... of machines to study complex industrial activity such as drilling and completions described in natural language and to apply reasoning and logic to automatically, and accurately provide quantitative analytics for faster well design as well as an expanded study of risk in historical wells, leading to lower...

... information) present significant challenges to traditional methods of incident classification and contextual understanding and are labor-intensive and error-prone. This paper addresses these challenges by proposing an approach that harnesses natural language processing (NLP) and computer vision techniques...

... the transformative potential of customized LLMs, capable of generating reports in just 10 minutes—compared to 4 hours manually—thereby revolutionizing labor-intensive processes and significantly improving work efficiency in the well logging industry. deep learning geologist well logging natural language...

... outcomes in detailed existed-well assessment tasks. agent geology geologist rock type artificial intelligence arxiv natural language application accuracy mechanism large language model manuscript deep learning machine learning interpretation agent framework curve reconstruction...

..., and service quality across geographically distributed drilling sites. deep learning artificial intelligence agent machine learning drilling operation vector database edge device procedure agent system automation enhanced observability & security suite sre team natural language database...

... and gas industry. geology well type artificial intelligence geologist prediction international petroleum technology conference time prediction application monte carlo simulation time estimation process natural language engineer ai tool implementation selection machine learning...

... Abstract Language models has powered a lot of applications and developments in the past years in different domains. One language model that became popular in the recent years is BERT which is used as a base for many different natural language processing tasks such as classification and question...

... Abstract Large Language Models (LLMs) are attracting an enormous amount of interest at the moment in many domains. Their general nature, and ability to "understand" natural language, has already stimulated multiple areas of research at our company. Here we successfully demonstrate a Natural...

... of these unstructured documents and their proper characterization with respect to E&P domain objects remain a significant challenge. To address this issue, we developed an - "AI-based unstructured document geotagging solution" that utilizes text mining, optical character recognition ( OCR ), natural language...

... fracturing artificial intelligence large language model equation compressibility coefficient petroleum science shale gas mudstone weijermar interference international petroleum technology conference iptc-23764-ms chatbot machine learning natural language coefficient fracture pearson...

... and sustainability through digital technologies. air emission operation artificial intelligence natural language climate change large language model helicopter reduction helicopter operation algorithm efficiency optimization offshore operation llm ghg emission consumption scheduling offshore...

... operational conditions and corresponding healthy sounds across various operating modes. The primary mechanism that downstream operators have started leveraging Generative AI today is through intelligent chatbot interfaces that process natural language text and based on the index created over large corpus...

... functionality internet of things natural language iot gateway requirement architecture hardware international conference foundation integration disruption utilization operation international petroleum technology conference transition Introduction The modern industrial landscape is evolving...

... and subcodes can be used to extract structured data out of the drilling reports for reporting purposes. machine learning natural language artificial intelligence drilling operation upstream oil & gas classification correcting classified activity drilling report natural language processing...

... network morphology. The approach in this paper provides a theoretical basis for flow simulation of stimulated reservoirs and optimization of fracture networks. natural language artificial intelligence hydraulic fracturing complex reservoir upstream oil & gas fracture tip fractal index...

... requirements including big data analytics, EQLS is future-proof. real time system data mining natural language Artificial Intelligence big data Upstream Oil & Gas query language domain query language ETP eql operation workflow application eql query query energy query language...

... to avoid breakouts related to chemical instability or shear failure even though the pore pressure profile may not necessarily require any further increase in the mud weight. Reservoir Characterization natural language wellbore integrity Artificial Intelligence drilling fluids and materials...

... through Natural language processing (NLP), and then use the data mining method to excavate the rules information. First of all, the words in the text are recombined through technologies such as Chinese word segmentation, part-of-speech labeling, named entity recognition and the like, the word...

... their effectiveness in information retrieval from textual databases from various sources. Moreover, the situational types where each technique may be beneficial are explored. machine learning natural language Artificial Intelligence Upstream Oil & Gas text mining application classification drilling...