自然语言处理技术在油气勘探开发的应用前景——以ChatGPT为例
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作者单位:

中海油能源发展股份有限公司 工程技术分公司,天津 300450

作者简介:

李桂仔(1988—),男,硕士研究生,工程师,主要从事油气勘探开发大数据及人工智能方向研究,(E-mail)ligz3@cnooc.com.cn。

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基金项目:

海油发展重大专项(HFKJ-ZX-GJ-2023-02)。


The prospects of applying natural language processing technology in oil and gas exploration and development: A case study of ChatGPT
Author:
Affiliation:

CNOOC EnerTech-Drilling & Production Co., Ltd., Tianjing 300450, P. R. China

Fund Project:

Supported by Major Special Program of Cenertech(HFKJ-ZX-GJ-2023-02).

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    摘要:

    随着人工智能的快速发展,自然语言处理技术的应用逐渐扩展至各领域,如金融、医疗、教育和电子商务等,它为多元业务领域提供了更高效、智能的解决方案。研究重点讨论了ChatGPT在油气勘探开发领域的具体应用场景、面临的挑战以及未来发展的可能性。利用Python调用ChatGPT的API(应用程序接口),通过实例解析,说明ChatGPT在油气勘探开发领域,在诸如信息检索、决策支持、客户服务等方面具有显著的优势。这些优势表现为提高工作效率、优化决策制定、提升客户服务和沟通质量,以及创新的方法解决问题。ChatGPT在编程方面的强大优势进一步提升人工智能在油气勘探开发领域中的应用效率。ChatGPT支持利用专业知识和数据对模型进行微调,构建专属油气勘探开发智能专家,数据的数量和质量决定模型精准度和专业性。同时,需要应对挑战,如回答的真实性、数据质量,模型的准确性以及数据安全等问题。未来,ChatGPT的发展趋势可能表现为增强理解能力、创新能力、智能交互能力,而且ChatGPT可以与数据湖进行高效融合,实现在数据查询、故障预测、报告自动生成、培训以及自动化工作流程等方面的应用。

    Abstract:

    With the rapid progress of artificial intelligence, the application of natural language processing(NLP) has expanded across various fields, such as finance, medical care, education, and e-commerce, offering efficient and intelligent solutions for diverse business arenas. This study primarily discusses the specific application scenarios, challenges, and potential future developments of ChatGPT in oil and gas exploration and development. Using Python to access the ChatGPT API, illustrative examples demonstrate its strengths in information retrieval, decision support, and customer service within this industry. These advantages translate into improved operational efficiency, optimized decision-making, enhanced customer service and communication, and innovative problem-solving methods. Additionally, ChatGPT’s strong programming capabilities further improve the efficiency of AI applications in this field. Fine-tuning ChatGPT with domain-specific knowledge and data enables the development of dedicated intelligent systems for oil and gas operations, where the quantity and quality of data determine the model's accuracy and expertise. Nevertheless, challenges remain, such as response reliability, data quality, model accuracy, and data security. Future trends are expected to include enhanced comprehension, improved creativity, and greater interactivity. Furthermore, ChatGPT can be integrated with data lakes to support data querying, fault prediction, automated report generation, training, and workflow automation. With continuous upgrades and user-driving optimization, NLP technologies such as ChatGPT are anticipated to play an increasingly critical role in the oil and gas sector.

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引用本文

李桂仔,魏莉,尹彦君,冯高城,王凤刚,张震.自然语言处理技术在油气勘探开发的应用前景——以ChatGPT为例[J].重庆大学学报,2025,48(10):95-109.

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  • 收稿日期:2023-08-12
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  • 在线发布日期: 2025-10-20
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