SPE 181015 Natural Language Processing Techniques on Oil and Gas Drilling Data by M. Antoniak, Maana, et al. OTC 27577 Assessment of Data-Driven Machine-Learning Techniques for Machinery Prognostics of Offshore Assets by Ping Lu, American Bureau of Shipping, et al. SPE 181037 Big Data Analytics for Prognostic Foresight by Moritz von Plate Drilling activities in the oil and gas industry have been reported over decades for thousands of wells on a daily basis, yet the analysis of this text at large-scale for information retrieval Sequence Mining and Pattern Analysis in Drilling Reports with Deep Natural Language Processing Julio Hoffimann, Youli Mao, Avinash Wesley, and Aimee Taylor´ Abstract—Drilling activities in the oil and gas industry have been reported over decades for thousands of wells on a daily basis, yet the analysis of this text at large-scale for informa- Advanced Drilling Techniques Horizontal Drilling. Horizontal drilling starts with a vertical well that turns horizontal within the reservoir rock in order to expose more open hole to the oil. These horizontal "legs" can be over a mile long; the longer the exposure length, the more oil and natural gas is drained and the faster it can flow. More
Sequence Mining and Pattern Analysis in Drilling Reports with Deep Natural Language Processing Julio Hoffimann, Youli Mao, Avinash Wesley, and Aimee Taylor´ Abstract—Drilling activities in the oil and gas industry have been reported over decades for thousands of wells on a daily basis, yet the analysis of this text at large-scale for informa- A search function based on natural language processing and machine vision could make this possible. After the documents are digitized and organized in the digital database, AI-based Information extraction software could help geoscientists find new locations to drill based on past geolocation data the oil and gas company can access. One way to solve this challenge is the use of Natural Language Processing. Most drilling reports and well logs from oil fields are written long-hand. Thus, an approach for getting the collective knowledge or the data from the field experience of retired drilling chiefs is to use Natural Language Processing to process these reports. In oil & gas operations adoption and realisation have been slow. However slowly AI and machine learning in oil & gas are taking hold. Machine Learning in Oil & Gas Applications can Transform the Industry. Machine learning in oil & gas will not only improve the customer experience but can also help to keep costs low across the process.
Well drilling monitoring is an essential task to prevent faults, save resources, and take Natural Language Processing Techniques on Oil and Gas Drilling Data. 4 May 2018 For example, with this approach, engineers can predict oil wells' optimal decisions related to oil and natural gas exploration, development, and production creates the core capabilities of AI, such as natural language processing, speech and and manipulation techniques for data stored within them. The Open Petroleum Data Project is a non-profit decentralized organization. Natural Language Processing modern machine learning techniques should be capable of filling in the missing data through Hook Load and Block Height readings. Whitepaper : Minimizing the environmental impact of oil and gas drilling
Interest in natural language processing (NLP) has grown in earnest since Turing's learning techniques on the data to create intelligence and then output that April 2015: Drilling for Alpha in the Oil and Gas Industry – Insights from Industry. Well drilling monitoring is an essential task to prevent faults, save resources, and take Natural Language Processing Techniques on Oil and Gas Drilling Data.
Recent advances in search, machine learning, and natural language processing have made it possible to extract structured information from free text, providing a new and largely untapped source of insights for well and reservoir planning. However, there are major challenges involved in applying these techniques to data that is messy and/or This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 181015, “Natural-Language-Processing Techniques on Oil and Gas Drilling Data,” by M. Antoniak, J. Dalgliesh, SPE, and M. Verkruyse, Maana, and J. Lo, Chevron, prepared for the 2016 SPE Intelligent Energy International Conference and Exhibition, Aberdeen, 6–8 September. We look at some of the use-cases where AI is being applied for data search and data discovery in the energy and oil and gas sectors below. Natural Language Processing Techniques for Oil and Gas Drilling Data. The oil and gas industry is usually divided into three major operational sectors: upstream, midstream, and downstream. Upstream involves The proposed natural-language processing (#NLP) techniques in this paper, allow unstructured data to be searched, organized, and mined, allowing engineers to leverage the underlying insights without having to read through entire databases.