Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a ...
the algorithms, without diving too deep into the theoretical aspects of the algorithms employed.Machine Learning in the Oil and Gas Industrycovers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering...
Digitalization of workflows using machine learning and advanced analytics is the new go-to strategy to add business value in the oil and gas industry. Enterprises strive to embrace these new technologies; but struggle to put their models in production, deliver tangible results and obtain favorable ...
Machine Learning has offered novel ways to increase automation, efficiency, and productivity in many sectors - including the oil and gas industry. Its ability to find patterns in huge volumes of data has made machine learning into a highly effective tool, thanks to the amount of informa...
Machine Learning and Data Science in the Oil and Gas Industryexplains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the...
MACHINE learningPROBLEM solvingGAS industryARTIFICIAL intelligenceREINFORCEMENT learningGEOLOGICAL mappingThe article describes the tasks of the oil and gas sector that can be solved by machine learning algorithms. These tasks include the study of the interference of wells, the classific...
These machine-learning algorithms are configured to predict Poisson's ratio (ϑ) and maximum horizontal stress (σH) from available well-log input data. A large dataset from three wellbores drilled though the Gachsaran Formation in the Marun oil field, the second largest in Iran, is used to...
Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applicationsdelivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The ...
A systematic quality assessment of Environmental Impact Statements in the oil and gas industry Sci. Total Environ., 572 (2016), pp. 570-585 View PDFView articleView in ScopusGoogle Scholar Anifowose et al., 2017 F. Anifowose, J. Labadin, A. Abdulraheem Ensemble machine learning: An unta...
Since the first neural network prototype was developed in 1957, machine learning has undergone multiple hype and bust cycles (AI winter). Today, machine learning is being deployed to help researchers across many different industries, such as pharmaceutical R&D, oil and gas, and agricultural science...