Artificial Intelligent Approaches in Petroleum Geosciences

Cranganu, Constantin

Artificial Intelligent Approaches in Petroleum Geosciences
  • 出版商: Springer
  • 出版日期: 2024-07-16
  • 售價: $5,810
  • 貴賓價: 9.5 折 $5,520
  • 語言: 英文
  • 頁數: 277
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031527143
  • ISBN-13: 9783031527142

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

This book presents cutting-edge approaches to solving practical problems faced by professionals in the petroleum industry and geosciences. With various state-of-the-art working examples from experienced academics, the book offers an exposure to the latest developments in intelligent methods for oil and gas research, exploration, and production. This second edition is updated with new chapters on machine learning approaches, data-driven modelling techniques, and neural networks.

The book delves into machine learning approaches, including evolutionary algorithms, swarm intelligence, fuzzy logic, deep artificial neural networks, KNN, decision tree, random forest, XGBoost, and LightGBM. it also analyzes the strengths and weaknesses of each method and emphasizes essential parameters like robustness, accuracy, speed of convergence, computer time, overlearning, and normalization.

Integration, data handling, risk management, and uncertainty management are all crucial issues in petroleum geosciences. The complexities of these problems require a multidisciplinary approach that fuses petroleum engineering, geology, geophysics, and geochemistry. Essentially, this book presents an approach for integrating various disciplines such as data fusion, risk reduction, and uncertainty management.

Whether you are a professional or a student, you can greatly benefit from the latest advancements in intelligent methods applied to oil and gas research. This comprehensive and updated book presents cutting-edge approaches and real-world examples that can help you in solving the intricate challenges of the petroleum industry and geosciences.

商品描述(中文翻譯)

本書介紹了針對石油產業和地球科學專業人士所面臨的實際問題的前沿解決方案。透過來自經驗豐富的學者的各種最先進的實作範例，本書提供了對於油氣研究、勘探和生產中智能方法最新發展的了解。本書的第二版更新了有關機器學習方法、數據驅動建模技術和神經網絡的新章節。

本書深入探討了機器學習方法，包括進化算法、群體智慧、模糊邏輯、深度人工神經網絡、KNN、決策樹、隨機森林、XGBoost 和 LightGBM。它還分析了每種方法的優缺點，並強調了穩健性、準確性、收斂速度、計算時間、過度學習和正規化等重要參數。

整合、數據處理、風險管理和不確定性管理是石油地球科學中的關鍵問題。這些問題的複雜性需要一種多學科的方法，融合石油工程、地質學、地球物理學和地球化學。實質上，本書提出了一種整合數據融合、風險降低和不確定性管理等各種學科的方法。

無論您是專業人士還是學生，都可以從應用於油氣研究的智能方法的最新進展中獲益良多。本書全面且更新，呈現了前沿的方法和實際範例，能幫助您解決石油產業和地球科學中的複雜挑戰。

作者簡介

Constantin Cranganu is a professor of geophysics and petroleum geology at Brooklyn College of the City University of New York. He obtained a Ph.D. degree (ABD) from the University of Bucharest, Romania (1993), in geophysics and another Ph.D. from the University of Oklahoma (1997) in geology.

Before coming to Brooklyn College, he worked at "Al. I. Cuza" University of Iasi, Romania, and the School of Geology and Geophysics of University of Oklahoma. His main research covers various areas of petroleum geosciences: oil and gas generation, abnormal fluid pressures in sedimentary basins, gas hydrate exploitation, identification of gas-bearing layers using well logs, geostatistics, etc. Lately, Prof. Cranganu started using artificial intelligent approaches in his petroleum-related research. He published many books, peer-reviewed articles, book reviews, and essays. His paper, "Using gene expression programming to estimate sonic log distributions based on the natural gamma ray and deep resistivity logs: A case study from the Anadarko Basin, Oklahoma", (co-author Elena Bautu), published in Journal of Petroleum Science and Engineering in 2012 was nominated for ENI Awards 2012.

In 2014, he was the author and the senior editor of "Artificial Intelligent Approaches in Petroleum Geosciences", Springer, 1st edition.


作者簡介(中文翻譯)

Constantin Cranganu 是紐約市立大學布魯克林學院的地球物理學和石油地質學教授。他於1993年在羅馬尼亞布加勒斯特大學獲得地球物理學的博士學位（ABD），並於1997年在奧克拉荷馬大學獲得地質學的另一個博士學位。

在來到布魯克林學院之前，他曾在羅馬尼亞的「阿爾·I·庫扎」雅西大學和奧克拉荷馬大學的地質與地球物理學院工作。他的主要研究涵蓋石油地球科學的各個領域：油氣生成、沉積盆地中的異常流體壓力、氣水合物開採、利用井測資料識別含氣層、地質統計等。最近，Cranganu 教授開始在與石油相關的研究中使用人工智慧方法。他出版了許多書籍、同行評審的文章、書評和隨筆。他的論文「使用基因表達編程估算基於自然伽瑪射線和深度電阻率井測資料的聲波井測分佈：來自奧克拉荷馬州安納達科盆地的案例研究」（共同作者 Elena Bautu），於2012年發表在《石油科學與工程期刊》，並被提名為2012年ENI獎。

在2014年，他是《石油地球科學中的人工智慧方法》的作者和主編，該書由Springer出版，為第一版。

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