A method for training a well model to predict material loss for a pipe string having a wall thickness and located within a borehole. The method may include measuring the wall thickness of a first pipe string at locations axially along the first pipe string with a logging tool at a first time. The method may also include measuring the wall thickness of the first pipe string at the locations with the logging tool at a second time. The method may further include training a first well model based on a machine learning (ML) algorithm to predict a predicted amount of material loss in the future for the first pipe string at a selected location using the wall thickness measurements at the first and second times and well operating condition information related to the first pipe string.

Systems and methods include a computer-implemented method: Historical and forecasted field life data for existing gas wells is received, including pressure and temperature data at different depths of the existing gas wells over the life of the existing gas wells. Using the historical and forecasted field life data for the existing gas wells, a sub-erosion production rates model is generated for in situ estimation of sub-erosion for gas wells. Well parameters for a subject gas well are received. Using the well parameters of the subject gas well, the sub-erosion production rates model is executed to identify high-erosion risk spots in the subject gas well, including using iteratively evaluating results using three different methods. Outputs of the sub-erosion production rates model are provided for presentation to a user in a graphical user interface (GUI).

A method for obtaining information on quality of combustion of a liquor in a chemical recovery boiler. The method comprises entering a value of a first input parameter to a computational model configured to determine, based on the value of the first input parameter, a value of the quality of combustion of the liquor in the chemical recovery boiler, and at a first time, running the computational model to obtain a first modelling result. The method comprises measuring, from the chemical recovery boiler a value indicative of carryover to obtain a measurement result; comparing the first modelling result with [a] the measurement result or [b] a result derived from the measurement result, to obtain a primary comparison result; and adjusting the value of the first input parameter based on the primary comparison result to obtain an adjusted value of the first input parameter. The method comprises entering the adjusted value of the first input parameter to the computational model, and at a second time, running the computational model to obtain the information on quality of combustion of the liquor in the chemical recovery boiler.

A method for simulating fluid surfaces in real-time in response to user input includes detecting interactive conditions triggering insertion of a heterogeneous mesh sequence in a 3D model sequence for rendering, fetching ones of the heterogenous mesh sequence from a computer memory, inserting the successive members in corresponding representations of the 3D model sequence in a computer memory, and rendering successive video frames from the representations of the 3D model sequence each including a successive member of the heterogenous mesh sequence. A related method for generating a compact heterogeneous mesh sequence for use in rendering corresponding frames of video includes generating a heterogenous mesh sequence modeling response of a fluid surface to physical forces, the heterogenous mesh sequence characterized by position values represented in computer memory by not less than 12 bytes for each vertex thereof, transforming the heterogenous mesh sequence into the compact heterogeneous mesh sequence, at least in part by quantizing the position values to not greater than four bytes, and storing the compact heterogeneous mesh sequence in a computer memory for use in real-time rendering.

Disclosed are computer implemented techniques for correcting for numerically generated pressure waves at an inlet of a simulation space. The techniques include receiving a model of a simulation space and applying an inlet pressure to an inlet of the simulation space. The applied inlet pressure generates fluctuating velocities that produce undesired, numerically-generated pressure waves. The numerically generated pressure waves are measured to establish a measured pressure history. The measured pressure history is subtracted from the applied inlet boundary pressure history to provide a set of boundary conditions. The process conducts a fluid simulation using the set of boundary conditions. The process repeats using a subsequent set of boundary conditions, until an iteration is reached where the measured pressures near the inlet are sufficiently small to compensate for undesired, numerically-generated pressure waves, and thereafter stores that subsequent set of boundary conditions to provide a corrected set of boundary conditions.

A method for simulating a flow in which a structure is submerged, the method being implemented by computer, and the behavior of the structure in the flow being modeled by radial and rotational sources generating a velocity field representing the flow around the structure.

System and methods for training neural network models for real-time flow simulations are provided. Input data is acquired. The input data includes values for a plurality of input parameters associated with a multiphase fluid flow. The multiphase fluid flow is simulated using a complex fluid dynamics (CFD) model, based on the acquired input data. The CFD model represents a three-dimensional (3D) domain for the simulation. An area of interest is selected within the 3D domain represented by the CFD model. A two-dimensional (2D) mesh of the selected area of interest is generated. The 2D mesh represents results of the simulation for the selected area of interest. A neural network is then trained based on the simulation results represented by the generated 2D mesh.

A numerical experimental method for urban waterlogging includes the following steps: acquiring raw data of an urban underlying surface; batch-processing urban waterlogging modeling data; batch-running urban waterlogging numerical experimental models; batch-processing urban waterlogging numerical experimental results; and displaying and analyzing the batch-processed urban waterlogging numerical experimental results. The numerical experimental method constructs a numerical experimental process, which can perform an unlimited number of repeated experiments in the numerical simulation process of urban waterlogging and achieve batch-running of data preprocessing, model operation, and data post-processing processes. Therefore, the numerical experimental method has the advantages of high efficiency, high convenience, high reliability, and low cost.

The present invention provides a simulation method of predicting a behavior of a curable composition in a process of bringing a plurality of droplets of the curable composition arranged on a first member into contact with a second member and forming a film of the curable composition in a space between the first member and the second member, wherein for each of the plurality of droplets of the curable composition, a distance from a representative point of the droplet to a point on a contour of the droplet is obtained so as to match the area of the inner region of the contour to an area of the droplet obtained from a volume of the droplet and a distance between the first member and the second member in accordance with a change of the distance between the first member and the second member.

Techniques for simulating fluid flow using a lattice Boltzmann (LB) approach for solving scalar transport equations and solving for total energy are described. In addition to the lattice Boltzmann functions for fluid flow the techniques include modifying a set of state vectors of the particles by adding specific total energy to states of particles that will be advected and subtracting the specific total energy from states of particles that will not be advected over a time interval and performing advection of the particles according to the modified set of states.