Multi-channel machine learning model-based inversion

A method for identifying a collar using machine learning may include acquiring one or more measurements from one or more depth points within a wellbore including a tubular string, training a machine learning model using a training dataset to create a trained machine learning model, and identifying at least one hyperparameter using the trained machine learning model. The method may further include 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 hyperparameter, 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.