Abstract: A method for performing production engineering tasks includes receiving a question or instruction related to an oil and/or gas industry. The question or instruction is received by a large language model (LLM) agent. The method also includes selecting one or more tools from a plurality of tools using the LLM agent based upon the question or instruction. The tools include a data tool, a retrieval augmented generation (RAG) tool, a simulation tool, and an analytical tool. The method also includes generating output data related to the question or instruction using the one or more identified tools. The method also includes generating a response to the question or instruction using the LLM agent based upon output data.

Abstract: A method for building a production asset time-series foundation model includes receiving input data related to equipment. The input data includes (1) domain knowledge and equations related to the equipment and (2) metadata related to the equipment. The method also includes training the production asset time-series foundation model based upon the input data to produce a trained production asset time-series foundation model. The method also includes performing a downstream task using the trained production asset time-series foundation model. The downstream task includes forecasting, imputation, anomaly detection, history matching, health monitoring, or a combination thereof.

Abstract: A system, method, and computer-readable storage medium, of which the method includes receiving an image of a tool including a consumable object from a remote device via a network at a processor, decoding the image to identify the consumable object, using the processor, and determining a degradation characteristic, a consumption, or both for the consumable object by providing the decoded image to a neural network. The degradation characteristic represents a mode of degradation and the consumption represents an amount of degradation.

Abstract: A system, method, and computer-readable storage medium, of which the method includes receiving an image of a tool including a consumable object from a remote device via a network at a processor, decoding the image to identify the consumable object, using the processor, and determining a degradation characteristic, a consumption, or both for the consumable object by providing the decoded image to a neural network. The degradation characteristic represents a mode of degradation and the consumption represents an amount of degradation.

Abstract: A system, method, and computer-readable storage medium, of which the method includes receiving an image of a tool including a consumable object from a remote device via a network at a processor, decoding the image to identify the consumable object, using the processor, and determining a degradation characteristic, a consumption, or both for the consumable object by providing the decoded image to a neural network. The degradation characteristic represents a mode of degradation and the consumption represents an amount of degradation.

Abstract: A system, method, and computer-readable storage medium, of which the method includes receiving an image of a tool including a consumable object from a remote device via a network at a processor, decoding the image to identify the consumable object, using the processor, and determining a degradation characteristic, a consumption, or both for the consumable object by providing the decoded image to a neural network. The degradation characteristic represents a mode of degradation and the consumption represents an amount of degradation.