The invention relates to a computer implemented method and tool for determining pressure-drop in multiphase pipeline flow where the effective surface roughness, k.sub.eff, of liquid film coated sections of the inner pipeline wall is assumed to be equal to the maximum hydraulic roughness, k.sub.s.sup.max. The maximum hydraulic roughness is further assumed to be proportional to a maximum stable droplet size, d.sub.droplet.sup.max, i.e.: k.sub.eff=k.sub.s.sup.max=K.Math.d.sub.droplet.sup.max, where K is a correlation coefficient. The invention further relates to applying the computer implemented method for designing a pipeline-based fluid transport system for transport of multiphase fluids.

An improved solution accurately predicts of an underground pipe's likelihood of leaking. A data-driven approach uses a combination of information acquisition, classification, regression and/or machine learning. The replacement of underground pipes can be prioritized. Pipe data is inputted and processed. Potential features within the cleaned data is used in pipe life of failure prediction models. The importance of the potential features is ranked. The most important features are extracted and applied to a likelihood of failure model that is created based on historical data and machine learning. Future likelihood of failure for each pipe in the network of pipes can be predicted using the model.

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.

Electromagnetic logging tools are optimized using synthetic logs for the purpose of pre-job planning and accuracy/resolution estimation. One, two and three-dimensional forward modeling are used to generate accurate inspection tool responses. A radial one-dimensional (R1D) electromagnetic forward model is also used to compute an approximate log. By constructing non-linear mapping functions between the R1D model-based log and the 2D model-based log, and mapping the R1D synthetic log using the non-linear mapping functions, a quasi 2D log is computed. The quasi 2D log is processed using model-based inversion, thereby providing estimates of pipe parameters. By analyzing the estimates of pipe parameters, tool performance metrics are obtained and analyze to determine the performance of the tool. The tool parameters are adjusted in order to optimize the performance metrics.

The present invention relates to a method for calculating a head loss coefficient and branch pipe flow distribution of a multi-point water intake. The method includes the following steps: inputting and determining a structure and size information of the multi-point water intake; determining a head loss coefficient; determining a head loss coefficient form of a confluence port; pre-estimating or adjusting a trial flow; performing trial calculation on the head loss coefficient of each branch pipe; comparing the head losses calculated by two flow paths; and carrying out overall calculation. According to the present invention, the flow of each branch pipe is adjusted and the head loss coefficient is repeatedly calculated by utilizing iterative calculation of the head loss coefficients of the flows in two directions, so that the head loss and the flow distribution proportion can be finally and accurately calculated.

Provided is a method of automatically forming a pipe, the method including inputting a design file to a program for automatically extracting information for forming a pipe, automatically extracting, from the design file, information about a cutting point for dividing a pipe included in the design file into a plurality of pipes and information about a bending point of each of the plurality of pipes, and transmitting, to a forming device for forming the pipe, pipe forming information including the cutting point and the bending point.