Abstract: Hydraulic fracturing data can be processed by a trained machine learning model to identify hydraulic fracturing well data characteristics corresponding with hydraulic fracturing events. The model can be trained using pre-processed hydraulic fracturing well data including multiple data channels. The trained model can then be fed hydraulic fracturing well data to identify stage start times, stage end times, and instantaneous shut-in pressure values among other well data events.

Abstract: Embodiments of the invention provide methods and systems for or providing automated assistance in making a decision such as selecting a product when shopping. According to one embodiment, a method of providing automated decision assistance can comprise presenting a user interface for selecting between a plurality of products identified in a product catalog. A question and answer session can be conducted via the user interface. Each question in the question and answer session can be selected based on a current context of the question and answer session and a relevance of each of the plurality of products identified in the product catalog to the current context of the question and answer session. At least one of the plurality of products identified in the product catalog can be suggested via the user interface based on results of the question and answer session.