AI Applications and Emerging Trends in Petroleum Exploration and Development

This paper examines how AI is transforming petroleum exploration and development, addressing current applications and future directions. Machine learning is being used to enhance tasks like identifying rock types, reconstructing logging curves, and estimating reservoir parameters, showing promise in improving data processing and interpretation. In seismic analysis, computer vision helps with identifying initial seismic signals and detecting faults. Deep learning and optimization techniques are applied in reservoir engineering, enabling real-time waterflooding optimization and production forecasting for oil and gas. Data mining is also enhancing drilling, completion, and facility operations, leading to smarter equipment and integrated software. Looking ahead, AI in petroleum is poised to advance with intelligent production tools, automated data processing, and specialized software platforms. Future innovations are expected in digital basin modeling, fast imaging logging tools, advanced seismic systems, smart drilling and fracturing technologies, and real-time monitoring of injection and production zones.

Authors

Publication Details

Journal
International Journal of Innovative Science and Research Technology (IJISRT)
Published
2024-11-21
DOI
https://doi.org/10.38124/ijisrt/ijisrt24nov818
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
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article

AI Applications and Emerging Trends in Petroleum Exploration and Development

Praveen Kumar Mishra, Manish Kumar
International Journal of Innovative Science and Research Technology (IJISRT)
Reservoir Engineering and Simulation Methods
article

AI Applications and Emerging Trends in Petroleum Exploration and Development

Praveen Kumar Mishra, Manish Kumar
article en

Abstract

This paper examines how AI is transforming petroleum exploration and development, addressing current applications and future directions. Machine learning is being used to enhance tasks like identifying rock types, reconstructing logging curves, and estimating reservoir parameters, showing promise in improving data processing and interpretation. In seismic analysis, computer vision helps with identifying initial seismic signals and detecting faults. Deep learning and optimization techniques are applied in reservoir engineering, enabling real-time waterflooding optimization and production forecasting for oil and gas. Data mining is also enhancing drilling, completion, and facility operations, leading to smarter equipment and integrated software. Looking ahead, AI in petroleum is poised to advance with intelligent production tools, automated data processing, and specialized software platforms. Future innovations are expected in digital basin modeling, fast imaging logging tools, advanced seismic systems, smart drilling and fracturing technologies, and real-time monitoring of injection and production zones.

International Journal of Innovative Science and Research Technology (IJISRT)
Industry, innovation and infrastructure
Openalex Percentile: Top 72%
Reservoir Engineering and Simulation Methods
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AI Applications and Emerging Trends in Petroleum Exploration and Development — Praveen Kumar Mishra, Manish Kumar · International Journal of Innovative Science and Research Technology (IJISRT) (2024) | TGRS Research Map | TGRS