Patent ID: 11914096
Assignee: HALLIBURTON ENERGY SERVICES, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method comprising:
disposing an EM logging tool in a wellbore;
acquiring one or more measurements with the EM logging tool from one or more depth points within the wellbore comprising a tubular string;
training a machine learning model using a training dataset to create a trained machine learning model;
identifying at least one inversion hyperparameter using the trained machine learning model and the one or more measurements;
creating a synthetic model, wherein the synthetic model is defined by one or more pipe attributes;
minimizing a mismatch between the one or more measurements and the synthetic model utilizing the at least one inversion hyperparameter and a cost function, wherein the cost function is defined as, F
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  ,, wherein x is a vector of N unknown model parameters which comprise a number of pipes, a thickness of the pipes, a magnetic permeability of the pipes, and an eccentricity of the pipes, wherein m is a vector which comprises complex-valued measurements acquired at different receivers and frequencies, wherein s(x) comprises predicted or synthetic responses, wherein Wm,abs and Wm,angle are weighting factor, wherein Wcal is a matrix of calibration constants, wherein Wx is a matrix of regularization parameters, and wherein xIG is a vector of initial guesses;
updating the synthetic model to form an updated synthetic model; and
repeating the minimizing the mismatch with the updated synthetic model until a threshold is met.