| CPC G06F 30/12 (2020.01) [G06F 8/315 (2013.01); G06F 30/27 (2020.01); G06N 20/00 (2019.01)] | 20 Claims |

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1. A computer-implemented method, comprising:
receiving historical well data corresponding to a well, wherein the historical well data comprises information about past operations of the well;
generating an expanded range of values for parameters used in a well model for the well, wherein the expanded range of values expands a range of values corresponding to the historical well data;
generating, using the historical well data and the expanded range of values, object-oriented object instances representing the historical well data, wherein each object-oriented object instance is an object configured to be used by the well model and comprising a combination of parameters within the expanded range of values;
executing the well model using the object-oriented object instances to generate result objects, wherein each result object is an object-oriented object instance representing a result of the well model;
generating, using the object-oriented object instances and the result objects, a hybrid well model variant of the well model that models combinations of the object-oriented object instances and the result objects;
passing, by an object-oriented application, a data object encapsulating the object-oriented object instances and the result objects to a machine learning model, wherein passing the data object occurs in an absence of database tables;
executing the machine learning model using the data object;
generating, in response to the executing, an electric submersible pump (ESP) optimization dashboard displaying suggestions for production improvements for a well; and
implementing user-selected suggestions to change settings on ESPs used in the well.
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