difference across the pump, establishing a hydraulic model based on the determined flow rate and pressure difference from at least two measurements from step, and at least one additional measurement for at least two hydraulic lines, specifying a desired flow rate for each of the hydraulic lines, and adjusting one or more of the dedicated balancing valves in order to meet the desired flow rate for each of the hydraulic lines by using the hydraulic model.

Abstract: A system for estimating a volume of activation around an implanted electrical stimulation lead for a set of stimulation parameters includes a display; and a processor coupled to the display and configured to: receive a set of stimulation parameters including a stimulation amplitude and a selection of one of more electrodes of the implanted electrical stimulation lead for delivery of the stimulation amplitude; determine an estimate of the volume of activation based on the set of stimulation parameters using the stimulation amplitude and a database including a plurality of planar distributions of stimulation threshold values and a map relating the planar distributions to spatial locations based on the one or more electrodes of the implanted electrical stimulation lead selected for delivery of the stimulation amplitude; and output on the display a graphical representation of the estimate of the volume of activation.

Abstract: 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.

Abstract: Examples described herein relate to apparatuses and methods for predicting strength of a coupon of composite material. A first critical damage event and strain and stress distributions of the coupon is determined by performing a finite element analysis (FEA) of a finite element model of the coupon. The first critical damage event is associated with the strain and stress distributions. The strain and stress distributions are received as inputs to at least one surrogate model. A final load corresponding to a final failure of the coupon is determined using the at least one surrogate model.

Abstract: Techniques and systems for solving a set of constraints are described. Binary decision diagram (BDD) learning can be applied to a proper subset of the first set of constraints to obtain a set of bit-level invariants. The set of bit-level invariants can then be used for solving the set of constraints. The set of bit-level invariants can include (1) forbidden invariants, (2) conditional invariants, and/or (3) bit-level invariants that are determined by applying BDD learning to a conjunction of constraints and range expressions. If multiple implied constraints have a common right-hand-side (RHS) expression, then BDD learning can be applied to the common RHS expression only once.

Abstract: Provided in this disclosure are systems and methods for selection of petrophysical techniques to model reservoirs. Reservoir properties were calculated using two techniques—a deterministic technique and an optimizing petrophysics technique, and simulation models were developed. The technique that yielded a simulation model that aligned more accurately and consistently with the reservoir data was selected to further develop the reservoir model.

Abstract: An electromagnetic measurement tool for making multi-frequency, full tensor, complex, electromagnetic measurements includes a triaxial transmitter and a triaxial receiver deployed on a tubular member. An electronic module is configured to obtain electromagnetic measurements at four or more distinct frequencies. The measurement tool may be used for various applications including obtaining a resistivity of sand layers in an alternating shale-sand formation; computing a dielectric permittivity, a conductivity anisotropy, and/or a permittivity anisotropy of a formation sample; and/or identifying formation mineralization including discriminating between pyrite and graphite inclusions and/or computing weight percent graphite and/or pyrite in the formation sample.

Abstract: The present disclosure relates to a method of calculating the radiogenic heat production (RHP) of a geophysical structure, wherein there is provided at least one geophysical parameter of the geophysical structure, the method including inverting the at least one geophysical parameter to estimate the RHP of the geophysical structure.

Abstract: Embodiments provide techniques for estimating seasonal indices for multiple periods. Some embodiments can receive a signal comprising a plurality of measures sampled over a span of time from an environment in which one or more processes are being executed. Some embodiments may then extract a seasonal effector and a de-seasonalized component from the signal. Next, some embodiments can apply one or more spline functions to the seasonal effector to generate a first model. Some embodiments may then apply a linear regression technique to the de-seasonalized component to generate a second model. Some embodiments may then initiate actions associated with the code. Some embodiments may then generate a forecast of the signal based on the first model and the second model. Next, some embodiments may initiate, based at least in part on the forecast, one or more actions associated with the environment.

