Abstract: A method involves detecting primary entities in a document, involving determining that a subset of the primary entities are associated with a first primary entity type, and determining a second primary entity type of one of the primary entities. The method further involves processing the primary entity of the second primary entity type to determine a secondary entity type of the primary entity. The secondary entity type is a subcategory of the second primary entity type. The method also involves hierarchically organizing the primary entities into a document layout structure that includes a top level and a child level. The top level is established by the first subset of primary entities based on the first primary entity type identifying the first subset as headings, and the child level is established by the primary entity based on the second primary entity type, the child level identifying the secondary entity type.

Abstract: Systems, computer-readable media, and methods are provided. Relevant documents related to a specific entity are identified based on document metadata. Text and associated spatial coordinates are extracted based on relevant document pages. Significant document entities and associated spatial locations are identified. Page ranking is based on the extracted text and the spatial coordinates, the significant document entities, and image vector representations of the pages. A deep learning language model that utilizes the text and the spatial coordinates, layout information of the document entities, and the image vector representations of the pages is used to extract the user-defined attributes from the relevant document pages. First attribute values associated with the user-defined attributes are aggregated from the pages of one of the relevant documents into a single record. Second attribute values associated with the user-defined attributes are aggregated across the relevant documents.

Abstract: A method involves obtaining query pressure transient analysis (PTA) data from a well associated with a reservoir, and obtaining a selected class of physics models from a multitude of classes of physics models using a first machine learning model operating on the query PTA data. A physics model in at least one of the multitude of classes of physics models includes a well model and a reservoir model. The well model and the reservoir model are parameterized with model parameters having model parameter values. The method further involves obtaining a multitude of model parameter value estimates to form a parameterized query physics model of the selected class of physics models, using a second machine learning model operating on the query PTA data; and providing the parameterized query physics model to a user.

Abstract: Systems, computer-readable media, and methods are provided. Relevant documents related to a specific entity are identified based on document metadata. Text and associated spatial coordinates are extracted based on relevant document pages. Significant document entities and associated spatial locations are identified. Page ranking is based on the extracted text and the spatial coordinates, the significant document entities, and image vector representations of the pages. A deep learning language model that utilizes the text and the spatial coordinates, layout information of the document entities, and the image vector representations of the pages is used to extract the user-defined attributes from the relevant document pages. First attribute values associated with the user-defined attributes are aggregated from the pages of one of the relevant documents into a single record. Second attribute values associated with the user-defined attributes are aggregated across the relevant documents.

Abstract: A control system and method utilizing one or more processors that are configured to determine contaminant loading of blades of a turbomachinery compressor based on one or more environmental conditions to which the turbomachinery compressor is exposed and one or more atmospheric air inlet conditions of the turbomachinery compressor. The one or more processors then determine a corrosion contaminant concentration on the blades of the turbomachinery compressor based on the contaminant loading that is determined and determine an upper limit on or a distribution of potential corrosion of the blades of the turbomachinery based on the corrosion contaminant concentration, at least one of the environmental conditions to which the turbomachinery compressor is exposed, and the corrosion contaminant concentration that is determined.

Abstract: A control system and method utilizing one or more processors that are configured to determine contaminant loading of blades of a turbomachinery compressor based on one or more environmental conditions to which the turbomachinery compressor is exposed and one or more atmospheric air inlet conditions of the turbomachinery compressor. The one or more processors then determine a corrosion contaminant concentration on the blades of the turbomachinery compressor based on the contaminant loading that is determined and determine an upper limit on or a distribution of potential corrosion of the blades of the turbomachinery based on the corrosion contaminant concentration, at least one of the environmental conditions to which the turbomachinery compressor is exposed, and the corrosion contaminant concentration that is determined.