Energy

Cheat Sheet | Large Language Models+ For Scientific Research

Jul 5, 2023

Large Language Models+ For Scientific Research Updated August 2023 LLMs and Tools for R&D To help scientists and researchers navigate the increasing number of advanced artificial intelligence (AI) options, Enthought’s experts put together this summary of Large Language Models (LLMs) and related tools that are most relevant for R&D updated as of early August 2023.…

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Enthought | ChatGPT, Large Language Models, Generative Artificial Intelligence

WEBINAR: What Every R&D Leader Needs to Know About ChatGPT and LLMs

Jun 29, 2023

View Webinar-on-Demand Live webinar held on June 27, 2023 Overview ChatGPT and the explosion of advanced Large Language Models (LLMs) are disrupting every industry. We are now living in a new age of AI with an unprecedented pace of advancement. This paradigm shift is forcing all businesses, including innovation-driven companies in the life sciences and…

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Enthought | The Lab of the Future

5 Tips to Kickstart Your Journey to the Future-Proofed R&D Lab

Oct 21, 2022

5 Tips to Kickstart Your Journey to the Future-Proofed R&D Lab   Despite an increase in digital transformation efforts across all industries, 70% fall short of their objectives. For science-driven organizations whose core innovation center is the R&D lab, success can be even more out of reach. To build the digital lab of the future,…

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10X Efficiency Gain and Improved Classification Using Deep Learning

Dec 7, 2021

Use AI techniques to efficiently extract mineralogy and grain size statistics from thin sections Thin sections provide the closest examination of in situ rock properties, essential for accurate reservoir characterization and reserves estimates. Standard analysis techniques such as point counting yield the types of constituent minerals and their shape characteristics, however this is a time…

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Integrating Weather and Renewable Energy Sources Data for 2.5 Million Viewers

Mar 13, 2021

Educating and developing a culture of responsible energy consumption The EnergizAIR project is presented both to show the innovative technology and methodology to solve the challenge, and to demonstrate Enthought’s time-proven expertise in designing and delivering solutions. The EnergizAIR project ran from 2010-2012, with phase 2 continuing into 2015. EnergizAIR is a European Commission, Intelligent…

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Manual Processes for CSEM Replaced by Computational Tools and Strategies

Feb 5, 2021

Shell needed a way to effectively visualize a new scientific measurement Controlled-Source Electromagnetic sounding (CSEM) is a new tool for marine oil exploration. Sensitive electric and magnetic field detectors are deployed to the seafloor over a prospect. A ship then tows a low-frequency electric source over the detectors. Variations in the electromagnetic properties of the…

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Predicting Pore Pressure From Very Limited Data Sets

Feb 5, 2021

ConocoPhilips wanted to make pore pressure predictions with limited data sets Logs from two wells and a limited set of 2D and 3D seismic were the only data available to model subsurface pressure. With this limited data set and available software, it was difficult for CoPEG to develop confident models, as well as visualize comparisons…

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AI/Machine Learning Techniques Quantify AVA Seismic Analysis Uncertainty

Feb 5, 2021

Help ConocoPhillips apply advanced AI techniques to Amplitude Versus Angle (AVA), seismic analysis Amplitude Versus Angle (AVA), seismic analysis is a well-established oil exploration tool. A set of seismic data around a particular point looking at a particular depth under ground can be summarized by numbers called attributes. Different rock properties, like being filled with…

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Model-Based Approach to Rock Physics Improves Predictions

Feb 5, 2021

ConocoPhillips wanted a more flexible way to model rock physics An important activity in characterizing reservoirs  is constructing models of rock physics, which represent how properties of rocks result in observable characteristics. This model-centric approach contrasts with an analysis-based approach, which reasons backwards from observables to rock properties. The process used in the model-centric approach…

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Applying Machine Learning to Subsurface Data Reduces Uncertainty

Feb 5, 2021

Overcome slow and tedious nature of core analysis Core analysis provides ground truth data of rock properties, and can be time consuming and expensive to collect. Often, measured properties are known only at plug locations within the core, and conventional sampling can miss important heterogeneity that is critical for determining reservoir properties. Core analysis generates…

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