.... The proposed solution utilizes large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and chain-of-thought reasoning to extract structured data (such as fees, escalations etc.) from contracts, perform analyses, and generate natural language responses. It enables use cases like...

... short-term memory (LSTM) were used. However, these had limitations related to spelling errors, acronyms, and miscellaneous symbols. Subsequently, the decision was made to transition to Large Language Models (LLMs). To address it, this paper proposes a novel approach using LLMs for multi-label drilling...

... is proposed—a framework that, to the best of our knowledge, represents the first application of Text-to-SQL using LLMs within the Oil & Gas (O&G) domain, specifically designed to handle complex database structures. This paper presents a novel solution that bridges the gap between drilling engineers...

... Abstract This paper presents a novel approach to training evaluation using Language Models (LLM) and Generative AI (GenAI) to build a classification model. The study aims to develop a resource-efficient solution for analyzing training rubrics and transcripts, thereby enhancing the assessment...

... (LLMs) and information retrieval methods to translate natural language descriptions of failures into structured insights. A comprehensive knowledge base, populated with operational log data and expert- validated solutions, empowers the LLM to perform in-context learning and iterative diagnosis...

... ; Liu et al. 2024 ; Amin et al. 2024 ). by taking into account the large AIGC model (LLM) abilities including understanding, conversation, content generation, as well as the sets of RLHF based techniques including chain of thought (COT) ( Wei et al. 2023 ), prompt engineering ( Wei et al. 2023 ), LoRa...

... matter experts. Large Language Models (LLMs) supported by Retrieval Augmented Generation (RAG) systems can help expedite information retrieval and processing. However, Enterprise-scale LLM implementation faces challenges, that include confidentiality, scalability, handling hallucinations, handling domain...

... Abstract The primary objective of this research work is to harness the advanced capabilities of Artificial Intelligence (AI), specifically Deep Learning (DL) and Large Language Models (LLMs), to develop a comprehensive system for detecting and understanding the causes of oil spills. Our...

... denotes the causal relationship with reversed causality based on SME knowledge. Table 3 shows two sample queries sent to the LLM (left) and the responses back from the LLM (right). In the first example, the LLM is asked about the causal relationship between Critical Corrective Maintenance Delay...

... The developed methodology requires LLM to be applied for the knowledge graph creation and therefore apply higher computational requirements, while the preceding steps are less computational demanding. One of the advantages of the described method is that LLM is applied on the formed clusters...

... simulation reservoir simulation assistant simulation model reservoir engineering knowledge base agent engineer simulator information simulation result application reservoir engineer vector store llm gen ai callback agent Introduction In this introduction, we will focus on two main...

...., BERT with 330M parameters and GPT-2 with 1.5B parameters) and demonstrate surprising capabilities ( Wei et al. 2022 ) in solving a range of complex tasks. As a result, the research community coined the term "large language models (LLMs)"1 for these large PLMs ( Zhao et al. 2023 ), and they have...

..., the chatbot can be configured with optional confirmation or cancel prompts to clarify the conversation. Once all slots are complete, the chatbot fulfills the user's intent by providing answers. This involves querying databases using LLM, generating charts, performing NLP based search using cloud native search...

... and provide recommendations at a frequency suitable to the operator's business process requirements. australia government requirement application operator recommendation dataset mim llm upstream oil & gas natural language operational efficiency consideration maintenance inventory...

... Although there has been significant progress in applying LLMs across various domains, their potential remains largely untapped. Given the complexity of industries such as oil and gas and the diverse range of possible applications for these models, it is crucial to continue researching...