Abstract: The embodiments of the invention provide an intelligent prediction method and apparatus for reservoir sensitivity, belonging to the technical field of reservoir sensitivity prediction. The method includes: acquiring a reservoir sensitivity influence factor item related to a reservoir sensitivity result to be predicted and numerical values of corresponding reservoir sensitivity influence factors; determining a corresponding type of database according to the reservoir sensitivity influence factor item; determining whether numerical values of reservoir sensitivity influence factors corresponding to core parameters in the numerical values of the reservoir sensitivity influence factors include a first upper boundary value or a first lower boundary value; and using, according to whether the first upper boundary value or the first lower boundary value is included, different intelligent sensitivity prediction models to calculate the reservoir sensitivity result to be predicted.

Abstract: A domain specific language, or Scenario Description Language (SDL), can be used for quickly enumerating scenarios in a simulation for testing and validating interaction of an object (e.g., an autonomous vehicle) within an environment. Scenarios in a simulation are defined using one or more primitives. Primitives are used to define objects to be instantiated (such as body size, position, orientation, velocities, etc.) and/or actions to be performed by the objects in the simulation (such as wait for a period of time, goal positions, follow a particular object, etc.). The SDL enables simple creation of multiple scenarios by combining primitives combinatorially and in some examples, limiting which scenarios are created to those that correspond to combinations that provide meaningful information. Additionally, the SDL allows for instantiation to be agnostic of map features so that a particular scenario can be instantiated automatically over all possible positions within a map.

Abstract: A solar irradiance intensity estimation apparatus has an estimation model generation unit that generates estimation models of solar radiation intensities at a plurality of observation points based on observed cloud state data and solar radiation intensities observed at the plurality of observation points, an estimation model interpolation unit that generates an estimation model of a solar irradiance intensity at a target point based on the estimation models of solar radiation intensities at the plurality of observation points, and a solar irradiance intensity estimation unit that estimates a solar irradiance intensity at the target point based on a reflection intensity at the target point obtained from the cloud state data and the estimation model of a solar irradiance intensity at the target point.

Abstract: A method for accelerating an explicit finite element analysis (FEA) simulation of a modeled system or process includes performing an initial iteration of the FEA simulation according to a baseline time interval via an FEA computing network, and calculating a criteria ratio of a predetermined set of scaling criteria for the modeled system or process. The method includes determining a time-scaling factor using the criteria ratio via the FEA computing network as a function of the criteria ratio, and then applying the time-scaling factor to the baseline time interval to generate a scaled time interval. The scaled time interval accelerates simulation time of the FEA simulation. The method includes performing a subsequent iteration of the explicit FEA simulation at the scaled time interval using the FEA computing network. The process continues for subsequent iterations, with the time-scaling factor adapting with each iteration.

Abstract: A simulation circuit, that simulates characteristics of transistors is produced to include: an isolation body resistor representing resistance of a channel isolation portion of a transistor; a main body resistor representing resistance of main channel portion of the transistor; an isolation transistor connected to the isolation body resistor; and a body-contact transistor connected to the main body resistor. Simulated data is generated by supplying test inputs to the simulation circuit, while selectively activating either the isolation transistor or the body-contact transistor. Test data is generated by supplying the test inputs to the transistors, and measuring output of the transistors. The simulated data is compared to the test data to identify data differences. The design of the transistors is changed to reduce the data differences. The generation of test data, comparing, and design changes are repeated, until the data differences are within a threshold.

Abstract: A method for monitoring movement of a fluid interface in a composite reservoir includes receiving data related to a composite reservoir. The composite reservoir includes an uninvaded oil zone, a water-invaded transition zone, and an aquifer. A model is generated using the data. The model is updated in response to movement of a fluid interface between the water-invaded transition zone and the uninvaded oil zone in the composite reservoir is identified. The model is also updated in response to movement of water from the aquifer toward the wellbore is also identified, before the fluid interface reaches a wellbore formed in the composite reservoir. A remedial action is determined to take in the wellbore in response to the movement of the fluid interface, the movement of the water, or both.