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 ...
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 surv...
Artificial Intelligence in oil and gas is the use of computer systems to control and monitor oil and gas wells. Then machine learning is also used in oil and gas to predict the best places to drill. How computers are useful in petroleum industry?
This study offered a detailed review of data sciences and machine learning (ML) roles in different petroleum engineering and geosciences segments such as petroleum exploration, reservoir characterization, oil well drilling, production, and well stimulation, emphasizing the newly emerging field of unconventi...
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...
A typical Recurrent Neural Networks include Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU) and Simple RNN has been developed to predict oil and gas production. The results have shown that machine learning gained good results in the early stage of the production phase and the ...
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...
diagnosis spatiotemporal pattern network (STPN) with convolutional neural network (CNN) have been used as a hybrid model. This deep learning methods has been used for the analysis of bearing fault data set as a case study. The performance of STPN-CNN has been evaluated based on accuracy ...
Petroleum Analytics Learning Machine (or PALM) system is a machine learning based, “brutally empirical” analysis system for use in all upstream and midstream oil and gas operations.
To avoid the need for the long processes involved in conventional manual analysis, we developed an automatic AVO analysis method for common midpoint (CMP) gathers through using machine learning (ML) with a convolutional neural network (CNN). To deal with complicated seismic data, the network was...